university microfilms international€¦ · left hand corner of a large sheet and to continue...
TRANSCRIPT
INFORMATION TO USERS
This m~terial was produced from a microfilm copy of the original document. Whilethe most advanced technological means to photograph and reproduce this documenthave been used, the quality is heavily dependent upon the quality of the originalsubmitted.
The following explanation of techniques is provided to help you understandmarkings or patterns which may appear on this reproduction.
1. The sign or "target" for pages apparently lacking from the documentphotographed is "Missing Page(s)". If it was possible to obtain the missingpage(s) or section, they are spliced into the film along with adjacent pages.This may have necessitated cutting thru an image and duplicating adjacentpages to insure you complete continuity.
2. When an image on the film is obliterated with a large round black mark, itis an indication that the photographer suspected that the copy may hav~
moved during exposure and tP'-us cause a blurred image. You will find.agood image of the page in the adjacent frame.
3. When a map, drawing or chart, etc., was part of the material beingphotographed the photographer followed a definite method in"sectioning" the material. It is customary to begin photoing at the upperleft hand corner of a large sheet and to continue photoing 'from left toright in equal sections with a small overlap. If necessary, sectioning iscontinued again - beginning below the first row and continuing on untilcomplete.
4. The majority of users indicate that the textual content is of greatest value,however, a somewhat higher quality reproduction could be made from"photographs" if essential to the understanding of the dissertation. Silverprints of "photographs" may be ordered at additional charge by writingthe Order Department, giving the catalog number, title, author andspecific pages you wish reproduced.
5. PLEASE NOTE: Some pages may have indistinct print. Filmed asreceived.
University Microfilms International300 North Zeeb RoadAnn Arbor, Michigan 48106 USA
SI. John's Road. Tyler's GreenHigh Wycombe, Bucks, England HP10 8HR
,; I. I
77-23,481
AHN, Chung ~S";i;, .~ 944\'DEVELOPMENT, EQUALITY,. AND POLITICALVIOLENCE: CROSS-NATIONAL ANALYSISOF THE CORRELATES AND CAUSES OFDOMESTIC POLITICAL VIOLENCE.
University of Hawaii, Ph.D., 1977Political Science, general
Xerox University Microfilms, Ann Arbor. Michigan 48106
DEVELOPMENT, EQUALITY, AND POLITICAL VIOLENCE:
CROSS-NATIONAL ANALYSIS OF THE CORRELATES AND
CAUSES OF DOMESTIC POLITICAL VIOLENCE
A DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THEUNIVERSITY OF HAWAII IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
IN POLITICAL SCIENCE
MAY 1977
By
Chung-Si Ahn
Dissertation Committee:
Michael Haas, ChairmanRichard W. Chadwick
Philip E. JacobGlenn D. PaigeYasumasa Kuroda
Helge H. Mansson
ABSTRACT
This study is an effort to bring an explicit theoretical vision to
the interpretation of political violence, its correlates, and causes.
Theoretical and empirical definitions of the term political
violence are first discussed in order to operationa1ize the concept
systematically. A dimensional analysis of 18 indicators of political
violence, collected across 81 countries for the period of 1960-1967,
delineated two types of mass political violence and two types of
governmental political violence, namely, Protest and Internal War, and
Political Restrictiveness and Provoked Repression, respectively.
The analysis proceeded to a test of major theories on the causes
of political violence. A series of hypotheses were first translated
into structural equations. Regression and path analyses were then applied
to uncover the precise structure (i.e., linear vs. nonlinear) and para
meter estimates of the variables in order to evaluate the relative power
of each of the hypotheses.
On the whole, the results contradict the commonly held view of the
functionalist model that governments with greater "capacity" and "will"
provide more effective political performance, thereby leading toward a
more equitable and stable political system. Accordingly, a revised model
of political violence is formulated incorporating variables operationa1ized
from the functionalist theory into an analysis of a competing paradigm,
based on conflict and power analysis.
The results of the test of the revised model are consistent with the
new theory. The revised model explained a much larger percentage of
variance in the variab1e~.
TABLE OF CONTENTS
ABSTRACT •••
LIST OF TABLES •
LIST OF FIGURES.
PART I. THE STUDY OF POLITICAL VIOLENCE
. • iii
• yii
• • .xii
CHAPTER I INTRODUCTION I
The Problem, Scope, Method and Plan of the Research. IData . • • . . . . . . . . . . . . . . 4
CHAPTER II POLITICAL VIOLENCE: DEFINITION AND MEASUREMENT • 8
Ideology and the Theory of Political Violence:Toward an Eclectic View • • • • • • • • • • • 8
Defining Political Violence: A Working Typologyof Variables. . . . . . . . . . . . . . . . . . . 13
Measuring Political Violence: Selection andOperationalization of Indicators ••Indicators of Protest • • •Indicators of Internal War.Indicators of Coercion. • • • •••Indicators of Repression. •
Factor Analysis of the Indicators: RevisedTypology and Measurement. • • •
Final Indicators of Political Violence
PART II. TESTING HYPOTHESES ON POLITICAL VIOLENCE
CHAPTER III ECONOMIC DEVELOPMENT AND POLITICAL VIOLENCE.
Theoretical Orientations • • • • • • • • • •Testing Hypotheses on Economic Development and
Political Violence. • • • • • • • • • •
2024272932
3438
45
45
55
. . .
CHAPTER IV SOCIAL MOBILIZATION, INSTITUTIONALIZATION ANDPOLITICAL VIOLENCE: THE "GAP" HYPOTHESES ••
Theoretical Orientation.Measurement of Variables
Social Mobilization IndexCapacity and Responsiveness of Government to
Meet Mass Demands ••Political Participation and Political
Institutionalization • • • • • • •
67
677272
73
77
v
Page
Testing the "Gap" Hypotheses with Cross-National Data • • • • • • • • • • • • • • • 82
Political Protest and "Gap" Hypotheses • 83Internal War and "Gap" Hypotheses. • • • • •• 88Provoked Repression and "Gap" Hypotheses • • • •• 93Political Restrictiveness and "Gap" Hypotheses 97Summary and Implications for a More Complete
Causal Model. • • • • • • • • • • • • • • • •• 102
CHAPTER V TOWARD A MULTIEQUATION CAUSAL MODEL • 104
Theoretical Orientation • • • • • • • 104Bivariate Effects of Intervening Variables on
Political Violence • • • • • • • • • • • • • . •• 109Bivariate Effects of Social Mobilization on
PoIitical Violence • • • • • • • • • • • • • 112Toward Multiequation Specifications • • • •• 123
Provoked Repression. • • • • • • • •• 123Protest. . . . . . . . . . . . . . .. 123Political Restrictiveness. • 124Internal War • • • • • • • • • • • 134
PART III. TOWARD A NEW THEORY OF POLITICAL VIOLENCE
CHAPTER VI SOME CHALLENGING HYPOTHESES • 151
Preliminary Observations. • 151The Logic of Political Performance: Perspectives
of Rival Models. • • • • • . • • • • • • • • 156Functionalism vs. Power and Conflict Model 156Politics and Social Equality: Perspectives
from Conflict Paradigm. • • • • • • • 161Social Inequality and Political Violence:
Empirical Hypotheses • • • • • • . • • • 166
CHAPTER VII SOCIAL INEQUALITY AND POLITICAL VIOLENCE:AN EMPIRICAL RESEARCH • • • • • • • • 175
A Note on the Problem of Data • 175Measurement of Variables. • • • • • • • • •• 177
Sectoral Disparity in Income Distribution. • 177Inequality in Land Distribution. • • • • • • 179Inequality in the Distribution of Personal Income. 181Strength of the Egalitarian Political Campaign 182Interaction Effects of Inequality and the
Extent of Egalitarian Political Campaign. 184Empirical Evaluation of the Hypotheses. • 186
Testing Research Proposition 1-1 • 186Testing Research Proposition 1-2 • • • • • • • 189
vi
Page
CHAPTER VIII DEPENDENCY, INEQUALITY AND POLITICAL VIOLENCE••
Introduction • • • • • • •Measurement of Variables •
Vertical Trade. • • • •Trade Partner Concentration and Trade
Commodity Concentration.Composite Index of Dependency •
Empirical Evaluation of the HypothesesTesting Research Proposition 2-1:
Correlational Analysis • • • •Testing Research Proposition 2-2:
Spurious Relationships • • • •
204
204206206
208209209
209
211
CHAPTER IX CONCLUSION: SUMMARY AND IMPLICATIONS. 216
APPENDICES:
An Overview of Major Findings••Implications for Further Studies • . ~
216221
APPENDIX I FACTOR ANALYSIS OF 18 'PROPOSED' INDICATORSOF POLITICP~ VIOLENCE (OBLIQUE ROTATION). • 227
APPENDIX II FACTOR ANALYSIS OF INDICATORS OF GOVERNMENTALPERFORMANCE: OBLI QUE ROTATION. • • • • • • • •• 230
APPENDIX III PERSONAL INCOME DISTRIBUTION: DATA AND SOURCES.. 231
REFERENCES CITED 241
Table
1-1
2-1
2-2
2-3
2-4
3-1
3-2
3-3
4-1
4-2.1
4-2.2
4-3.1
4-3.2
4-4.1
LIST OF TABLES
List of Countries Analyzed in the Study •
A Three Dimensional Classification of the PoliticalViolence Indicators ••. • • • • . •
A Typology of Political Violence: A Working Scheme••••
Dimensions of Political Violence: Summary ReportExtracted from Factor Pattern Matrix. • • • •• • • .
Indicators of Political Violence and Method ofCalculation . . . . . . . . . . . . . . . .
Linear Regressions of Political Violence on EnergyConsumption per capita, 1965.•••••
Curvilinear (polynomial) Regressions of PoliticalViolence on Energy Consumption per capita, 1965 • •
Curvilinear (logarithmic) Regressions of PoliticalViolence on Energy Consumption per capita, 1965 • •
Variables and Indices for Testing the "Gap" Hypotheses. •
Regression of Protest on Social Mobilization and Government Expenditure as percentage of GNP: Ratio InteractionModel . . . . . . . . . . . . . . . . . . . . . . . . . .
Regression of Protest on Social Mobilization andGovernment Expenditure as percentage of GNP: logMultiplication Model. • • • • • • • • • • • • • •
Regression of Protest on Social Mobilization andGovernment Responsiveness: Ratio Interaction Model
Regression of Protest on Social Mobilization andGovernment Responsiveness: log Multiplication Model
Regression of Protest on Social Mobilization andPolitical Institutionalization: Ratio Interaction Model •
Page
7
16
17
36
43
59
60
61
81
83
84
85
85
86
Table
viii
Page
4-4.2 Regression of Protest on Social Mobilization and PoliticalInstitutionalization: log Multiplication Model • 86
4-5.1 Regression of Protest on Political Participation andPolitical Institutionalization: Ratio Interaction Model.. 87
4-5.2 Regression of Protest on Political Participation andPolitical Institutionalization: log Multiplication Model. 87
4-6.1 Regression of Internal War on Social Mobilization andGovernment Expenditure as percentage of GNP: RatioInteract ion Model. • • •• • • • • • • • • • • • • 88
4-6.2 Regression of Internal War on Social Mobilization andGovernment Expenditure as percentage of GNP: logMultiplication Model • • • • • • • • • • • • • • • 89
4-7.1 Regression of Internal War on Social Mobilization andGovernment Responsiveness: Ratio Interaction Model. • 89
4-7.2 Regression of Internal War on Social Mobilization andGovernment Responsiveness: log Multiplication Model. • 90
4-8.1 Regression of Internal War on Social Mobilization andPolitical Institutionalization: Ratio Interaction Model.. 91
4-8.2 Regression of Internal War on Social Mobilization andPolitical Institutionalization: log Multiplication Model. 91
4-9.1 Regression of Internal War on Political Participation andPolitical Institutionalization: Ratio Interaction Model.. 92
4-9.2 Regression of Internal War on Political Participation andPolitical Institutionalization: log Multiplication MOdel. 93
4-10.1 Regression of frovoked Repression on Social Mobilizationand Government Expenditure as percentage of GNP: RatioInteraction Model. • • • • • • • • • • • • • • • • • • •• 94
4-10.2 Regression of Provoked Repression on Social Mobilizationand Government Expenditure as percentage of GNP: logMultiplication Model • • • • • • • • • • • • • • • • • •• 94
4-11.1 Regression of Provoked Repression on Social Mobilizationand Government Responsiveness: Ratio Interaction Model •• 95
4-11.2 Regression of Provoked Repression on Social Mobilizationand Government Responsiveness: log Multiplication Model.. 95
4-12.1 Regression of Provoked Repression on Social Mobilizationand Political Institutionalization: Ratio InteractionModel. . . . . . . . . . . . . . . . . . . . . . . . . .. 96
Table
ix
Page
4-12.2 Regression of Provoked Repression on Social Mobilizationand Political Institutionalization: log MultiplicationModel . . . . . . . . . . . . • . . . . . . . . . . . . .. 96
4-13.1 Regression of Provoked Repression on PoliticalParticipation and Political Institutionalization: RatioInteraction Model • • • • • • • • • • • • • • • • • • • 97
4-13.2 Regression of Provoked Repression on PoliticalParticipation and Political Institutionalization: logMultiplication Model. • • • • • • • • . • • • • • 97
4-14.1 Regression of Political Restrictiveness on SocialMobilization and Government Expenditure as percentageof GNP: Ratio Interaction Model. • • • • • • • • 98
4-14.2 Regression of Political Restrictiveness on SocialMobilization and Government Expenditure as percentageof GttP: log Multiplication Model. • • • • • • • • 98
4-15.1
4-15.2
4-16.1
4-16.2
4-17.1
4-17.2
Regression of Political Restrictiveness on SocialMobilization and Government Responsiveness: RatioInteraction Model • • • • • • • • • • • . • • • •
Regression of Political Restrictiveness on SocialMobilization and Government Responsiveness: logMultiplication Model. • • • • • • • • • • • • • •
Regression of Political Restrictiveness on SocialMobilization and Political Institutionalization:Ratio Interaction Model • • • • • • • • • • • • •
Regression of Political Restrictiveness on SocialMobilization and Political Institutionalization:log Multiplication Model. • • • • • • •
Regression of Political Restrictiveness onPolitical Participation and Political Institutionalization: Ratio Interaction Model. • • • • • •••
Regression of Political Restrictiveness on PoliticalParticipation and Political Institutionalization:log Multiplication Model. • • • • • • • • • • •
99
99
100
101
101
102
5-1 Stepwise Regression for Determinants of Protest 113
5-2 Stepwise Regression for Determinants of Internal Har. 114
5-3 Stepwise Regression for Determinants of PoliticalRestrictiveness . . . . . . . . • . . . . . • . . . . . 115
Table
5-4
5-5
5-6
5-7
5-8
5-9
5-10
5-11
5-12
5-13
5-14
5-15
5-16
5-17
5-18
7-1
7-2
Linear and Curvilinear Regressions of Protest onSocial Mobilization Index • • • • • • • • • • •
Linear and Curvilinear Regressions of ProvokedRepression on Social Mobilization Index • • • •
Linear and Curvilinear Regressions of Internal War onSocial Mobilization Index • • • • • • • • • • • • • • •
Linear and Curvilinear Regressions of PoliticalRestrictiveness on Social Mobilization Index. •
Linear and Curvilinear Regressions of PoliticalInstitutionalization on Energy Consumption per capita •
Linear and Curvilinear Regressions of PoliticalInstitutionalization on Social Mobilization Index
Stepwise Regression for Determinants of PoliticalRestrictiveness •• •• • • • • • • • • • • •
Stepwise Regression for Determinants of PoliticalInstitutionalization. • • • • • • • • •
Linear and Curvilinear Regressions of Voter Turnouton Energy Consumption per capita. • • • • • •
Linear and Curvilinear Regressions of Voter Turnouton Social Mobilization Index. • • • •
Linear and Curvilinear Regressions of GovernmentResponsiveness on Energy Consumption per capita •
Linear and Curvilinear Regressions of GovernmentResponsiveness on Social Mobilization Index • • •
Stepwise Regression for Determinants of Internal War••
Stepwise Regression for Determinants of Voter Turnout •
Stepwise Regression for Determinants of GovernmentResponsiveness. •• • • • • • • • • • • • • •
Partial Correlations Between Political Violence andSocial Inequality, Egalitarianism and MultiplicationEffects . . • . . . • . . • . . . . . ~ . . • . ~ , . .
Equality Variables Selected to Test ResearchProposition 1-2 • • • • • • • . • • • • • • • • • • • •
x
Page
119
120
121
122
127
128
132
133
138
140
141
142
144
145
147
187
192
xi
Table Page
7-3.1 Stepwise Regression for Determinants of Protest · · 195
7-3.2 Stepwise Regression for Determinants of Protest · · · 196
7-4.1 Stepwise Regression for Determinants of Internal War. · 198
7-4.2 Stepwise Regression for Determinants of Internal War. . · · 199
7-5 Stepwise Regression for Determinants of ProvokedRepression . . . . . . . . . . . . · . . . · · 202
8-1 Correlations of Dependency Variables with SocialInequality and Political Violence • • • • • • •• • • • 210
8-2 Testing Spurious Relationship Between Dependency andPolitical Violence. • • • • • • • • • • • • • • • • • • • • 213
9-1 Major Predictors of Political Violence: FunctionalistModel vs. Power Analysis. • • • • • • • • • • • • • • • • • 222
Figure
2-1
3-1
3-2
3-3
3-4
3-5
LIST OF FIGURES
An Empirical Typology of Political Violence Variables. • • •
Economic Development and Political Violence: Linear Model ••
Economic Development and Political Violence: CurvilinearModel. . . . . . . . . . . . .
Scatter Diagram of Political Protest across EnergyConsumption per capita, 1965 • • • • • • • •
Scat~er Diagram of Political Restrictiveness acrossEnergy Consumption per capita, 1965••••••
Scatter Diagram of Internal War across EnergyConsumption per capita, 1965 • • • • • • • • •
Page
39
49
51
62
64
65
5-1.1 An Extended Causal Model of Deutsch-Huntington Theory. • 106
5-1.2 A Revised Causal Model of Political Violence. 110
5-2 Provisional Path Model of Protest. • • • • • • 124
5-3.1 Recapitulation of Analyses on Political Restrictiveness. 125
5-3.2 Provisional Path Model of Political Restrictiveness. 135
5-4.1
5-4.2
5-4.3
9-1
Recapitulation of Analyses on Internal War • • • • •
Scatter Diagram of Voter Turnout across EnergyConsumption per capita, 1965 • • •
Provisional Path Model of Internal War •
A Model of Political Violence: A Synthetic View.
, . 136
139
148
224
PART I. THE STUDY OF POLITICAL VIOLENCE
CHAPTER I
INTRODUCTION
1. The Problem, Scope, Method and Plan of the Research
Those who stand for authority fear violence and attribute it to
the escapist acts of the powerless. They tend to conceive violence as
deviant, disruptive, and dangerous to the "stable" development of
society. Those who are outside of the power--either seeking for new
power or attempting to get rid of another's authority--often regard
violence or, at least, some forms of it as an efficient means to
secure "better" goals. Still others advocate violence as an ultimate
means of social and political justice. A few reject the necessity and
justification of political violence under any circumstances. l
The varied ideological background of different researchers is
reflected in the variety of rival approaches to the study of political
violence. The philosophy of inquiry explicitly followed in this study
is that, without presumptuously pretending to be ideology-free or value-
neutral, a more important question in scientific discourse and growth of
knowledge is to "criticize," "detect," and to "reduce" the error found
in incumbent hypotheses in favor of, hopefully, "challenging hypoth
eses,,,2 rather than quibbling with the sources of knowledge.
lGene Sharp, The Politics of Nonviolent Action (Boston: PorterSargent Publishers, 1973).
2This point is cogently expressed by such terms as a theory's
"explanatory incompleteness" by Hempel, and its "falsifiability,"
2
The primary motive which prompted me to embark upon the current
topic is to supply a humane attempt to answer to one of the raison
d'etre questions in the political affairs of mankind--name1y, the sub-
ject of political violence within the boundary of the sovereign
political systems. The subject has so far produced a multitude of
theoretical structuring and the proliferating quantitative analyses,
perhaps more than any other single topic in the field of comparative
political studies.
However, the fundamental problem here is that many of the studies
are atheoretical in the sense that they have not been completed with
theory-building in any specific and explicit manner. In addition, most
of the quantitative studies are concerned with finding correlates of
political violence, neglecting possible causal linkages among the
explanatory variables. The search for correlates has also been largely
limited to an examination of linear bivariate relationships which often
require an unacceptably strong ceteris paribus assumptions. Such
strategies, by examining only the linear and additive relationships, have
resulted in neglecting the possibil~ties of more complex causal order-
ings and indirect relationships.
The strategy I pursue is based on the assumption that the theoreti-
cal groundwork for the concerned topic requires an integration of
evidence and method. Empirical analyses also need to be based on more
complex models than has been customary. Moreover, in my opinion, the
"refutability" or "testability" by Popper. See Carl G. Hempel, "Explanatory Incompleteness," in May Brodbeck, ed., Readings in the Philosophyof the Social Science (New York: MacMillan, 1968), pp. 398-415; Karl R.Popper, Conjectures and Refutations (New York: Harper Torchbooks, 1968);and Popper, The Logic of Scientific Discovery (New York: Basic Books,1959).
3
correlates of political violence and associated measures of statistical
significance can no longer stand alone, untested for their political
significance and historical experiences. Consequently, my analysis
attempts a precarious marriage between a collage, derived by the inter
locking of alternative approaches and stream of evidence accumulated so
far, and a painting of a future history in which any of the individual
elements--hypotheses--can stand only in terms of the overall impression
they draw together within a given canvas.
The research design and procedure adopted herein is a sequential
model-building process, beginning from bivariate specifications, leading
to more complex ones, taking advantage of data, and integrating the
emerging result in a cumulative manner. A brief outline of the contents
and processes employed in this study is noted below.
In part I, political violence is initially conceived as a phenomenon
composed of several dimensions of structural and behavioral elements
which are closely related to the physical use of force. Multivariate
research, guided by such a formal definition, will then follow in order
to explain dimensions and interrelationships in the universe of political
violence.
Part II focuses on a series of hypotheses that have been put forward
in various forms by others, beginning from the direct effects of economic
development on political violence. The analysis of this part purports
both to evaluate the rival theoretical arguments with empirical data and
to provide some empirical foundation for the specification of a more
integrated causal model of political violence. Thus, in each chapter of
part II, a series of bivariate hypotheses is delineated, to generate an
4
adequate framework to analyze the causes of political violence. Equipped
with measures of major theoretical variables, hypotheses will be re-
formulated in terms of structural equations. Regression analysis is
used to unravel empirical estimates of the precise structure of each
of the variables postulated in the equation. The results of the
regression analyses will then be integrated into a causal model, derived
from a general theory, in the final chapter of this part.
In Part III, a discussion on the shortcomings of existing theories
is followed by the specification and requirements of a modified causal
model of political violence. Then, the analysis will proceed to fit
data to this model and to derive meaningful parameter values accordingly.
The study concludes with a summary of the major results of the
research and their theoretical implications for further research. Some
policy implications of the findings will also be explored.
2. Data
Since the focus of inquiry is the variation of political violence
at national level, the data base was confined to a macro-systemic level
of aggregate data. Fortunately, many of the data used in the current
study, especially in parts I and II, were available through published
sources and compilations such as the World Handbook of Political and
Social Indicators,3 Dimensionality of Nations Project Report,4 Cross-
3Char1es L. Taylor and Michael C. Hudson, second edition, WorldHandbook of Political and Social Indicators (New Haven: Yale UniversityPress, 1972), hereafter referred to as Handbook; Bruce M. Russet, et al.,World Handbook of Political and Social Indicators (New Haven: YaleUniversity Press, 1964).
4R. J. Rummel, et a1., Attribute of Nations: Data and Codes, 1950-1965, The Dimensionality of Nations Project, Research Report No. 65(Honolulu, 1973), hereafter referred to as DON 65.
5
Polity Time-Series Data,5 and so on. United Nations publications,
official reports of national governments, other international agencies,6
and scholarly sources7 were also carefully checked to draw reliable
comparative data on social security and income distribution. Data for
such measures as Trade Partner Concentration, Trade Commodity Concen-
tration, and Vertical Trade Index were made available by one of my
colleagues' dissertation research. 8
I have used a 1965 time point for most of the variables. When data
for this time point were not available, the nearest year was used
instead. These instances and sources for individual variables are
noted at appropriate places in the text.
The original data collection started with a list of 112 non-Communist
sovereign countries. After three months of an extensive effort to
5Authur S. Banks, Cross-Polity Time Series Data (Cambridge: TheMIT Press, 1971).
6Specia1 thanks are noted here to an anonymous correspondent of theInternational Bank for Reconstruction and Development who made availableto me a very useful bibliography of basic sources on size distributionof income and compilation of the data.
7Simon Kuznets, "Quantitative Aspects of the Economic Growth ofNations (VIII): Distribution of Income by Size," Economic Developmentand Cultural Change (January, 1963); Hollis Chenery, et al., Redistribution with Growth (London: Oxford University Press, 1974); Irma Adelmanand Cynthia T. Morris, Economic Growth and Social Equity in DevelopingCountries (Stanford: Stanford University Press, 1973); Bruce M. Russett,"Inequality and Instability: The Relationship of Land Tenure to Politics,"in Robert A. Dahl and Dean E. Neubauer, eds., Readings in Modern PoliticalAnalysis (Englewood Cliffs: Prentice Hall, 1968); Robert W. Jackman,Politics and Social Equality: A Comparative Analysis (New York: JohnWiley, 1975).
8Robert D. Wa11eri, The Political Economy of International Inequality:A Test of Dependency Theory (Ph.D. dissertation in Political Science,University of Hawaii, 1976). These indices are originally drawn fromrespectively; I.M.F., Directions of Trade: 1960-1970 (Trade Partner
6
collect as many countries' data as possible, the country list was
reduced to 81 in number as a result of the limited availability of data,
especially on income distribution and other equality variables. These
data proved to be most difficult to obtain. Also the income distribution
data is alleged to be least reliable since it is readily subjected to
distortion by political propaganda. Special care and various cross-
checks in alternative data sources were applied to improve the quality
of data. At the same time, analysis on this problem is limited to a
lower level sophistication, even at the cost of rigorous generalizability
of the research result. The 81 countries included in the study are
identified in Table 1-1
Concentration); United Nations, Yearbook of International TradeStatistics: 1960-1970 (Trade Commodity Concentration and VerticalTrade).
Table 1-1. List. of Cour.t.ries Analyzed in the Study
No. I Count.ry Abbrevia- No. Country Abbrevia-tion t.ion
Europe 41 T::.-inidod & Tobago TRI42 Barbados BDS
1 Austria AUS 43 Pueto Rico PeO2 Belgium BEL3 I Denmark DEN Asia4 Finland FIN5 France FRN 44 Burma BUR6 Germany(West.) GEW 45 Ceylon CBlY7 Ireland IRE 46 India IIID8 Luxemburg LUX 47 Indonesia INS9 Netherland NTH 48 Japan JAP
10 Norway NOR 49 Korea KOS11 sweden Stm .50 Halaysia MAL12 Switzerland SWZ 51 Pakistan PAl{
13 United Kingdom UNK 52 Philippine PHI14 Greece GRC 53 Taiwan TIiN15 Italy ITA 54 Thailand TAl16 Portugal POR 55 VietnaJll(Sout.h) VTS17 Spain sm
Middle EastNorth America
56 Iran nUl18 Canada CAN 57 Iraq IRQ19 U.S.A. USA .58 Israel ISR
.59 Jordan JOROceania 60 Lebanon LEE
61 Libya LEY20 Australia AUL 62 Sudan SUD21 Newzealand NEW 63 Turkey TUR
64 Egypt UARLatin America
Africa22 Argentina ARG23 Bolivia BOL 6.5 Horocco MOR24 Brazil ERA 66 Tunizia TUN2.5 Chile CHI. 67 Chad CHA26 Colombia COL 68 Dahomey DAtI27 Ecquador ECU 69 Gabon GAB28 Paraguay PAR 70 Ivory Coast IVO29 Peru I'ER 71 Kenya KNY30 Uruguay URA 72 Madagascar MDR31 Venezuela YEN 73 11auritius MTS32 Costa Rica COS 74 Niger NIR33 Dominican Rep. D0l1 75 Nigeria NIGJ4 E1 Salvador ELS 76 Senegal SEN35 Guatemala GUA 77 Sierra Leone smJ6 Honduras HON 78 South Africa SAF37 Jamaiea JA.'1 79 Tanzania TAZ38 Mexico MEX 80 Uganda UGA39 Nicaragua NIC 81 Zambia ZBA40 Panama. PAN
7
CHAPTER II
POLITICAL VIOLENCE: DEFINITION AND MEASUREMENT
1. Ideology and the Theory of Political Violence: Toward an
Eclectic View
Political scientists explain that domestic political conflictsl
and violence take place when political institutions fail to function in
their proper roles or where political elites lose authority and
legitimacy. Behind these explanations lie the assumption that govern-
ment or the political institutions possess a legitimate claim to a
monopoly of force. 2
The approach taken by this consensus (or equilibrium) model of
society conceives conflicts and violence as political aberrations and
"stability" as a normal (or desirable) state of politics. Political
violence in such studies is seen largely as the failure of the ruled in
complying with formal authority. It results from attempts by those
who are outside of the power and authority to undermine them and
challenge the monopoly by elites. As a result, the literature largely
identifies the agents of violence as insurgents and as anti-system,
lThe term conflict is used in this study as' a metaconcept ofviolence in the sense that conflict usually refers to a state of incompatibility in values, interests, or goals between parties, which isshort of a manifested use of force.
2See , Max Weber, The Theory of Social and Economic Organizations,translated by Talcott Parsons (New York: Free Press, 1947); TalcottParsons, The Social System (New York: Free Press, 1951); David Easton,The Political System (New York: Alfred A. Knopf, 1953); Samuel P.Huntington, Political Order in Changing Society (New Haven: YaleUniversity Press, 1968).
See also, Lewis A. Coser, The FunctionFree Press, 1956).
9
and the problem of "stable" political order is seen as the task of
creating and strengthening political institutions and control mechanisms
of politics. This orientation views social and political change as an
adaptive process of the system toward consensus-building or equilibrium.
An alternative view of violence is derived from the conflict model
of social science. 3 This model posits essentially that at every point
of social change disensus and conflict are normal phenomena. It is
naturally followed by the assumption that every society and political
process is based on the control and the coercion of some by others.
Simmel goes further from this and asserts that there is a positive
sociological function of conflict. Conflict, being "designed to
resolve divergent dualisms," is "a way of achieving some kind of unity,
even it be through the annihilation of one of the conflicting parties."
"This is roughly parallel to the fact that it is the most violent
symptom of a disease which represent the effort of the organism to free
itself of disturbances and damages caused by them.,,4 Scholars following
this model attribute political violence and unrest to a characteristic
of civilizationS and "a sign that men have begun to hope, "even unwisely,
against oppression and injustice. Kenneth B. Clark notes that,
3See, Ra1f Dahrendorf, Class and Class Conflict in IndustrialSociety (Stanford: Stanford University Press, 1959); Georg Simmel,Conflict and the Web of Group A!fi1iations, translated by K. Wolff andR. Bendix (New York: Free Press, 1955).
4Simmel, .2£.. cit., p. 13.of Social Conflict (New York:
5See, Barrington MOore, Jr., Social Origins of Dictatorship andDemocracy: Lord and Peasant in the Making of the Modern World (Boston:Beacon Press, 1966).
10
As studies on social disasters have demonstrated, peoplewho feel there is no escape submit to their fate: it isthose who see an exit sign and an open escape door whostruggle to reach it.
Furthermore, energies devoted to a struggle for constructive social change are clearly not simultaneously availablefor antisocial and self-destructive patterns of behavior. Inthose cormnunities such as Montgomery, Alabama, where Negroesmobilized themselves for sustained protest against prevailingracial injustice, the incidence of antisocial behavior anddelinquency decreased almost to a vanishing point during theperiod of protest. (Emphasis added.)b
Recently in his essay, deve1opmenta1ist Denis Goulet similarly writes
that:
Whether it is viewed as disruptive or constructive, conflictis always taken to be a stepping-stone to some terminal condition of solidarity or peace. The dynamism of conflict thusturns out to be a luminous principle of institution buildingand of development itse1f. 7
The difference between two models is not only ideological but also
has quite a distinctive consequence in regard to research on political
conflict and violence. In consensus models, the end of system
maintenance and stable pattern of authority can easily justify the means
of coercive force employed by the elite upon the mass in the name of
order and stability. Strong political institutions and a stable
authority structure are often espoused at the cost of substantive
political performance, for which the government supposedly finds its
6Kenneth B. Clark, "The Invisible Wall," in Peter Collier, ed.,Crisis: A Contemporary Reader (New York: Harcourt, Brace &World,1969), p. 55.
7Denis Goulet, World Interdependence: Verbal Smokescreen or NewEthic? (Washington: Overseas Development Council, 1976), p. 28. Seealso, Irving Louis Horwitz, Three Worlds of Development: The Theory&ld Practice of International Stratification (New York: Oxford University Press, 1966); Aristide R. Zolberg, "The Structure of PoliticalConflict in the New States of Tropical Africa," APSR, 62, 1 (March, 1968),pp. 70-87.
11
existing rationale. Theorists within the consensus paradigm often do
not consider governmental violence as political violence. Instead, they
tend to focus on "abnormal," "anti-system," "mass" violence, or what is
commonly referred to as "civil strife. ,,8 The scope of research among
consensus theorists has also been limited to examining the manifest
physical violence, and is rarely inclusive of the structural or in-
direct violence.
The conflict model posits political process as maintained by
coercion rather than consensus. Moreover, since the state of equilibrium
or consensus is seen as "abnormal" rather than normal, the model views
violence as largely resulting from coercion. System change being taken
basically to be a tension-producing process, conflict theory focuses more
upon the mutual responsiveness of political interactions and the out-
come of changes brought into the system than does the rival model.
Scholars associated with this orientation tend to be less prone to the
bias of prejudging governmental violence as legitimate. Rather, con-
f1ict theory explores more the structural conditions in which government
and the people interact and react to each other in regard to changes in
social, economic and political environment rather than merely looking
,into the behavioral manifestation of political conflicts. As a result,
the literature on violence within this paradigm is relatively rich in
the notion of "structural" or "indirect" violence. However, a few
notes should be made explicit on the overly inclusive connotation in the
term "structural."
8The term civil strife employed by scholars of this approach is notnecessarily inclusive of only physical violence. It may simply refer toprotest, strikes and demonstrations which are not actual physical attacksby people on another. However, the concept rarely includes violentactions by governmental agencies.
12
Emphasis on the notion of structural violence as an analytical
concept in studies on political development has produced two distinc-
tive traditions of theorizing. The first maintains that violence need
not be overt in objective structural conditions in order to be
acknowledged as "structural violence." This school insists that any
social system commits structural violence so long as it keeps one class
or group within its membership from enjoying social, cultural, economic,
or political benefits available to the other class or group.9 Denis
Goulet, for example, takes a similar position to this in his statement
cited below:
Underdevelopment is a chronic state of violence. • • • the adoptionof a gradualist path to social improvement may entail much complicity with violence. Revolutions also lead to violence. Thefirst form of violence is expressed in inhumanly high birth anddeath rates, degrading poverty, ignorance, and non-participationin significant decisions affecting the lives of countless men.Support given to a more visible and militant form of violence,revolutionary activity, likewise involves the loss of 1ife.10
The second approach focuses only on the type of structural con-
ditions that lead explicitly to manifest physical force. The approach
taken in defining the scope and operational mapping of the concept of
political violence employed in this study is primarily concerned with
9This is a rather abstract statement taken to be a pure typedefinition that may not be referred to concrete realities. However, Itake that the class conflict theory of Marx, the notion of violenceimplicit in the works of Franz Fanon (The Wretched of the Earth (NewYork: Glove Press, 1966)), Alber~ Camus (The Rebel (New York: VintageBooks, 1956)), etc., is similar to this. The modern imperialismtheorists, who posit that dependency, domination, and exploitation of onegroup or country over another constitute structural violence whether ornot they would actually lead or have led direct physical violence canalso be categorized into this school.
10Denis Goulet, The Cruel Choice: A New Concept in the Theory ofDevelopment (New York: Atheneum, 1975), p. 317.
13
the latter type of structural violence. It is not because I consider
the former type theoretically unimportant. Rather, it is because we
can deal with such structural violence more effectively by subsuming
it under the "political performance" variables, treating them as
exogeneous variables to' the phenomenon of political violence defined in
this study. Part III of this dissertation is devoted mainly to such
a purpose.
In the following section, a working definition of political
violence is proposed to integrate both the manifest behavioral and
overt structural aspects of political violence into a full theory of
political violence.
2. Defining Political Violence: A Working Typology of Variables
I will propose a theory for the structure of political violence in
this section. The theory will be tested with empirical data in the
following section. Political violence is defined in this study as an
overt act of structural or physical force initiated by political
motives, whose effects depend upon one or any combination of the
following strategic elements:
a) the existence or procurement of large-scale organizations whose
principal objectives are to evoke fear of violence and the use
of other physical force; or,
b) the actual or potential threat to use the means for physical
force; or
c) the actual use of the physical force.
The scope of this definition is limited to the boundary of an autonomous
sovereign political system. The working definition of political violence
14
is broad enough to help us formulate a tentative and exhaustive
typology of political violence indicators. ll
The motives of political violence are to maintain or change the
legal or political order of an existing system. The political motives
of violence are largely dependent upon who exercises it and for what
interests. Depending upon whether it is initiated by the official sector
of a political system or by an unofficial private sector, political
violence can be classified into mass-initiated violence and government-
initiated (official) violence. Thus, the agent of political violence
becomes our first criterion in classifying types of political violence.
The impact of political violence makes a crucial difference depend-
ing upon what kinds of action are principally adopted by the agents of
political violence. According to the strategy of change adopted by an
agent, we may locate the phenomenon of political violence on a
reactionary-incremental-revolutionary continuum. Again, to the extent
that the principal means applied to achieve an objective involves the
actual use of the physical force (or the threat of using it to evoke fear
of violence), we can further imagine a continuum of the means dimension,
ranging from threats to the use of severe physical force.
llNote that, at this point, the definition is also inclusive of"authoritative" use of physical force, which has seldom been the casein the conventional definition of political violence. Later on in theactual working list of the proposed indicators, we will use the term"authoritative" in its restricted scope and include only those thatare conceived as "reactionary" uses of physical or structural authority.For example, the use of police force to crack down on crimes in thestreets is not considered as political violence, while mobilizing policeforce to implement martial law constitutes political violence. But bothmay be "authoritative" uses of physical (police) force in the conventionaluse of the term.
15
A conceptual matrix can be drawn to map the universe of political
violence indicators in a unified theoretical system. Table 2-1 is
such a conceptual map. In order to comprehend all the theoretically
possible phenomena of political violence, one can complete the con-
ceptua1 map by creating new concepts and filling in operational in-
dicators accordingly. However, the necessity for using secondary data
to test our hypotheses on the causes and correlates of political violence
renders a direct use of the above framework as a way of defining
political violence variables to be impractical. Moreover, since our
main purpose here is to develop a typology of political violence
variables as a step toward establishing empirical hypotheses, rather
than an exhaustive typological theory, it is theoretically tempting to
focus more on certain central phenomena of political violence, even at
the cost of neglecting theoretically less important ones. 12 Consequently,
we may simplify the schema by collapsing Reactionary - "Normal" -
Revolutionary into a continuum from the Incremental to Radical dimension
of change strategy. By dropping the Threat-Revolutionary cell in the
table as is beyond'the scope of this study, we can simplify the three
dimensional conceptual framework into a two dimensional empirical
classificatory scheme of political violence variables. Table 2-2,
derived in this manner, represents our conceptual guidepost in mapping
the phenomenon of political violence empirically.
12For example, "normal" police operations, revolutionary propagandaactivities, and non-violent movements short of mass rallies or protestsare considered as less salient aspects of political violence for ouranalysis.
Table 2-1. A Three Dimensional. Classification of the PoliticalViolence Indicators
16
~- ends Objective of Political Change
~~c!C:
means ~ Reactionary "Normal" Revolutionary(incremental)
XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXXXXmass violence mass violence mass violence
XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXXXX
Vigilantism Protest Revolutionary Prop-Demonstrations aganda of insurgent
General Strikes groupsNon-violent resis-
Threat tance(i. e., Gandhiand !1.L. King)
XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXXXXX official X X official X X official XX violence XX violence X X violence X
Q)
XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXXXXgQ)
Legal and Police and In- "Agitprop" IM0
oM Political ternal Security Irredentist appeals I> Bestrictions Operations~ XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXXXXI0
oM mass violence mass violence mass violence+3 XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXXXXoMM0 Assassinations Riots Armed uprisings~
cti Coup d' etats Guerrilla warfare0
»~ XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXXXXQ)
Physical.~ X official. official. X X official XForce X violence violence XX violence X+3til XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXXXXXX
Purges and Capital Class purgesPhysical. punishmentSanctions Public Surveillance by
Political brutality secret policeArrests andExecutions
Surveillanceby secretpolice
17
Table 2-2. A Typology of Political Violence Variables.A Working Scheme
initiator of political violence
mass violence government violence•~e~~e:estsmeans t-------------------t& objectives
threat and
incremental
changeschange ~--..---~ status quo
I(incrementalism pr policy orientedconflicts)
potentiaJ.1violence
actuaJ.violence
xxxxxxxxxxxxxxx xxxxxxxx:xxxxxxfuITERNAL WAR ~ ~ REPRESSION 2x x x xxxxxxxxxxxxxxxx xxxxxxxx:xxxxxxrevolutionary ~---~ reactionary
(radiCalism, or~tructure-oriented[ violence)
physical .
force and
radical
changes
potential
t-------+-! violence
actualviolence
strategy
. of
political
violence
18
The four concepts in each of our classificatory cells are largely
self-explanatory. Protest is an overt act on the part of the private
parties in a political system to dramatize an injustice. Protest
activities are usually resorted to situations in which conflicts arise
in the arena of policy-oriented issues. The main power of protesting
groups is to threaten the regime by a demonstration of will that there
is a potential for anti-regime movements. Coercion is a counterpart to
protest, as initiated by the official sector of a polity. Coercive
effects may be evoked by the sheer size or resources devoted by regimes
to maintain ordinary internal political and military control. Coercion
can be measured more directly by looking into the degree of institution
alized political restrictions imposed upon the potential contenders by
an existing regime to maintain or strengthen internal political control.
Internal war is mass-oriented, large-scale and violent physical political
violence with a radical action strategy. Repression constitutes the
use of coercive force or physical structure by government in response to
mass uprisings, opposition movements and other perceived dangers to the
maintenance of political order under the existing regime.
The proposed scheme also has further important implications on
dynamics of political change. The agent of an action usually has an
explicit political interest in mind which he seeks to maximize by an
action strategy. The interests at stake in protest movements on the
part of the masses and coercive measures by a government mainly involve
changes in public policy or political arrangement within the frameworks
of existing legal or political structures. Therefore, the conflicts of
interests along this dimension tend to be predominantly issue-oriented,
19
and both parties are likely to find their differences basically referring
to the incremental changes. On the contrary, the main conflicts between
parties engaged in internal war or repression as a principal action
strategy are more likely to involve structural issues of a fundamental
sort. Therefore, the strategy most likely to be followed by two opposing
parties will entail negating the legitimacy'of the authority claimed by
the other party. Consequently, the dynamics of change brought by these
latter action strategies will result in a radicalism of either revolution-
ary or reactionary types and higher levels of structurally induced
violence.
When the process of incremental changes is swayed from one extreme
13to another, the dynamics of change are likely to bring into a polity
what Goulet calls palliative incrementalism, as opposed to the creative
incrementalism. 14 In addition, both protest and coercion, if unchannelled
and uncontrolled, are likely to escalate into internal war and repression.
In short, it should be empirically demonstrable that: (1) the proposed
scheme of classification will sort a set of diverse and heterogeneous
phenomena of political violence into more parsimonious classes that are
l3For example, the uncontrollable extent of mass political protestwill lead to, as Kornhauser fears, a mass society and resultant"praetorian" polity. On the other hand, an extreme sway toward governmental coercion means a totalitarian polity. William Kornhauser, ThePolitics of Mass Society (New York: The Free Press, 1959).
l4palliative incrementalism obstructs basic developmental change,often worsening the conditions set out to improve, and, thereby postponestreatment until the problem becomes incurable without more radicalmeasures. Creative incrementalism, on the other hand, breeds newpossibilities, reduces obstacles impeding authentic developments, and"propels society beyond immediate problem-solving toward new possiblefutures." See, Denis Goulet, The Cruel Choice, pp. 294-298.
20
sufficiently homogeneous to provide more precise explanation and
generalization; (2) there are empirical connections among different
types of political violence. That is, protest may correlate with more
coercion; coercion may be associated with increasing internal war and/or
more repression, and so on. Further hypotheses based on the typological
framework will be possible after we establish a firm empirical ground
on these points. The evaluation of the proposed framework by means of
empirical data will also allow us to revise, if necessary, the schema.
The revised typology and measures of political violence will then
enable us to test further hypotheses on the correlates and causes of
political violence. We will now turn to observe the world of political
violence.
3. Measuring Political Violence: Selection and Operationa1izationof Indicators
Our main objective in measuring political violence is to
empirically derive a set of dimensions out of all possible indicators.
Further analyses will become much simpler if a smaller number of
patterns can be identified which account for most of the variance of
those indicators, and can therefore be used in their place. The factor
analytic model is one of the most commonly used methods for this
purpose. 1S A few theoretical considerations, however, justify the use
of a particular factoring model as our logical choice.
1SFactor analysis selects factors on the basis of the intercorrelations among variables available to it, and is mathematicallydefined in such a way to maximize the explained variance of the variables.R. J. Rummel, Applied Factor Analysis (Evanston: Northwestern UniversityPress, 1970).
21
We expect our indicators to be correlated with underlying
dimensions of political violence which are conceptualized in Table 2.2.
That is, each indicator should be unambiguously correlated with one
of the four conceptual dimensions. Then, it is also expected that these
dimensions of violence are to be closely related to each other at the
same time. This judgment justifies the use of oblique rotation of a
principal component solution based on the complete matrix of all
variables in preference to separate analyses of each set of indicators
wh • h . lId' . 16~c represent S1Ug e conceptua ~mens~ons. Factoring such a
comprehensive correlation matrix will also serve the purpose of testing
the usefulness of the conceptual scheme developed in Table 2.2, since
the analysis makes possible an empirical determination of the uni- or
multi-dimensionality of each of the conceptual dimensions "relative,,17
to one another.
l6The latter is what Chadwick was logically compelled to do in hisstudies. For further discussions on this point, see Richard W. Chadwick,"An Empirical Test of Five Assumptions in an Inter-Nation Simulationabout National Political System," General Systems, Vol. XII, 1967, pp.177-192; also Chadwick, Developments in a Partial Theory of InternationalBehavior: A Test and Extension of Inter-Nation Simulation Theory, Ph.D.thesis (Northwestern University, 1966).
l7Unlike in the case of Chadwick's study where the use of unrotatedprincipal component factor solution of indicators representing a singleconcept is logically compelling, I could not do a completely a prioriclassification of the violence variables. Therefore, an empiricaldetermination of the dimensionality of the conceptual scheme is by itself a crucial step toward establishing further hypotheses. However, itshould be noted that determination of an empirical dimensionality by meansof factor analysis is only contextually valid, and, thus, it should beunderstood as "relative" to the context of the parameters provided to themodel. For example, when Rununel factored foreign and domestic conflictvariables apart from the larger set of data, he found three domestic andthree foreign conflict factors, whereas when they were factored as a partof the complete 235 variable matrix, only one domestic and one foreign
22
Three theoretical considerations dictated the selection of the
proposed indicators to be factor analyzed. The first is that the in-
dicators selected are expected to be unambiguously correlated with one
of the four dimensional concepts represented by each cell in Table 2.2.
The second criterion is that as many indicators should be included to
represent each cell as possible. Related to the second, our third
concern is that all four cells in the typological scheme should be
represented with less systematic sources of either over- or under-
representation of one against the others as possible as the practical
choice permits. Methodologically, this means that no single category
should have many more or much less numbers of indicators than any other.
The reason for this is that if one category is more over-represented
than others, the result of dimensional solution and unit profiles derived
as such (i.e., factor score indicators) may distort the basic dimensions
in reality.18
conflict factor appeared. This point came to my attention in the courseof discussions with Professor Chadwick. For further reference to theillustration on Rummel's study, see Rummel, "Dimensions of ConflictBehavior within and between Nations," General Systems Yearbook, VoL 8(1963), pp. 1-50; Rummel, The Dimensions of Nations (Sage Publications,1972), chapter 9.
18This is so because, as I have noted before, the dimensionalityderived by factor analysis is relative to the context of the parametersprovided to the system. This point is consonant with the theoreticalargument made by Michael Haas. He stated that, "in selecting indicators••• , the preferred procedure would be a random sample of all possiblemeasures." Michael Haas, International Conflict (Indianapolis: BobbsMerrill, 1974), p. 182.
On another occasion, he also claims that, "one must demonstratethat one's variables are a representative, randomly chosen sample ofindicators from a universe of all possible variables. Lacking such ajustification of one's sample of indicators, one cannot infer that one'sfactors are indeed basic dimensions." Haas, "Dimensional Analysis inCross-National Research," Comparative Political Studies, Vol. 3, No. 1(April, 1970), p. 6.
23
Our three theoretical criteria were again balanced against
practical constraints19 of research and the state of empirical data.
For the variables of which the stability of events may vary from year
to year, the averaging procedures of over-time frequencies are used
instead of data for any single year unit. In addition, to the researcher's
chagrin, the existing data which attempt to measure some variables
directly are so lean and unreliable that they do not warrant an adequate
reflection of the empirical reality. Therefore, some variab1es20 that I
wish to examine could only be traced by means of indirect statistical
indicators. Most of the indicators for coercion and some for repression
had to be sought in such a manner. 21
The indicators finally selected are listed and discussed below by
category.
19These are the criteria of reliability and prec1s10n, objectivityand cross-unit comparability, sensitivity, and economy of collectingdata. For a standard reference on these criteria, see, Ted Robert Gurr,Po1imetrics: An Introduction to Quantitative Macropo1itics (EnglewoodCliffs: Prentice-Hall, 1972).
20For example, legal or political restrictions, purges, arrests,and executions belong to these instances.
21That is, since a concept cannot be defined satisfactorily by aspecific measuring operation, inferences are made from the specificobservations to general phenomena. By this inference on the interchangeability of indicators to a substantive problem, we can measurephenomenologically not the same traits of a concept, but functionallyequivalent to it. For the logic and methodology of inferred measureme~t,
see, Adam Prezeworski and Henry Teune, The Logic of Comparative SocialInquiry (New York: Wiley, 1970), chapters 5 and 6. For further application of this method to comparative inquiry, see Hortense Horwitz andElias Smith, "The Interchangeability of Socia-Economic Indices," inPaul F. Lazarsfe1d and Morris Rosenberg, eds., The Language of SocialResearch (New York: Free Press, 1955), pp. 73~77; and Philip E. Jacob,et a1., Values and the Active Community: A Cross-National Study of theInfluence of Local Leadership (New York: Free Press, 1971), especiallychapter 8.
24
A. Indicators of Protest
1. Average annual frequency of non-violent demonstration for 1960-1967(Demonstration)
Demonstration is defined as a non-violent gathering of people
organized for the announced purpose of protesting against a regime,
government, or one or more of its leaders; or against its ideology and
related issues, intended or implemented policy, or lack of policy; or
against its previous action or intended action.
The following definitional criteria are salient for ~stab1ishing
coding rules for the variables: (a) The issues involved in the protest
actions should be perceived as significant at the national political
level. However, within this framework of issues, acts of demonstration
may be directed to all branches and levels of government. Events which
typically include demonstrations for or against foreign governments, its
leaders or its visiting representatives are included within the definition
whenever such a demonstration is reported to indicate opposition to the
demonstrators' own government; (b) The variables exclude protest actions
inside the formal structures of government. For example, election
meetings, rallies, and boycotts are excluded because such gatherings are
associated with a particular formal process of a government that is
unevenly distributed across countries and over time period covered,
thus, significantly endangering the comparability problem; (c) If
reported evidence indicates any destruction of property or bloodshed
more than marginal to a demonstration, the event is judged to have been
transformed into a riot and is coded as such even if it began as a
demonstration. If it is indicated that a demonstration terminated
peacefully, but that after a period of time a new crowd began rioting in
25
the same place and presumably over the same issue, then two events--one
demonstration and one riot--would be coded. 22 After averaging eight
years' data, the variable is transformed into natural log values to
reduce skewness in the distribution.
2. Average annual number of demonstration per 1,000,000 populationfor 1960-1967 (Demo/capita)
This variable is operationally derived by dividing the above
Demonstration by the population around the year 1965, and it is intended
to tap the magnitude of demonstrations in order to infer their political
significance. Theoretically, we expect that measurement of political
violence by aggregate total frequencies, normed by population, would
measure salience of issues. For example, the political significance of
ten counts of demonstration for a populous country may get lost
significantly compared to the effect of the same count for a small country.
Alternatively, one may argue that a small number of demonstrations can
have decisively important political impact despite the size of the
country and thus, that, it is a redundant procedure. We believe that
a more constructive solution of this theoretical controversy may be
found if we include variables operationalized in both ways into our
analysis. After the frequency data are normed by population, the variable
is transformed by means of natural logarithm in order to normalize the
distribution.
22This definition is from the source: Charles Lewis Taylor and
Michael C. Hudson, Handbook (1972), pp. 66 and 88-93.
26
3. Average annual frequency of riots for 1960-1967 (Riot)
A riot is a violent demonstration or disturbance involving a large
number of people acting spontaneously and tumultuous1y.23 "Violent"
implies the use of physical force which is usually evidenced by the
destruction of property by rioters, the wounding or killing of people
by fighting between rioters and the official authorities, the use of
riot control equipment, and by the rioters' use of various weapons.
Riots are also characterized by apparent spontaneity by most of the
participants and by tumultuous group behavior, which often brings
unpredictable acts of disorder. Reported riots also rarely involve a
small number of participants and, in most cases, a riot involves
hundreds or thousands of participants rather than tens. Therefore,
premeditated violent raids against property or persons which were
directed by opposition to the government were not coded as riots but as
armed attacks. Or if they were planned and directed by the government
against its opposition, they become governmental sanctions but not riots.
The data are taken from the Handbook, and transformed by natural logarithm.
4. Average annual number of riots per 1,000,000 population for 19601967 (Riot/capita)
This variable is acquired by dividing the Riot, variable by
population around the year 1965. Similar to the case of demonstration,
it is expected to tap different meanings of riots and, thus, is expected
to consist of a spearate measure from the mere frequency variable. Data
were likewise transformed by natural logarithms due to an excessive
skewness in distribution.
23Definitional notes are drawn from Handbook, p. 67.
27
B. Indicators of Internal War
1. Average annual frequency of armed attack for 1960-1967(Armed Attack)
Armed attack is defined as an act of violent political conflict
carried out by or on behalf of an organized group with the object of
weakening or destroying the power exercised by another organized group.
The following operational criteria distinguish an armed attack from
other variables: 24 (a) It is an organized violent act in that (i) it
is characterized by a systematic utilization of a wide variety of
weapons by the opposing parties in order to weaken or destroy the power
of another organized group, and (ii) it ~ypically results in bloodshed,
physical struggle, or the destruction of property. (b) It is a political
violence relevant to domestic cleavages, conflicts, and issues in a
state's political processes in that (i) it is organized by political
groups that wish to displace an established regime or gain for them-
selves substantial power or autonomy and (ii) the target of attacks
typically is a regime, government, political leader, or a prevailing
ideology, policy, or actions.
Therefore, all non-violent protests (Demonstrations), incidents of
Riots, acts' of non-political organized violence (such as crime that is
~ot observed to be directly relevant to domestic political cleavages,
conflicts, and issues), and acts of political violence organized and
initiated by foreign groups within the country are excluded within this
definition. Also excluded are confrontations of armed forces in time
of international war and security measures undertaken by governments in
24See, Handbook, pp. 67-68.
28
situations short of civil war and assassinations. The situation for a
colony in which the forces of metropo1e engage indigenous forces (e.g.,
independence movements) is, however, included in the definition of an
armed attack. Data are coded from the Handbook, and afterward trans-
formed into logarithmic values to reduce the skewness.
2. Average annual number of armed attacks per 1,000,000 Population for1960-1967 (Attack/capita)
This is derived by norming Armed Attack by the size of a country's
population. Data were transformed logarithmically in order to reduce
the skewness in the distribution.
3. Average annual number of deaths from domestic violence for 1960-1967(No. of Death)
Deaths from domestic political violence is the number of persons of
the country who reportedly were killed in conjunction with political
violence, such as armed attack and riots. The definition includes
victims who died while participating in foreign interventions inside
one's country but excludes foreigners and persons wounded during political
violence. It also excludes assassination victims, political executions,
deaths in enemy prisons, deaths in formal warfare or in border incidents
with other countries, and victims of criminal homicides. The source is
the Handbook. Data were transformed into logarithmic values due to the
skewness in the distribution.
4. Average annual number of deaths from domestic violence per 1,000,000Population for 1960-1967 (Death/capita)
No. of Deaths is normed by population size to create this variable.
A log transformation is applied to normalize the data.
29
5. Total number of irregular power transfer during the period of1960-1967 (No. of Coups)
Similar to the conventional definition of a coup d'etat, irregular
power transfer is defined as a change in the office of the national
executive from one leader or ruling group to another that is accomplished
outside the conventional legal or customary procedures for transferring
power in effect at the time of the event. The event usually accompanies
either actual physical violence or the clear threat of violence. No
qualitative assessment is made regarding the subsequent political
significance of the event; the coding criterion does not distinguish
whether an irregular power transfer eventuated in a fundamental change
in the political system (a political or social revolution) or the system
continued substantially unchanged except for the .irregularity of the
power transfer itself. No minimum tenure limit is imposed after it was
reported that a new leadership had actually replaced the old, arrogating
to itself the titles and functions of chief executive. Excluded from
the variable, according to the Handbook, are unsuccessful attempts to
overthrow incumbent executives, such as an abortive coup. The variable
is transformed logarithmically based on values of the total incidence
within each country during the period of 1960-1967.
C. Indicators of Coercion
A. Governmental expenditure as percentage of gross national pr~duct
(Government Expenditure)
The base year of this variable is 1965. Government expenditure
refers to the budgeted current and capital outlays of the national
government. This variable is included in the analysis primarily to see
if the procurement of large resources by government relative to that of
30
civilian sectors is related--even indirectly--to the organizational
resources of coercion. 25 Redemption of debt and certain capital
transfers are excluded, while grants to foreign governments are included
in above definition. (Source: DON No. 65)
2. Defense expenditure as percentage of gross national product(Defense Expenditure)
This variable is us~d as a proxy to the resources devoted to the
internal security forces. 26 Defense expenditures are defined as current
and capital expenditures to meet the needs of the armed forces and to
cover all expenditures of national defense agencies other than those
expenditures used for civilian projects. They include the distinguish-
able military component of such activities as atomic energy, space,
research and development, and para-military forces. Where possible,
military assistance to foreign countries, retirement pensions of career
personnel, and military equipment stockpiling are included, but civil
defense, civilian space exploration, and industrial stockpiling are
excluded. The base year of data collection is 1965. Data are
logarithmically transformed to reduce the skewness in the distribution.
(Source: Handbook)
3. Internal security forces per 1,000,000 working age population(Internal Security Forces)
Internal security forces include police forces at all levels of
government and such paramilitary internal security forces as gendarmeries,
25The problem of conceptual validity of this variable as a measureof coercion will be discussed later on in section 5 of this chapter.
26Police expenditure as a percentage of GNP would be more appropriatedata. But the data are unavailable. See section 5 of this chapter forfurther discussions on this variable as a measure of coercion.
31
active militias, and active national guards. Data for 1965 are log
transformed due to skewness. (Source: Handbook)
4. Index of the freedom of a country's press systems and broadcastingto criticize their own local and national government (Press FreedomIndex)
This variable is created by University of Missouri School of
Journalism. The score range is from -4.00 for least freedom to +4.00
for greatest freedom. The base year is 1965. (Source: Handbook)
5. Index of competitive and free election (Electoral Competition Index)
The competitiveness and freedom of an election is coded by the
following criteria,27 covering elections from 1960 to 1967 (Source:
Handbook):
"1" : no election within the time whatsoever, or marked by "extremedeviation"28 from the free and competitive norm, thus allowingno effective voter choice.
27These criteria are proposed by W. J. Mackenzie with the followingscheme:a. an independent judiciary to interpret electoral law.b. an honest, competent, non-partisan administration to run elections.c. a developed system of political parties, well enough organized to
put their policies, traditions and teams of candidates before theelections as alternatives between which to choose.
d. a general acceptance throughout the political community of certainrather vague rules 0 f the game, which limit the struggle for powerbecause of some unspoken sentiment that if the rules are not observedmore or less faithfully the game itself will disappear amid thewreckage of the whole system.
28The "extreme deviation" or rigged category, involves instances inwhich the fundamental electoral structure prohibits a competitive andfree choice for the voters, either among candidates or in the selectionof candidates. This may happen because there are irregularities inelectoral procedure, as in the case of code "2", or because the electionitself is annulled and its results immediately overturned. For example,elections are considered "rigged" when racial discrimination disenfranchises most of the voters or whenever there are single-party electionsin which the candidates are selected by the ruling group and not on localinitiatives.
32
"2" marked by "significant deviation"29 from the competitive andfree norm.
"3" competitive and free, with no manifest coercion of voters.
6. Index of horizontal lower distribution (Power Distribution Index)
This variable measures the extent of political centralization between
central government structure and municipality. The base year of the
variable is 1965. This variable is coded as follows:
"1" negligible horizontal power distribution
"2" limited horizontal power distribution
"3" significant power distribution (Source: DON No. 65)
7. Index of the freedom of political opposition (Freedom of OppositiE~
Index)
With the bas~ year of 1965, this variable is coded as follows:
"1" political opposition not permitted or groups not allowed toorganize for political actions (e.g., interest groups, politicalparties)
"2" only restricted political opposition allowed or groups to organizein politics, but oppositional role very limited and not allowedto campaign for control of government.
"3" political opposition mostly unrestricted or groups can organizefor political action and may campaign for control of government.
(Source: DON No. 65)
D. Indicators of Repression
1. Annual average incidence of governmental sanctions(Government Sanction)
29The "significant" deviation", refers to one or more of the follow-ing characteristics: elections accompanied by extreme violence; fraud;intimidation of voters; a boycott by one or more major political groups;the outlawing of any major parties; single-party systems; manipulation ofthe electoral system so as to guarantee results beforehand; and any othertampering with the electoral law and voting procedures to affect the outcome.
33
A governmental sanction is an action taken by authorities to
neutralize, suppress, or eliminate a perceived threat to the security
of the government, the regime, or the state itself. The definition
encompasses a variety of governmental units. However, all of them
share a conceptual unity; that is, specific responses by the govern
mental authorities to a perceived threat to political security of the
existing authority in conformity with the particular constitution of
the state. For example, a sanction against criminal behavior that has
no observed relevance to the political security of the state (e.g.,
police crackdowns of crime in the streets) is excluded from the
definition. Three major types of activities included in the definition
are: (a) Censorship: an action by the authorities to limit, curb, or
intimidate the mass media. (b) Restrictions on political participation:
an action by the authorities to restrict general political participation,
such as declaring martial law, mobilizing troops for domestic security,
newly instituting a curfew, or any other restrictive measure directed
against an individual, a party or other political organization. The
latter includes the removal of a governmental official because of his
political beliefs or activities, the banning of a political party or
acts of harassment against it, the arrest of opposition politicians on
grounds of state security, the exiling or deportation of persons who
engage in political actions or who express opposition regarded as
detrimental to the alleged national interest, and the arrest or detention
of persons reportedly involved in political protest actions, and
assassination attempts. (c) Arrests based on allegations of espionage:
actions by the authority in which one or more persons (national or
34
foreigners) are arrested or detained on charges of spying, sabotage,
or prohibited interference in the domestic politics of the state per-
ceived as a threat to internal security. Data are for the years 1960
to 1967 and are logarithmically transformed due to the skewness of the
distribution. (Source: Handbook)
2. Average annual incidences of governmental sanction per 1,000,000population for 1960-1967 (Sanction/capita)
This is derived by dividing Government Sanction by the population
of the country. Data are transformed into natural log values to reduce
the skewness in the distribution.
4. Factor Analysis of the Indicators: Revised Typology andMeasurement
All the indicators of political violence were factor-analyzed to
determine whether sets of indicators vary together in ways similar to our
original conceptual scheme of classification. Any significant diversion
of the result from the proposed conceptual grouping will guide us to
revise the working typology in the light of new empirical result. The
analysis will also enable us to choose the final indicators of political
violence so that they will replace the "proposed,,30 indicators and be
used in our subsequent analysis.
All 18 indicators were factor analyzed. Principal factoring without
iteration3l produced five factors with eigenvalues above 1.0.
30Unti1 they are empirically validated, we will call the above 18variables "proposed" indicators of political violence.
3lThis method which is called PAl in SPSS enables us to extractprincipal component factors which are defined as the exact mathematicaltransformation of the original variables used as the input in the factor
35
The five factors were subsequently rotated with an oblique solution.
The proportion of the total variance in the original data which was
accounted for by these five factors amounted to 80 percent, and all
18 variables loaded on one of the five factors. The loadings of factor
pattern matrix are summarized in Table 2-3. Complete output of the
program is reported in Appendix I.
Table 2-3 shows several important properties which deserve some
further discussions. First of all, the patterns rather clearly dis-
tinguish different empirical types of political violence. That political
violence is not a uni-dimensional phenomenon is well supported by the
result. It is also clear that, in general, political violence initiated
by the mass is empirically distinguishable from the one by the official
sector of a political system. In addition, the empirical meaning of the
frequency variables turned out to be distinctive from the magnitude
measures of political violence.
Protest and internal war dimensions are quite clearly in line with
our initial specifications. High associations of the frequency of
Governmental Sanctions with other two protest variables reveal a strong
reciprocal relationship to an extent that is empirically inseparable.
The result indicates that the variable Frequency of Governmental
Sanctions should be treated as an integral part of the protest indicators
rather than as a measure of repression even at a moderate cost of com
pounding the pure meaning of the latter concept. 32 However, a closer
analysis. Missing data were deleted from the analysis with pairwisedeletion option. Norman H. Nie, et al., SPSS: Statistical Packaze for theSocial Science, second edition (New York: McGraw-Hill, 1970), pp. 479-480.
320ne could either eliminate the frequency of Government Sanctionas a component measure of protest or rename the protest to include also
a .Table 2-). Dimensions of Political Violences Summary Report Ext.racted from
Factor Pattern Matrix
Conceptual. Dimensions ProtestInternal Repression CoercionWar
~Internal. Pt:ovoked Political Coercive
Protest. Restrlc-b ResourcesVariables War Repression tiveness &: Or~an-
izat ons
1. Demonstration 0.9S*c*2. Riots 0.84
). Gov't Sanction 0. 78*d
4. Deaths/capita *0.91*5. No. of Deaths 0.8)
6. Attack/capita *0.810.47 *7•.Amed Attacks 0.71
8. No. of Coups 0.46*
9. Demo/capita O.88*e
O. Riot/capita 86*eO.
1. Sanction/capita *0.76
Freedom of Opposition *2. -0.90
*). Press Freedom -0.89
4. *Power Distribution -0.87*il-5. Electoral. Competition -0.8)
6. Gov't Expenditure 0.88*
0.40 *7. Defense Expenditure 0.69*8. Internal. Security Force 0.67
a. Five dimensions with eigenvalues above 1.00 only are reported. Loadings ofless than 0.40 are not reported.
b. Original. loadings on t..'lis factor were given opposite signs to make the nameof t.he factor cOnsistent with the direction and scales of variables.
c. Asterisked are those used for final. indicators for respective dimensions(see text and Table 2-4). .
d~ This variable was proposed to measure Repression (see text).
e. These two variables were proposed to measun Protest (see text.).
36
37
examination of factors which are made of our measures of coercion and
repression poses several intriguing points with reference to our
original typology and its revision.
Though hardly surprising, variables included as measures of
coercion unambiguously separate themselves into two distinctive factors.
One pattern represents the size of organizations and resources devoted
by regimes to maintain internal control and stability, as indicated by
such variables as governmental expenditure, defense expenditure as a
percentage of gross national product, and police and other internal
security forces. We may call this factor Coercive Resources and
Organizations. The other seems to indicate the degree of political
permissiveness provided in the political system and taps a rather direct
and institutionalized aspect of coercion. Thus, we may call it as the
Political Restrictiveness (or permissiveness) factor. The two dimensions
of protest and internal war represent both mass-oriented and, at the
same time, direct and physical manifestations of political violence.
On the contrary, the factors of coercive resource and political
restrictiveness are elitist types and primarily capture the structural
elements of violence or repression which are imbedded in the organiza-
tional or institutionalized processes of government and politics.
However, the dimension which is composed of the three magnitude
variables--demonstrations, riots and governmental sanctions--captures
a partial meaning of the repression. The former causes a loss ofinformation obtained and empirically verified on the ground oftheoretical pureness. The latter is less tenable in view of the factthat three population-normed variables (Demo/capita, Riot/capita andSanction/capita) capture a rather unambiguous meaning of the concept"repression." Henceforth, we include the Governmental Sanction in thefinal measure of the Protest with an appropriate caution noted.
38
aspects of both physical and structural types of political violence.
More interestingly, this is also a unique factor in which mass violence
--that is, protest--and governmental violence overlap empirically.
This factor seems to draw typical political situations in which serious
protest activities are met by a high degree of physical governmental
sanctions. Historically, a prolonged political situation of this type
goes hand in hand with unstable regimes and with extremely repressive
means of political control, which in turn sets the stage for internal
war movements. Thus, we may infer this dimension as the Provoked
Repression factor.
On the basis of our discussions so far, we now are ready to state
an empirical taxonomy in accordance with the emerging empirical result,
visualized as Figure 2-1. As indicated in the figure, we have found
that two dimensions of mass political violence--Protest and Internal
War--are tapping the phenomena of physical political violence, whereas
the two sets of variables purported to measure coercion--Political
Restrictiveness and Coercive Resources and Organizations--are denoting
the structural element of political coercion. We also found that the
locus of the Provoked Repression factor is within the area in which the
physical violence and structure of governmental coercion are empirically
overlapping each other. Our next step is to index these taxonomic con
cepts by means of more simplified composite indicators so that our
analysis in the next stage can be facilitated.
5. Final Indicators of Political Violence
The method chosen to derive composite indicators of political
violence, in line with the result of factor analysis, is a straightforward
Fie;ure 2-1. An Empirical TyPology of Political Violence Variables
Political Violence1-•.-------------- i
Ee.ss Violence Gove~mental Violence
J J J
(Fh~~ical Political Violence)
!
•- - - - - I- - _I.
(Structure of Politic~
~ Coerc~on)
I .J !Provoked Political Rest- Coercive Resou~"Ces
Repression rictiveness and OrganizationsI I II I
IIII( Indicators l
WarIntema1
!..---
?rotest
W\0
40
arithmetic scoring of the means for standardized scores of variables
representing each factor. This method has a disadvantage of discounting
the weight of each variable according to the result derived from the
factor solution. The advantage~. of this method, however, is to make
the substantive meaning of the raw data more readily apparent. Though
less elegant mathematically than the factor-scoring method, it enables
us to capture a clearer substantive interpretation of data without the
loss of information entailed in the representative variables. 33
It should also be noted that, in most cases, the relative
weighting problem among the component variables does not involve any
serious decisional criterion. That is, differences of the magnitudes
of loadings of the proposed indicators on each dimension are so marginal
that no compelling empirical reasons are found to weight, for example,
Demonstrations more heavily than Riots in the making of a single (com-
posite) indicator of the Protest dimension. Neither is there any
theoretical reason to believe that a demonstration constitutes a more
important type of protest activity than does a riot. Therefore, a method
of index construction which treats each component on an equal basis (such
as z-scoring or mean-scoring) is taken in preference to a method which
may be conceptually more complex and difficult to comprehend at the
intuitive level. 34 The loading of coup d'etat on the Internal War
33Note that the dimensional analysis employed in the prior sectionwas used for a descriptive purpose and primarily as a data reductiondevice, and not as a causal model. Hence, it is not assumed that thevariables loaded in each factor are necessarily in causal relationships,but only that it is useful in generating composite measures of lessidiosyncratic nature cross-nationally than any single individual variable.
340thers advocate the use of a single representative variable thatloads most highly on each dimension. This method, however, is more
41
dimension is an exceptional case. However, this variable is loaded
significantly only on this dimension, and there is no theoretical reason
for a coup d'etat to be a less significant instance of Internal War than
the other four components: so it is treated equally to the others in
the making of the final indicator of the internal war dimension.
In Table 2-3, the variable measuring frequency of Armed Attack is
associated with the Protest factor as well as the Internal War factor.
The decision in this case was to determine on which factor the variable
was loaded more significantly. On this basis, it became a component
of the Internal War dimension.
Finally, the Coercive Resources and Organizations factor reported
in Table 2-3 is discarded as an endogenous measure of political violence.
The reason for this is partly conceptual, as well as empirical.
In the factor analysis the proposed indications of coercion split
onto two dimensions, namely, Political Restrictiveness and Coercive
Resources and Organizations. All the variables with high loadings on
Political Restrictiveness factor belong to organizational characteristics
or structures that are directly related to the degree of institutionalized
political restriction imposed by the regimes upon the potential con-
tenders for power and authority. On the other hand, variables with
high loadings on the latter factor indicate the relative size of
resources--monetary and personnel--available to the elite structure.
readily subject to the influence of idiosyncratic characteristics ofcountries, and causes a rather significant loss of information includedin other variables loaded significantly on each dimension.
42
Considering the fact that our variables may be contaminated conceptually
with other factors,35 it is difficult to justify that the factor is an
aspect of direct political violence.
These considerations lead us to conclude that the factor named as
Coercive Resources and Organization in our prior analysis measures the
"existence or procurement of large-scale organizations" potentially used
for evoking political violence, but it does not necessarily meet the
criteria of our definition of political violence. 36 That is, the data
do not warrant us to assert that its principal objective is "to evoke
fear of violence and the use of other physical force." Therefore, we
exclude this factor from our dependent variables (measures of political
violence) and treat it as exogenous to the system of the dependent
variables.
The final indicators of political violence that were chosen for
subsequent analyses are reported in Table 2-4, with respective methods
of calculation specified.
35For example, a higher proportion of GNP occupied by governmentalsector relative to the one by civilian sectors may be more amenable toindicate the potential capacity of the government to increase masswelfare level, while it can also be utilized for coercive purposes.Military expenditure may be contaminated by the fact that countriesengaged in international war devote a very high proportion of nationalresources for this purpose but not necessarily for the internal securitypurposes.
36Refer to section 2 (definition of political violence) of thischapter.
Table 2-4. Indicators of PoliticaJ. Violence and Method of Calculation
43
I .Types Concepts Factors
IComponent. Hethod of !Name of theIndicators CaJ.culation final Indicators
Physi,caJ.Protest Protest Demonstration mean z-scores Frotest(li=81 )
Riots of the threepolitical Gov'i Sanctionviolence
Internal InternaJ. INo.of Deaths mean z-scores Internal vIal.'Har "Tar Deat.hsfcapita of the five (1·;=81)
Armed AttackAttack/capitaNo.of Coups
Structure Repressior Pr~lVoked Sanction/ mean z-scores Provoked Iof "pm,slonIcapita of the three Repressi.on I
Riot/capita (N=81) IpoliticaJ.coercion Demo/capita
Coercion PoliticaJ. Press Freedom mean of the IPoliticaJ.Restrict- Freedom of four B.estrictive-iveness Opposition componentsa I ness (;"=80)
Power Distri- I
bution
IElectoralCompetition
Ia. The scale of these four component indicators were first reversed t.o
arrange them from least rest.rictiveness (scale 1) to the most (scaJ.e 3).Then, means are derived from those components of which data are available.
PART II. TESTING HYPOTHESES ON POLITICAL VIOLENCE
Introduction
The purpose of this part is to make a systematic attempt to examine
intrinsic merits and utilities of each theory's testable hypotheses in
the light of current data. Each hypothesis on determinants of political
violence will be first introduced. The concepts which constitute the
exogeneous variables to the system of political violence will be
operationalized next and data will be collected accordingly. The test
will be done via simple and multiple regression. ~esults of the parameter
estimates are considered "significant" if the F values associated are
significant at the 0.05 level. l
Once the test of bivariate relationships is completed, the empirically
observed relationships will be integrated into a multivariate causal
model based on inferences drawn from prevailing theories. This is done
in the final chapter of this part (Chapter V). Conclusions drawn from
this part will enable us to further revise the model in Part III.
lStrictly speaking, the test of significance is not fully appropriate to our sample of countries, since it is not randomly chosen.However, it provides a useful criterion to guard the confidence of theresult in view of the fact that the models should not be treated asfixed, and that the result may vary if we test them by another bodyof data.
CHAPTER III
ECONOMIC DEVELOPMENT AND POLITICAL VIOLENCE
1. Theoretical Orientations
Economic change is one of the most frequently cited factors for
cross-national variations in political violence. However, the precise
nature of relationship has been a matter of controversy in the literature
on comparative political studies. In the early 1960's, Lipset established
a popular theoretical generalization on the subject that democratic
political order is in a complementary relationship with an improvement
of national wealth. "The more well-to-do a nation," the author argues,
"the greater the chances that it will sustain democracy."l The thrust
of this assertion implies that the linkage of political order with the
economic aspects of society can be most parsimoniously captured by
means of a linear relationship. Since then, many scholars have used
national statistics to run analyses, comparing nations in terms of
different indicators of economic growth and political behaviors and
structures, based upon the implied theory and method of test specified
by such a linear formulation. 2
lSeymour M. Lipset, Political Man: The Social Bases of Politics(New York: Anchor Books, 1963).
2See , P. Cutright, "National Political Development: Measurementand Analysis," American Sociological Review, Vol. 28 (April, 1963);D. J. McCrone and C. F. Cnudde, "Toward a Connnunication Theory ofDemocratic Political Development: A Causal Model," APSR, Vol. 61 (March,1967); and N. H. Nie, G. B. Powell, Jr. and K. Prewitt, "Social Structureand Political Participation: Developmental Relationship," APSR, Vol. 63(June, 1969), and Vol. 63 (Sept., 1969). -----
46
This theoretical perspective is further supported by longitudinal
analysis of W. H. Flanigan and Fogelman. Utilizing historical data
across 1860-1960 for over sixty countries, they found that the most
violent countries tend to be those at the lowest levels of development,
with a decreasing incidence of domestic violence as countries are more
developed. 3 Thus, they inferred that political violence has an inverse
and linear relationship through time with increasing level of nations'
economic growth. Yet this linear negative hypothesis has been challenged.
Classical statements on the destabilizing and violence-inducing role
of the accumulation of wealth and industrialization in societies are
found in Marx's prophecy. All the methods for raising productivity in
the capitalist system, Marx says, are brought about at the cost of the
proletariat class. "Accumulation of wealth at one pole is, therefore, at
the same time accumulation of misery, agony of toil, slavery, ignorance,
brutality, mental degradation, at the opposite pole, i.e., on the side of
the class that produce its own product in the form of capital. ,,4 As
capitalist production expands, its associated contradictions culminate.
The discontent and protest of the proletariat grow through various stages
of capitalist development. They will eventually erupt into "the violent
3William H. Flanigan and Edwin Fogelman, "Patterns of PoliticalViolence in Comparative Historical Perspective," Comparative Politics,Vol. 3, No.1 (Nov., 1970), p. 12.
~arl Marx, Capital, Vol. I (Moscow: Foreign Languages PublishingHouse, 1954), Chap. XXV, Sec. 4. requoted from Clark Kerr, John T.Dunlop, Frederick H. Harbison, and Charles A. Myers, Industrialism andIndustrial Man: The Problems of Labor and Management in Economic Growth(Cambridge: Harvard University Press, 1960), p. 25.
47
overthrow of the bourgeoisie" in the form of "open revolution," and
finally reaches the crescendo of a revolution under the communists, Marx
argued.
Recently, economist Mancur Olson, Jr. 5 also emphasized destabilizing
elements concurrent or typically associated with increasing levels of
economic growth in developing nations, especially when combined with a
rapid rate of growth. Heilbroner also warned that the process of economic
development and the changes it imposes on and requires from a society
inherently carry "the latent potential of revolutionary upheaval," as
well as of "heightened international friction.,,6 Employing a case study
method on Argentina's development since 1870, G. W. Merkx claims to have
found, contrary to Lipset's observation, that Argentina "has become more
tUlstable politically" and suffe:Eed more rebellions as it has developed
economically. On the basis of this finding, he generalizes that "the
growth of an industrial sector in an export-oriented economy" will lead
to "an eventual takeover of government by a populist leader who combines
appeals to the working class in the name of social justice with appeals
to industrial entrepreneurs in the name of industrial deve10pment.,,7
According to this theorizing, we should expect that, other things being
5Mancur Olson, Jr., "Rapid Growth as a Destabilizing Force,"Journal of Economic History, 23 (Dec., 1963).
6Robert L. Heilbroner, The Great Ascent: The Struggle for EconomicDevelopment in Our Time (New York: Harper &Row, 1963), chapter 7.
7Gilbert W. Merkx, "Economics and History in the Study of Rebellions;the Aagentine Case," in Garry D. Brewer and Ronald D. Brunner, eds.,Political Development and Change: A Policy Approach (New York: FreePress, 1975), pp. 112 and 126. The examples of Germany and Italy inthe 1940's, contemporary experiences of a few Asian and Latin Americancountries also contradict Lipset's prediction.
48
equal, the level of political violence is a linear positive function
of the level of economic deve1opment. 8 Figure 3-1 is a graphic view
of the two rival linear hypotheses.
There are also a few works positing the basic relationship to be
a curvilinear one. One pioneering study of the historical experience in
European industrialization has offered an explanation that is dialectically
opposite to the Marxian projection. It claims to have found that protest
activities and violence in most industrializing societies peaked in the
earlier process and as industrialization proceeded, whence they have
declined in intensity. The authors conclude:
At the earlier stages, the break with the traditionalsociety is sharpest; the labor force is making the more basicand difficult adjustments to the discipline and pace of industry; the plant and work community are at the most formativestages; nationalist and social revolutions are also likely tobe occurring in addition to the introduction of modern industry;the reactions of workers are more direct and violent; the appealof utopias and grandiose schemes for transforming society islikely to be greatest in such periods. • • •
As time passes, formal organizations of workers emerge,and, as has been observed, the forms of overt protest becomemore disciplined and less spontaneous. The organizationsgradually become centralized, formalized, legitimatized, andviable. The industrializing elite develops its strategiesand means of controlling, limiting, or directing workerprotest. Protest expressions are stripped of the inchoateand volatile character of the early stages. Sporadic riots,
8The literature suggests that the relationship should hold notonly cross-sectionally but also through time within societies. However,the aggregate cross-sectional data we have in this study do not allowus to make any rigorous inferences about patterns through time withinpolities or across individuals within them. Only the cross-sectionalexamination will be done subsequently, hoping at the same time that itwill enable us to understand better the diachronic aspect of the rivalmodels and make inferences applicable to an expanded scope with varyinglevel and units of analysis. This point will be discussed more in thelast section of this chapter.
Figure 3-1. Economic Develo'Pment and Political Violence: Linear Model
high ........... Hp I Olson. Merkx hypothesis
Violence
Lipset. Flanigan & Fogelmanhypothesis
lowKpre-industrialized industrializing industrialized T -(time)
Economic Development*
... Industrialization and Economic Development is used as anintexchangeable 'term in the figure'
..\0
50
violence, explosive outbursts are replaced by an industrialrelations system for establishing and administering therules of the work place. 9
The thrust of this hypothesis has been supported by many quantita-
tive analyses utilizing cross-sectional data. For example, Feierabend
et al. report:
Among the very few countries that might be characterizedas yet untouched by the process of economic change, there isa tendency toward political quiescence •
Countries in the transitional stage of economicmodernization are the most beset by political turmoil •
Once the system approaches full modernization (asindicated by almost universal literacy) and its economyapproaches the high mass-consumption level (as indicated bya GNP per capita well above the subsistence level), politicalstability tends to reemerge. IO
Hibbs' regression analysis of mass political violence, using cross-
sectional data on 108 countries, also confirmed a tendency for indicators
of Internal War and Collective Protest to increase with initial
increases in economic development (measured by log Energy Consumption per
capita of 1960), but "on the whole" decline with higher levels of
industrialization. II The Kerr-Feierabend-Hibbs hypotheses can be
presented as HI in Figure 3-2.
9Clark Kerr, et al., .£R. cit., p. 209.
10Ivo K. Feierabend, Rosalind L. Feierabend, and Betty A. Nesvold,"Social Change and Political Violence: Cross-National Patterns," inHugh Davis Graham and Ted Robert Gurr, eds., Violence in America:Historical and Comparative Perspectives (New York: The New AmericanLibrary, 1969).
llDouglas A. Hibbs, Jr., Mass Political Violence: A Cross-NationalCausal Analysis (New York: John Wiley & Sons, 1973). Hibbs conceptualized mass political violence in terms of the Collective Protest andInternal War. His operationalization of the Collective Protest andInternal War are slightly different from ours also. See pp. 11-16.
Figure 3-2. Economic Development and Political Violence: Curvilinear 110del
high
Violence
low
.)""'-'-.~ .... ,,.' ,. I ,
, 'I" I',. ,
.I
I,II,,
;.:,I, TO
Kerr, Feierabend. Hibbs
HJ
: Davies. Lasch
"
----- L - ...
T
pre-industrialized industrializing industrialized
Economic Development
l)* T~ T denotes the range of hl~torical time in which thecountries in our sample can be located.
\It~
52
Considering the fact that most of the nations in the sample for
current analysis are either caught in transitional or already highly
industrialized stages, we might expect that the prevailing pattern is
decreasing political violence with increasing levels of economic develop-
ment. However, it would not be a linear negative relationship; as
countries become more industrialized, the corresponding decreasing level
of violence will lose its magnitudes. This pattern would be like the
logarithmic function depicted as H2 in Figure 3_2. 12
Finally, the "rise and drop" hypothesis provides another potential
explanation on the nature of the relationship between economic develop-
ment and political violence. The structure of reasoning in this explan-
ation is focused more on conditions which prompt individuals to engage
in revolutionary activities and less on the specific objective conditions
per se, Le., economic development. James C. Davies reasons:
Revolutions are most likely to occur when a prolonged periodof objective economic and social development is followed by ashort period of sharp reversal. The all-important effect on theminds of people in a particular society is to produce, duringthe former period, an expectation of continued ability to satisfyneeds--which continue to rise--and, during the latter, a mentalstate of anxiety and frustration when manifest reality breaksaway from anticipated reality. The actual state of socioeconomicdevelopment is less significant than the expectation that pastprogress, now blocked, can and must continue in the future.!}-
l2Note that Hz is a variation of the HI. The primary reason thatit is to be treated as a separate hypothesis is that the artifact ofnation sample--that is, there is no existing pre-industrialized country-may force us to be unable to test HI fully. If we pull the time axist l to t 2 , HI and HZ become identical.
l3James C. Davies, "Toward a Theory of Revolution," AmericanSociological Review, 27 (Feb., 1962), p. 6 (emphasis added).
53
The assertion that the development of a violence-prone state of mind is
more important than actual conditions of deprived status is consistent
with writings of Crane Brinton, Tocqueville and their fo11owers. 14 Two
interrelated empirical generalizations may be drawn out of this inter-
pretation.
One is the null hypothesis that posits no meaningful relation at
all between the objective state of socioeconomic development and extent
of political violence. Rumme1,15 although the study is conducted in a
different context from such a theory, found that domestic violence
variables and economic development indicators loaded on separate
dimensions when they are jointly analyzed. Michael C. Hudson16 also
reported that economic development, measured by energy consumption per
capita, exerts no "substantial influence on political violence and
instability." Both Rummel and Hudson inferred from these results that
economic development is unrelated causally with the extent of domestic
political violence.
An alternative generalization drawn from the rise-and-drop hypoth-
esis is that, due to the rising expectations of people undergoing rapid
14See , Crane Brinton, The Anatomy of Revolution (New York: Vintage,1965); Alexis de Tocquevi11e, The Old Regime and the French Revolution(New York: Doubleday, 1955); Ted R. Gurr, Why Men Rebel? (Princeton:Princeton University Press, 1970); Robert M. Fogelson, Violence AsProtest: A Study of Riots and Ghettos (New York: Doubleday, 1971),especially see Chapters 1 and 2.
15R• J. Rummel, "Some Empirical Findings on Nations and theirBehavior," World Politics, Vol. 21, No.2 (Jan., 1969), pp. 226-241.
16Michae1 C. Hudson, Conditions of Political Violence andInstability: A Preliminary Test of Three Hypotheses (Beverly Hills:Sage Professional Papers in Comparative Politics, Series No. 01-005,1970).
54
socioeconomic change, we should expect an increasing level of political
turmoil as the industrializing countries proceed beyond a certain
threshold along their journeys into the processes of economic deve1op-
mente Tocquevi11e and Brinton's studies consistently stated that the
period of improvement yields the expectations of further improvements.
When these slacken, rebellion follows. This scheme of "rising expectation"
and "re1ative deprivation" has been largely used to explain the protest
activities by Negroes in American society. The increasing wealth
accumulated in society has given formerly deprived classes a higher
degree of economic expectation and the improvement in general social
conditions than before--i.e., more education, better jobs, more political
participation and acceptance. Realizing the allocation of social values
do not meet their psychological expectations, they become more and more
frustrated. As a result, people become increasingly impatient with the
slow pace of social evolution and begin to resort more than before to
direct action of progressive or leftist kinds in character.
Although the reasoning is different from the theory of rising
expectations, the theory of the post-industrial society17 yields the
same empirical generalization. For example, Lasch contends that the
17This theury is dissenting to the early theories of post-industrialsociety which spoke of pluralism as an impending reality and postulatedthe defining characteristic of post-industrial society as a static socialorder resistant to change. The early theories also share together thebelief that the age of political ideological conflicts will wither awayfrom the post-industrial Western world if only they succeed in defendingit from the revolutionary forces from outside. Contrary to thisoptimistic view of post-industrialism, the works of J. Ellul, T. Roszak,Christopher Lasch and Alain Touraine see post-industrialism as anexacerbating source of dehumanization and "programmed" society; see,J. Ellul, The Technological Society (New York: Vintage, 1967); T. Roszak,The Making of a Counter Culture (New York: Anchor, 1969); Christopher
55
post-industrial society produces a new class of poor who are "marginal"
to the industrial system and "technologically superfluous," with access
only to the most menial jobs. Similar to this group are the students,
"who are removed from the working force and placed in educational custody
where they are exposed to a combination of bureaucratic repression and
dangerous ideas." Insofar as their demands cannot be met under existing
institutions, these groups, being alienated and politically more and more
conscientious, will pose a potential revolutionary threat to the system.
Also in view of the fact that the cities become less inhabitable,
the air and water more polluted, and cultural life more impoverished,
the politics of the post-industrial society becomes increasingly
polarized. As a result, we will see, the theory claims, that the post-
industrial order is "an inherently unstable form of society," "breeding
riot and rebellion" at home and an "endless series of emergencies"
abroad. This model approximates the third hypothesis (H3) in Figure 3-2.
In the following section, an attempt has been made to test these rival
hypotheses with cross-national data.
2. Testing Hypotheses on Economic Development and Political Violence
The empirical adequacy of various hypotheses concerning the effect
of economic development on the level of political violence can be
evaluated by examining the estimates of the results of the following
regression models:
Lasch, "Toward a Theory of Post-Industrial Society," in M. Donald Hancockand Gideon Sjoberg, eds., Politics in Post-Welfare State (New York:Columbia University Press, 1972) and Alain Touraine, The Post-IndustrialSociety, translated by Leonard F. X. Mayhew (New York: Random House,1971).
56
(3-1) -------- y = a + b1X1 + e ------------
(3-2) -------- y = a + b1X1 + b2
(X1
)2 + e ---
(3-3) -------- y = a - b1X2 + e ------,..-----
Linear Model
Curvilinear Model(Polynomial)
Curvilinear Model(Logarithmic)
where: Y: measures of political violenceXl: measures of economic developmentX2 : logarithmic transformation of economic developmente: stochastic disturbance
The argument of the linear-curvilinear relationship can be tested
by comparing the overall variance explained (multiple R squared) by the
linear and non-linear models. The validity of positive-negative argu-
ments within the linear model (Hp vs. ~ in Figure 3-1) can be verified
by the sign of the regression estimate. For example, if b1 in equation
(3-1) is both positive and significantly greater from zero, it would
mean that the relationship between the two variables is linear positive--
that is, more national wealth leads to more political violence, consistent
with the 01son-Merkx hypothesis. The relative strength of explanatory
power between two different curvilinear hypotheses can be compared by
examining parameter estimates and the overall amount of variance explained
by the two curvilinear hypotheses. l8
Two variables are initially operationalized to measure the level of
economic development of countries. Data on Gross National Product per
capita and the Energy Consumption per capita in 1965 were collected.
However, it turned out that the two measures of economic development
correlated so highly (r = .93) that the relationship is nearly perfect
l~ote that both H1 and H3 in Figure 3-2 can be represented by asingle equation (3-2). If the sign of b1 is positive and b2 negative,H1 holds true. The reversed signs would mean that H3 is a validspecification.
57
linear. Therefore, only one indicator--Energy Consumption per Capita
in 1965--is chosen as the indicator of national wealth and industrial
ization to be used in subsequent regression analyses.
The least-square estimates for the three models are conducted for
each of our four measures of political violence. The results are
presented in Tables 3-1, 3-2, and 3-3. Protest does not display any
significant relationship with our measure of economic development in
both linear (Table 3-1) and logarithmic curvilinear (Table 3-3) estima
tions. However, it shows an improved goodness of fit with the polynomial
estimation. Not only does the amount of the explained variance (R
squared) increase substantially, but the estimate of b2 in Table 3-2
is statistically significant, indicating that apparently the presence
of curvilinearity is hardly due to chance.
Note also that the direction of relationship between Xl and Protest
is negative, while that of (Xl)2 to Protest is positive. This suggests
that societies at both the lowest bottom and the highest level of
economic development tend to suffer greater magnitudes of Protest and
those in the middle ranges of economic development experience less
Protest. However, as indicated in the magnitude of R squared in the
estimates of Protest, the overall explanatory power of the model is only
moderate, possibly indicating the stochastic nature of this dimension of
conflict behavior, or the weakness of the model. To illuminate the
problem, a scattergram is produced across the two variables. Inspection
of the scatter diagram in Figure 3-3 suggests that the positive slope
of the polynomial model at the highest level of Energy Consumption per
capita largely reflects an oversensitivity of this model to the effects
58
of the one country--the United States--which clearly is an outlier to
19the general pattern. It might be argued, on visual grounds, that,
when we remove the outlier, the logarithmic model of a very moderate
initial curve, with a slow tendency toward leveling off at higher stages
of economic development, would fit better with the general pattern of
our data. The power of the logarithmic model, however, fails to reach
our confidence limit as indicated by insignificant parameter estimate
in Table 3-3. Such considerations lead us to conclude that, in spite of
an apparent curvilinearity, we find no systematic evidence to support
that Energy Consumption per capita is related in any significant way to
the cross national variation of the measure of political protest.
Regression estimates for Provoked Repression do not indicate that
there is any significant relationship whatsoever between Energy Con-
sumption per capita and our measure of repression. The results 'show that
curvilinear models best capture the relationship between Energy
19This has been tested by the regression estimate of the model(.r2) with the United States excluded from the sample. When the UnitedStates was excluded from the sample, none of the two independent variablesin equation (3-2) produced significant parameter estimates. Compare theresult below with Table 3-2.
* Regression of Protest on Xl and (Xl )2 (without US: N=80)
independentvariable
Energy Consumptionper Capita: 1965
Energy Consumptionper Capita: 1965,Squared
Constant
parameterestimate (B)
-0.0001
0.0000
0.07
standardizedestimate (Beta)
-0.25
0.13
R2 = 0.02
standarderror of B
0.0002
0.0000
F = 0.71
F
0.65
0.18
Table 3-1. Linear Regressions of Political Violence onEnergy Consumption per C~pita, 1965 (N:81)
59
independent variable parameterestimate (B)
standardized standardestimate (Beta) error of B F
ProtestEnergy Consumptionper Capita, 1965constant
0.0001
--0.07
0.10 0.0001 0.76
2R :0.01
Repression
Energy Consumptionper Capita, 1965
constant
-0.0001
0.11
-0.17 0.0001 2.23
2R =0.03
Political Restrictiveness
Energy Consumptionper Capita, 1965
constant
-0.0002*
1.95
-0.55 0.00003 33.04
2R =0.30
Internal ''lar
Energy Consumptionper Capita, 1965
constant
-0.0001*
0.19
-0.31 0.0001
2R =0.10
* Siarred(*) are those whose parameter estimates are significant ata=0.05.
. ..: .
60
Table 3-2. Curvilinear (polynpmial) Regressions of PoliticalViolence on Energy Consumption per Capita, 1965 (N=$1)
independent variable parameterestimate(l~)
standardizedestimate(Beta)
standarderror of B F
ProtestEnergy Consumptionper Capita, 1975Energy Consumptionper Capita, 1975:squaredconstant
-0.0003*
0.0000*
0.14
-0.69
0.$6
0.0001
0.0000
6.91
10.76
2R =0.13 F=5.$1
ReI?I~ess:i.on
Energy Consumptionper Capita, 1975Energy Consumptionper Capita, 1965:squaredconstant
-0.0002
0.0000
0.16
-0.36
0.21
0.0001
0.0000
1.71
0.60
2R =0.03 F=1.41
2.062R =0.35
Political RestrictivenessEnergy Consumptionper Capita, 1975Energy Consumptionper Capita, 1965:squaredconstant
2R =0.37
-0.0004*
0.0000*
-1.15
0.66
F=22.52
0.0001
0.0000
26.36
$.73
Internal WarEnergy Consumptionper Capita, 1975Energy Consumptionper Capita, 1965:squaredconstant
2R =0.15
-0.0004*
0.0000*
0.0001
0.0000
10.69
* Starred (*) are those whose parameter estimates are significant ata~.05.
Table 3-3. Curvilinear (logarithmic) Regressions of PoliticalViolence on Energy Co~sumption per Capita, 1965 (N=81)
61
independent variable
ProtestLog, Energy Con·slimption perCapita, 1965constant
RepressionLog, Energy Consumption perCapita, 1965constant
parameterestimate(B)
0.02
-0.112R =0.001
-0.05
0.30
2R =0.01
'Standardizedestimate(Beta)
.0.03
--0.09
standarderror of B
0.06
0.06
F
o.m~
0.59
-0.26*
Political RestrictivenessLog, Energy Consumption perCapita, 1965constant
-0.62 47.90
Internal vlarLog, Energy Consumption perCapita, 1965constant
-0~17*
1.072R =0.11
-0.33 0.06
* Starred (*) are those whose parameter estimates are significantat a",,0.05.
Figure 3-3. Scatter Diagram of Political Protest across Energy Consumption per Capita: 1965 (N;81)
3.5 ..-1I•I3.0 +IIII
2.5 ..-1IJI ...
:.~ ~
~CD
~~....IIIU
'PI
;::;i-
.•----+----+----+----+----+----+----+----+----+----+----+----+----+----+----..-----..-----+----..---~+:~--..-.•IUSA • I
, 1: 1• •I 1
I 1• 1• 1I •
I 1, 1, 1
I' 1• +
I . • 11'1
1 • ' • 1I • .' 11.5. . , +I ...' • I. 1 •• .. II. • , •1 • , 1
1.0 ..-. • .,. ...1 '" .... I tI... ' II'" " 11 ... • : 1
0.5+ •• • ...... ... , .1- ... .... .. •r' ." ; __to. • /. ~
0.0 + '" • . '"·tt... _ .. I .._
~ 2 I1 • ... I12 •• III II ... , I
-0.5'" • ..-• ... ... 1I 2 *. 1••••• 1I * **'" *. •
-1.0..-·. * * * • •.*3.. II ... •1* * •I • ... •
-1.5'" ....•----+----~--- ...---~---+----~----+----~----.._---~----+---~---- ...----4----+----&----+---_'_--- ...---_4.t~O .939.0 1868.0 2797.0 3726.C 4655.~ 55B4.~ 6513.0 7442.0 8371.~ Q3~~.~
(Energy Consumption per capita in 1965: kilograms) ~N
63
Consumption per capita and our measures of Political Restrictiveness
and Internal War. Compared to the estimate of Table 3-1, the amount of
R squared increased substantially in two curvilinear estimates for
Political Restrictiveness (Tables 3-2 and 3-3). In general, however, the
logarithmic model represents slightly better fit to our data. While the
R squared difference between the two models does not allow us any
statistical grounds to choose one against the other, the criterion of
parsimony implies that the log specification is preferable to the
polynomial one. The validity of logarithmic specification is further
demonstrable by means of the scatter plot reported in Figure 3-4.
For the Internal War regression, R squared from the polynomial
model is highest among the three specifications, and the differences
between it and the other two are statistically significant at the .05
level of confidence. 20 The scatter plot of Figure 3-5 also reveals
that the polynomial specification conforms more closely with the
general pattern, in which the magnitude of Internal War decreases as
polities reach higher level of economic achievement, but it begins to
increase as they undergo further industrialization.
Examination of alternative models and their relative goodness of
fit to our empirical data enable us to conclude with the following
tentative descriptive propositions on the relationships between the level
of economic development and various dimensions of political violence:
20For the test of R squared differences between a simple and a morecomplex model and its test of significance, see Fred N. Kerlinger andE. J. Pedhazur, Multiple Regression in Behavioral Research (New York:Holt, Rinehart and Winston, 1973), pp. 70-72; Norman H. Nie et a1.,SPSS, .£p... cit., p. 339.
Figure 3-4. Scatter Diagram of Political Restrictiveness across Energy Consumption per Capita: 1965 (N=80)
.+----~----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+.3.0 + • * • +1 11 11 11 I
2.8 + +1 11.2. .. 11 J13.. J
2.6 + +I • J1 JJ* • JJ • J
2.4 + +1 . 11 J1 . 11 3* ., 1
2.2 + • +1 11 ; I1 11 1
2.0 + +-; 1*22 '" I
CD 1 1~ 1 1CII I I~ 1.8 + +~ 1 • I~ 1 3 .. 1b 1 1CD I •• , I~ 1.6 + ; +
1 1~ 1 13 12 2 0 1~ 1 1:: 1.4 + +~ 1 • ' I2 I I
I 11 *2 2 '4' • • • 1
1.2 + +1 • 11 • I1 11 1
1.0 + ••••• .... ..2 ••.' ". . +.•----+----.----+----.----+----4----+----.----+- • -+----A----.----A----.----~----+----~---+---~.10.0 939.0 1868.0' 2797.~ 3726.~ 46SS.C 5584.' 6513.0 7442.0 8371.Q 9~CO.~
(Energy Consumption per capita in 1965: kilograms)
0\~
Figure 3-5. Scatter Diagram of Internal War across Energy Consumption per Capita: 1965 (N=81)
.+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+.. 4.0 + +1 II . 1I .. S. Vietnam I1 J
3.5 + +I 1I I1 II I
3.0 + • +1 II II . I1 I
2.5 + . . +& • II • I1 , II I
2.0 + +I:' 11 • 1I .. 11 I
1.5 + . . +I 11 I,. 11 •• 1
I.e +. ... •. +1 • • 1
-;;- 1 • I., I 1::. .1." i 1.-4 0.5+ • +!. .. '. IB 1 1c 1** *. 1~ 0.0 + • +
1 • ~ 1I • •• 1
·1 2. 112. ~ 1
-0.5+.. • •• • +I. • • I1 • .. 11 • ~ • • • 1I •••• ~ I
-1.0+ . .. .A.+.+----+----~----+----~---+----Jr---+----~---+----~---+-- --.----+---~---+----4_---+---~---+----r.10.0 939.c:) 1868.(\ 2797.0 3726.1') 4655.':1 5584.0 6513.0 7_42." 8J71.r.·. 93(10.('
(Energy Consumption per capita in 1965: kilograms)0\\11
66
(1) The level of economic development has no systematic and directeffects on the cross-national variation on the level of Protestactivities.
(2) The level of economic development has no systematic and directeffects on the cross-national variation on the level of ProvokedRepression.
(3) The level of economic development tends to have a curvilinear(logarithmic) negative effect on the cross-national variation on .the level of Political Restrictiveness, and finally;
(4) The level of economic development tends to have a curvilinear(polynomial of degree two) relationship with the cross-nationalvariation on the level of Internal War.
The above findings are to be understood, at this stage, as mainly
descriptive relationships rather than as causal assertions. As Hibbs'
analyses proved, the causal impact of economic development on mass
political violence is multifaceted and primarily indirect. Unless we
introduce more variables into the system which intervene between the
bivariate relationships and inquire further into them, it would be
premature to conclude that the relationships we cona1uded with in this
chapter are really causal ones. We will now proceed in our study toward
such a direction.
CHAPTER IV
SOCIAL MOBILIZATION, INSTITUTIONALIZATION AND
POLITICAL VIOLENCE: THE "GAP" HYPOTHESES
Introduction
Another potent model, comparable to those we have examined so far,
is derived from Karl W. Deutsch and Samuel P. Huntington's works on the
processes and consequences of social mobilization, political participation
and political institutionalization. We will look into the thrust of
the "gap" hypotheses proposed by the two authors more carefully. Various
imbalance hypotheses of Ted Gurr (education and economic development),
Karl Deutsch (social mobilization and social welfare), and Huntington
(mobilization or participation to institutionalization) have been dis
confirmed by Douglas A. Hibbs' carefully designed causal analysis. The
study attempted in this chapter will replicate Hibbs' test of the
Deutsch-Huntington thoery by utilizing more current data and with more
refined operationalization of the variables. l In addition, I will also
attempt to broaden the perspective of this theoretical orientation by
combining Deutsch and Huntington's hypotheses into a more complete causal
framework in the following chapter.
1. Theoretical Orientation
Deutsch conceives of social mobilization as a process in which
"major clusters of old social, economic and psychological commitments
lSee Hibbs,~. cit., Chapter 4, and pp. 96-115 of Chapter 6.
68
are eroded or broken and people become available for new patterns of
socialization and behavior.,,2 Social mobilization calls for "an
expansion of the politically relevant strata of the population," which,
in turn, produces "mounting pressures for the transformation of political
practices and institutions."
If the "capacity" and "responsiveness" of government to meet mass
demands is outrun by expanding "needs and expectations" of the mobilized
population, Deutsch infers, the increased level of political tension,
albeit with a time lag, will bring the breakdown of domestic stability.
The logic behind this hypothesis goes on:
If it [the government] proves persistently incapable orunresponsive, some or many of its subjects will cease toidentify themselves with it psychologically; it will bereduced to ruling by force where it can no longer rule bydisplay, example, and persuasion; and if political alternatives to it appear, it will be replaced and eventuallyby other political units, larger or smaller in extent, whichat least promise to respond more effectively to the needs andexpectations of their peoples. 3
Huntington's theory provides us with a proposition similar to
Deutsch's. The stage of uprooting, or the induction of the mobilized
population into more modern patterns of political and organizational
membership, creates "social frustration," which leads to "demands on the
government and the expansion of political participation to enforce those
demands." If the level of political institutionalization is low, it is
2Karl W. Deutsch, "Social Mobilization and Political Development,"APSR, 55, 3 (Sept., 1961), reprinted in Jason L. Finkle and Richard W.Gable, eds, Political Development and Social Change, 2nd ed. (New York:John Wiley lie Sons, 1971), pp. 385-386°. Note that the logic of this thesisruns similar to that of the "rise and drop" or "relative deprivation"hypothesis discussed in Chapter 3. However, it is different from thedeprivation thesis in that Deutsch is concerned more with the politicalconditions, as well as the economic ones.
3Ibid., p. 395.
69
difficult for these demands to be expressed through legitimate channels
and to be moderated and aggregated within the political system.,,4 There-
fore, the sharp increase in the social mobilization or political
participation in relation to political institutionalization will give
rise to political instability.5 Although the concepts are somewhat
different, Deutsch and Huntington have much in common in their
theorizing. The following propositions derive from respective authors:
1. The higher the ratio of social mobilization to the performance ofgovernment in meeting civilian needs, the higher the level ofpolitical violence --- Deutsch's hypothesis.
2. The higher the ratio of social mobilization to the level of politicalinstitutionalization, the higher the level of political violence
Huntington's hypothesis.
3. The higher the ratio of political participation to the level ofpolitical institutionalization, the higher the level of politicalviolence -- Huntington's hypothesis.
Rigorous tests of these hypotheses require well-defined statistical
models. Three ratio interaction models would take the following forms:
where: Y: measures of Political ViolenceXl: measure of Social MobilizationX2: measure of Governmental Performance
Xl /X2 : ratio (interaction term) of Social Mobilization toGovernmental Performance
e: stochastic disturbance
(2 - 2.a) --- Y = a + blXl
+ b2
X3
+ b3
Xl
/X3
+ e --- Huntington'shypothesis
where: same as in (3 - l.a)measure of Political Institutionalizationratio (interaction term) of Social Mobilization toPolitical Institutionalization
4H • ·t 55untJ.ngton, .2£.. ~., p. •
5See ibid., pp. 78 ff.
70
(2 - 3.a) --- Y = a + bl X4 + b2X3 + b3 X4/X3 + e --- Huntington'shypothesis
where: X3X4 :X4/X3:
same as 3 - 2. ameasune of Political Participationratio (interaction term) of Political Participation toPolitical Institutionalization
If these hypotheses have any empirical validity, the ratio terms
should have significant parameter estimates. Such significant estimates
would indicate that the conjunction of high social mobilization and low
governmental performance, high mobilization and low institutionalization,
high participation and low institutionalization and so on, have positive
effects on the level of political violence which are multiplicative, that
is beyond the additive effects of the two independent variables in each
equation. 6
Alternative specifications to the ratio terms of the three hypotheses
are logarithmic formulations of them in the following way.
where: In Y : logarithmic values of political violenceInXI and InX2 are logarithmic values of Xl and X2
where: InX3 is logarithmic value of X3
where: InX4
is logarithmic value of X4
6It means, for example, that while Xl or X2 in (2 - l.a) may haveno separate effects on the Y, they have a joint effect on Y by means ofa ratio interaction. If it is true, one should expect that the parameterestimate of the ratio term (XI /X2) is positive and significant regardlessof whether the estimates of Xl or X
2are significant or not individually.
71
Logarithmic formulations7 of the hypotheses, having no additional
explicit ratio term, allow for estimates of effects which are less sus
ceptible to the problem of multicollinearity8 than the direct ratio
interaction models. Examined in conjunction with the estimates of ratio
term models, it would allow us to focus mainly on interaction effects
of the two variables in the equation, which are the thrust of the
Deutsch-Huntington hypotheses. 9 If the relationships postulated in ac-
cordance with the Deutsch-Huntington hypotheses are to hold systematically
--that is, the conjunction of high social mobilization or political
participation with low government performance and low institutionalization
breeds more political violence than that with a more balanced ratio, then
the regression estimates of the coefficient bl should be positive and
significant, while b2 should be both significant and negative.
When
7The equation implies Y = a*. x~1.x~2 • e*,where: log a* = a and log e* = e bl b2
b2 is negative, it implies Y = a* • Xl /X2bl b2• e* = a. Xl /X2 . e
8Multicollinearity refers technically to incidences where two or moreof supposedly "independent" variables are highly correlated. The neteffect of high multicollinearity is to increase the sampling errors ofregression estimates. When, for example, two independent variables areperfectly correlated (rX
l.X
2= 1.00), the sampling error becomes infinite:
that is, any solution will fit the data almost equally well. Therefore,multicollinearity "makes it difficult to choose reliably between alternative models." In other words, the higher the correlations betweenindependent variables, the less the estimated effects of individual independent variables are sharp, and although R2 may be high, it becomes increasingly impossible to reject hypotheses concerning them.
For more detailed presentation on the technical problems of multicollinearity and its possible solutions, see Hubert M. Blalock, CausalInferences in Nonexperimental Research (Chapel Hill: University of NorthCarolina Press, 1964), pp. 87-93; and Blalock, "Correlated IndependentVariables: The Problem of Multicollinearity," Social Forces, 62 (December,1963); Donald E. Farrar and R. R. Glauber, "Multicollinearity in RegressionAnalysis: The Problem Revised," in Review of Economics and Statistics,49 (February, 1967), pp. 92-107.
9By excluding the chances for additive (or "main") effects of theuntransformed variables to be introduced in the models, the log
72
In order to evaluate the validity of these specifications, the
concepts in each hypothesis should be operationally defined so that they
are to be measured by quantitative data.
2. Measurement of Variables
A. Social Mobilization Index
Deutsch has suggested as measures of social mobilization: lO
1. Percentage of population exposed in any substantial way to significantaspects of modern life;
2. Percentage of those exposed to mass media;
3. Percentage of inhabitants who have changed residence;
4. Percentage of population living in towns;
5. Percentage of population in non-agricultural occupations amongthose who are employed;
6. Percentage of literates.
To quantify the concept in line with Deutsch's suggestion, data were
collected on four of the above indicators. In order to capture as full
a range of the concept as the availability of the data permits, the
arithmetic mean of the four indicators is calculated after they are
standardized into Z-scores.
The four indicators which are used for calculating the index of social
mobi1izationll are as follows:
specifications actually max1m1zes the possibilities for interactioneffects to be captured in regression.
lODeutsch, ~. cit., pp. 386-387.
11All data are for 1965, unless not available. In the latter case,the available data nearest to 1965 are used. I have, of course, madesure that the component variables are correlated highly enough to betreated as "equivalent though not identical" measures of social mobilization. Intercorre1ations among the components and between each componentand the composite index variable are as follows:
73
1. Number of persons enrolled in higher education12 per one millioninhabitants. (Source: Handbook, pp. 229-231)
2. Percentage of the population living in cities of 100,000 or moreof population. (Source: Handbook, pp. 219-221)
3. Percentage of population belonging to non-agricultural13 sectoramong the total population. (Source: F.A.O. & I.L.O., Progressin Land Reform, New York, UN, 1970, pp. 332-344)
4. Literacy rate for population of 15 years old or more.(Source: Handbook, pp. 232-235)
B. Capacity and Responsiveness of Government to Meet Mass Demands
In line with Deutsch's original formulation, the performance of
government in meeting civilian demands can be operationalized by means
of two concepts. They are capacity and responsiveness of government to
meet civilian welfare demands. An increased capacity of government,
Deutsch says, implies operationally "an increased scope of government and
a greater relative size of the government sector in the national economy."
(1) (2) (3) (4) (5)1) Non-agricultural Population 80 80 76 802) Urban Population .76 81 77 813) Literacy Rate .87 .67 77 814) Enroll. in High. Educat. .67 .68 .63 77-----------------------------------------------------------------5) Social Mobilization Index .93 .88 .90 .65
*Numbers in upper diagonal are number of cases entered into correlations.All correlations are significant at p ~ 0.001.
l2Higher education is defined in the source as that "which require,as a minimum condition of admission, the successful completion of education at the second level, or evidence of the attainment of an equivalentlevel of knowledge."
l3Non-agricultural sector includes all persons who are depending fortheir livelihood on non-agricultural sectors and their non-workingdependents. It also excludes people living on forestry, hunting andfishing.
74
Responsiveness is a concern for "human needs that impinge upon the
political process," and calls for provisions as the following: 14
1. housing and employment;
2. social security against illness and old age;
3. medical care against the health hazards of crowded dwellings andplaces of work and the risk of accidents with unfamiliar machinery;
4. educational services for the people and for their children.
The government expenditure15 of 1965 as a percentage of gross
national product is taken as our principal measure of the capacity. In
order to capture the substantive content of responsiveness of government,
data for the following indicators were collected:
1. Social insurance program experience between 1934 and 1960. 16(Social Insurance Index)
l4Ibid., p. 391.
l5Government expenditure is defined in the source as the budgetedand capital outlays of the national government. Redemption of debt andcertain capital transfers are excluded, while grant to foreign governments are included. The base year for data collection is 1965. (Source:DON, 65).
l6This variable is operationalized by counting the total number ofyears that a country had a given type of social insurance program inoperation between 1934 and 1960 among the following five major types ofprograms; work~injury, sickness and/or maternity, pensions, familyallowances, unemployment. For example, a score of from 0 to 27 ispossible for each of the five programs. A country with a score of 27 oneach of 5 programs would have a maximum score of 135. Data for allAfrican countries, Jamaica, Trinidad and Tobago, Taiwan, Libya, Sudan,and Egypt are calculated from US, Social Security Administration Division'sreport. Others are taken from Cutright's article.
Source: U.S. Department of Health, Education &Welfare, SocialSecurity Administration, Social Security Programs Throughout the World,1973 (Washington: US Government Printing Office, 1973); Philips Cutright,"Political Structure, Economic Development, and National Social SecurityPrograms," in American Journal of Sociology, Vol. LXX, No. 5 (March,1965), p. 549.
75
2. Annual social security benefit expenditure17 per capita in 1963expressed in US dollar at parity rates. (Social Security $ percapita)
3. Social Security benefit expenditure of 1963 as percentage of totalconsumption expenditure. (Soc. Sec. % Cons. Exp.)
4. Per capita educational expenditure in 1965 as expressed in USdollars (Edu. Exp. $ Per Capita) (Source: Handbook, pp. 30-33)
5. Total educational expenditure as percentage of Gross NationalProduct in 1965. (Edu. Exp. %GNP) (Source: Handbook, pp. 30-33)
Unlike the Social Mobilization index, where the homogeniety of
indicators poses no problem, the intercorrelations among the six in-
dicators of governmental capacity and responsiveness reveal that two
of them--governmental expenditure as percentage of GNP and educational
expenditure as percentage of GNP--do not correlate enough with the rest
of them. 18 Factor analysis of the same variables reported in Appendix 2
l7Benefit expenditure is defined as the sum of medical care, cashbenefits, pensions, unemployment, family allowances, and public healthservices, or total social security expenditure minus the sum of administrative cost, transfer to other social security scheme, and otherexpenditures which are not related to benefits. Countries with noprograms are estimated as "0". Source: LL.D., The Cost of SocialSecurity: 6th International Inquiry, 1960-1963 (Geneva, 1967), pp. 313315.
18Corre1ations between indicators of the governmental capacity andresponsiveness to meet mass demand are as follows:
Indicators N 1 2 3 4 5 6 7
l. Gov't Exp. as % GNP 63 63 40 41 63 63 632. Social Ins. Index 81 0.09 44 45 81 81 813. Soc. Sec. $ per capita 44 0.43* 0.79** 43 44 44 444. Soc. Sec. % Cons. Exp. 45 0.36* 0.85** 0.91** 45 45 455. Edu. Exp.$ per capita 81 0.16 0.65** 0.84** 0.68** 81 816. Edu. Exp. % GNP 81 0.38** 0.33** 0.51** 0.49** 0.66** 81-------------------------------------------------------------------------7. Government Respon
siveness IndexKey: * is significant
** is significant
81 0.17
at p < 0.05at p ~ 0.001
0.91** 0.97** 0.94** 0.87** 0.52**
(Numbers in upper diagonal arenumber of cases entered intocorrelation. )
76
also proved that governmental capacity and its actual responsiveness to
meet mass welfare demands are two empirically separable dimensions of
the governmental performance. This suggests that, in line with Deutsch's
formulation, capacity and responsiveness consist of two separate concepts,
which are related but cannot be treated as interchangeable as far as the
respective indicators are concerned. Methodologically, therefore, the
proposition we have identified in line with Deutsch's theorizing should
be tested by means of the following two research hypotheses.
1-1: The higher the ratio of social mobilization to the capacity ofgovernment to meet civilian needs, the higher the level ofpolitical violence.
1-2 The higher the ratio of social mobilization to the responsivenessof government to meet civilian needs, the higher the level ofpolitical violence.
Government expenditure as a percentage of gross national product is
used as our measure of the capacity of government to meet mass welfare
demands. 19 The responsiveness to government to civilian welfare is
measured by the arithmetic mean of Social Insurance Program Index, Social
Security Benefit Expenditure per capita (in US dollars), Social Security
Benefit Expenditure as percentage of total Consumption Expenditure, and
per capita Educational Expenditure in US dollars, after raw data are
standardized into Z-scores.
19Note that total educational expenditure as percentage of GNP isdropped as a component of the responsiveness index. As shown in thefactor analysis, this variable loaded on both factors with almost equalimportance. This implies that, since the variable consists of a measureof capacity as much as a measure of actual performance, it is inappropriate to include it in only one case. Further, a relatively lowercommunality of this variable than others indicates that homogeneity ofthis variable with each of the two dimensions is relatively low. (SeeAppendix 2.)
77
C. Political Participation and Political Institutionalization
The extent of mass political participation is measured by Voter
Turnout as percentage of total electorate. Voter Turnout is defined in
the source (Handbook, pp. 22-23) as the total number of individuals casting
valid ballots in national elections20 and the electorate as those in-
dividuals legally able to vote in given elections.
According to Huntington, the level of political institutionalization
can be measured by "the adaptability, complexity, autonomy, and co
herence,,2l of a political system's organizations and their procedures.
Adaptability is referred to as the organizational characteristic of an
institution acquired through age and environmental challenge. Huntington
notes that the adaptability of an organization can "in rough sense be
measured by its age.,,22 Complexity refers to "multiplication of organiza-
tional subunits, hierarchically and functionally, and differentiation of
separate types of organizational subunits. 1123 found in each political
system. Political systems which depend upon one individual, political
authority and power centered in one institution, and a constitutional
system based on a single conception of political ideology constitute,
Huntington notes, measures of low complexity. Autonomy of a political
20For most countries, legislative elections were the base data.In countries with bicameral legislature the votes selected were thosefor the lower house. In a few cases, the presidential election datawere used.
2lHuntington, E£.. cit., p. 12.
22cf • Ibid. , pp. 13-17.
23cf • Ibid. , pp. 17-20.
78
institution is the "extent to which political organizations and pro-
cedures exist independently of other social groupings and methods of
behavior.,,24 Finally, coherence of an organization requires some measure
of consensus "on the functional boundaries of the group and on the pro
cedures for resolving disputes which come up within those boundaries.,,25
In order to capture this rather complex meaning of political
institutionalization, data for the following variables were collected:
1. Index of legislative representation as of 1965. This index variesfrom 1 to 5, and constructed by the following coding scheme:
"1" : No constitutional provision for legislature exists, orconstitutional provision exists but the legislature notconstituted or suspended by executive power.
"2" Legislature exists nominally. But it is either that themembers are recruited on the basis of "non-elective" method,or that its function is "ineffective."26
"3" Legislature that is: (1) recruited on the basis of nonelective methods but "partially effect ive," or; (2) recruitedon the bases of elective methods but largely ineffective
24H t" °bod 20 22un l.ngton, !......!...-., pp. - •
25Huntington's discussion does not provide a sharp empiricaldistinction between autonomy and coherence. Instead, he surmized thatthe "two are often closely linked together," and that "autonomy becomes ameans to coherence." Ibid., p. 22.
26"non-e1ective" method includes appointment by the executive,selection of the legislative members on the basis of hereditary or otherascriptive criteria. "Effective" is meant to indicate that the legislaturepossesses significant governmental autonomy including the authority related to taxation and disbursement and the power to override executivevetoes of legislation. "Partially effective" means that executive powersubstantially outweighs but does not completely dominate that of thelegislature. "Ineffective" legislatures are inclusive of: (1) rubberstamp legislature; or (2) implementation of legislation becomes impossibledue to, for example, the executive overpower or domestic turmoil whichimpede substantially the exercise of its constitutional functions. Thisdefinition and data are taken from Banks, .2£.. cit., Segment L Technically,this index is derived from Guttman scaling of Legislative Effectiveness andLegislative Selection of Banks data.
79
"4" Legislature recruited by elective methods and whose functionis partially effective.
"5" Legislature recruited by elective methods and whose functionis effective.
2. Number of major political parties as of 1965. Major political
parties are defined as one with a membership of more than one percent of
the population. The original data drawn from source (DON. 65, pp. 174-
175) were transformed into the following index:
"1" No party system or one party domination.
"2" two party system.
"3" three major parties.
"4" four or five major parties.
"5" more than six major parties.
3. Index of party distribution in legislative seats. This index is
calculated by the formula:
NF = 1 L ( Ni ) ( Ni - 1)
N=l N N - 1
(Ni = the total number of seats received by the ith party;N = the total number of seats)
This index actually measures the likelihood that two randomly
selected members of the legislature will belong to different parties.
Raw data refer to election for the lower (or only) house of the legis-
lature and exclude appointed members. The elections cover those held
between 1963 and 1968 for each country. The range of the index can vary
from 0 to 1. (Source: Handbook, pp. 48-50).
4. The age of national institution calculated on the basis of independence
(Source: Handbook, pp. 26-29). This variable is indexed by means of the
following criterion:
80
"I" independent since 1960
"2" independent between 1950 and 1959
"3" independent between 1945 and 1949
"4" independent between 1900 and 1944
"5" independent before 1900
5. The age of constitutional stability. This variable is calcuiated on
the basis of the year in which the present constitution or extra
constitutional operative rules as of 1970 came into effect. 27 Coding
scheme of this variable is the same as the age of national institution
since independence.
Having ensured some degree of homogeneity28 among five indicators of
political institutionalization, the final index in our measure of political
institutionalization is derived by taking the arithmetic mean of the
available data for a country. The following table summarizes the process
of operationalization and selection of our final variables to be used in
subsequent regression estimates of the four hypotheses. (Table 4.l.)
271n the source (Handbook, pp. 26-29), amendments and rev~s~ons to anexisting constitution were not considered as a break of the constitutionalstability. Draft constitutions if judged to be in force or changes inthe form of government were considered as new constitutional establishments.Territorial losses or additions without any substantial constitutionalforms were not judged as new constitutional establishments. Partitionsor federations which appear to alter the previous forms of governmentwere counted as new constitutions (e.g., East and West Germany in 1949).Military coups are not evidence of constitutional change unless there areexplicit suspension of the previous constitution beyond some temporaryabridgement. For the countries that have undergone more than one changeof regime after the suspension of original constitution, the most recentcoup is taken as the date of current constitution. See pp. 17-18 formore definitional notes.
28 .1ntercorrelat~ons between indicators of political institutionali-
zation are as follows:
..
. 1'.-.1. 4--1. SUIIII8ry: Variables aDd Indices for 'restiDa the "Cap" Bypothese.,I
Concept Bav data collected. Var.1able or 1ndex wsed Method offor Begresa10n Analyses IndexiDg'
Soc1al MobUizatlon 'j enmllmeot in ...... "'.at1on{196Sl Social 1'Ioblliza.tion mean2 "urban populations (196.5)' Index Z-scores of 1) 2) ):3 :c non-agricultural :}pulatiOn(1965) " 4)4 Literacy rate (196.5 .
Governmental 1) CoV't expo as ~ GNP (196.5) Cov't expo as" Ball datacapacity to meet of GNPveUare demands
Governmental 1llSOCial insuranc~ index(19)4-60) Governmental _aDBesponsiveness to 2 social security benefit $/capIta(6:3) Besponsiveness z,-acores of 1) 2) :3} 4}welfare demand :3 social security benefit % CODSump- I.ndex
tion expenditure(1963)4~ educate expo $/capita (1965)
.. .5 educate expo as %of GNP '" '.
Political 1) 1egis.Representation(196.5) Political Institu- mean score af'tervInatitutionalizatlon 2~ No. of major po1.parties(65) tlonalization Index tX'ansformatiOD of
:3 party distribution in party distribution .(J). legislative seats(196)-68) into a range of 1-54) age of national institution.
independence(19?O).5) age of national instItution.
constitutional stabllIty(1970)
Political 1) voter tumout as %of tote Tumout .' n.v dataP artIc1pation total electorate(1960-6S}
•* not used for Index
()Q.I-'
•
82
3. Testing the "Gap" Hypotheses with Cross-National Data
The main purpose of this section is to test the validity of various
gap hypotheses which we have discussed in the foregoing parts of this
chapter. As we have noted before, the ratio interaction specifications
are mainly to see if those gap hypotheses exert significantly positive
effects on our measures of political violence beyond the simple additive
effects of the individual variables included in each hypothesis. On the
other hand, logarithemic specifications focus only on each of the inter-
action effects. Having the simple additive effects excluded in the model,
they would enable the gap effects to show up better, while minimizing
the problem of multicollinearity. Once we find, for example, that the
gap hypotheses are disconfirmed, we would be able to proceed to evaluate
Indicators N 1 2 3 4 5 6
1- Leg. Representation 79 75 66 79 79 792. No. of maj or Pol. Parties 75 0.56 62 75 75 753. Party Dist. in Leg. Seats 68 0.60 0.74 67 67 684. Age of National Instit.: 80 0.29* 0.48 0.48 80 80
Independence5. Age of National Instit.: 80 0.50 0.39 0.39 0.50 80
Constitutional Stability---------------------------------------
6. Political InstitutionIndex 81 0.76 0.81 0.80 0.74 0.75
1) * is significant at p = 0.004
<2) All others are significant at p = 0.001
3) Numbers in upper diagonal are number of cases entered intocorrelations
4) The range of Party Distribution in Legislative Seats is adjustedto 1-5 prior to the making of Political Institutionalization Index.
83
the theory only in terms of the additive effects of individual variables.
This task is reserved for the following chapter (Chapter V).
It should be noted that for the gap hypotheses to hold empirically,
both of the parameter estimates in a log specification are expected to
be significantly different from zero. At the same time, the sign of
parameter estimate for denominator should be negative, while that of
dividend term should be positive. In each table, the dividend term is
located on the upper part of the denominator term.
A. Political Protest and "Gap" Hypotheses
The regression estimates of the Protest variable cluster on the
ratio interaction and log multiplicative specifications of Deutsch-
Huntington hypotheses are reported in Tables 4-2.1 to 4-5.2. As Tables
4-2.1, 4-3.1, 4-4.1, 4-5.1 demonstrate, none of the ratio interaction
terms produced significant parameter estimates.
Table 4-2.1 Regression of Protest on Social Mobilization and GovernmentExpenditure as Percentage of GNP: Ratio Interaction Model(N=63)
independent variableparameterestimate (B)
standardizedestimate (Beta)
standarderror of B F
F = 0.15
dependent_ variable: ProtestSocial Mobilization Index
Governmental Expenditure %GNP
Social Mobilization/Government Expenditure
constant
0.15 0.15
-0.001 -0.01
-1.16 -0.07
0.03
R:2 = -0.04
0.33
0.01
5.41
0.21
0.01
0.05
84
Table 4-2.2 Regression of Protest on Social Mobilization and Government Expenditure as Percentage of GNP: log MultiplicationModel (N=63)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:log Protest
log Social Mobilization Index 0.01 0.02 0.11 0.02
log Governmental Expenditure -0.52* -0.25 0.26 3.82Index
constant 1.12
R2 = 0.06 F = 1. 99
* starred(*) estimate is significant at a ~ 0.05
In the log specification estimates, parameter estimates are
correct in regard to the direction of signs in Table 4-2.2, but the
estimate of the divided term (Social Mobilization) is insignificant. In
Table 4-3.2, neither the signs are correct nor the estimates are signif-
icant. The results in general disconfirm both of the imbalance hypoth-
eses of Deutsch.
Log multiplication estimations of Huntington's hypotheses do not
sustain any systematic validity either. As shown in Tables 4-4.2 and
4-5-.2, not both of the estimates are significant as expected. In
addition, the signs do not point in the predicted direction. In sum, the
present cross-national data do not sustain the view that the imbalances
between social mobilization and governmental performance, social mobiliza-
tion and political institutionalization, political participation and
political institutionalization, as operationalized in line with Deutsch-
Huntington arguments, are powerful variables for explaining cross-national
85
Table 4-3.1 Regression of Protest on Social Mobilization andGovernmental Responsiveness: Ratio Interaction Model (N=63)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:Protest
Social Mobilization 0.36* 0.35 0.20 3.38Index
Governmental Respon-siveness Index -0.35* -0.32 0.21 2.88
Social Mobilization/ -0.01 -0.08 0.01 0.51Governmental Respon-siveness
constant -0.02
R2 = 0.04 R2 = 0.01 F = 1.20
* starred(*) estimates are those parameter estimates significant ata ~ 0.05
Table 4-3.2 Regression of Protest on Social Mobilization and Governmental Responsiveness: log Multiplication Model (N=81)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:log Protest
log Social Mobilization -0.03 -0.04 0.10 0.11Index
log Governmental 0.19 0.18 0.11 2.65Responsiveness Index
constant -0.36
R2 0.04 -2 0.01 F 1.43= R = =
86
Table 4-4.1 Regression of Protest on Social Mobilization and PoliticalInstitutionalization: Ratio Interaction Model (N=8l)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:Protest
Social Mobilization -0.22 -0.21 0.25 0.75Index
Political Institution- -0.08 -0.09 0.15 0.25alization Index
Social MObilization/ 0.88 0.41 0.55 2.56Political Institution-alization
constant 0.34
R2 = 0.04 RZ = 0.001 F = 1.04
Table 4-4.2 Regression of Protest on Social Mobilization and PoliticalInstitutionalization: log Multiplication Model (N=8l)
independent variable
dependent variable:log Protest
parameterestimate(B)
standardized standardestimate(Beta) error of B F
log Social Mobilization -0.05Index
log Political Institution- -0.36alization Index
-0.05
-0.17
0.10
0.23
0.22
2.41
constant -0.03
F = 1.31
Table 4-5.1 Regression of Protest on Political Participation andPolitical Institutionalization: Ratio Interaction MOdel(N=67)
87
independent variable
dependent variable: Protest
parameterestimate (B)
standardized standardestimate(Beta) error of B F
Voter Turnout
Political Institutionalization Index
Voter Turnout/PoliticalInstitutionalization
constant
-0.01
-0.23
-0.02
1.99
-0.16
-0.29
-0.42
il2 = 0.11
0.01
0.22
0.01
F = 3.69
0.78
1.17
1.77
Table 4-5.2 Regression of Protest on Political Participation andPolitical Institutionalization: log MultiplicationModel (N=67)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:log Protest
log Voter Turnout -0.12 -0.03 0.46 0.07
log Political Institution- -0.37 -0.18 0.26 2.03alization Index
constant 0.52
R2 .,...2
= 0.03 R = 0.001 F = 1. 02
88
variations of political protest. In other words, we do not have to
look into beyond the simple additive specifications of the model in order
to search for significant causal factors for this dimension of political
violence.
B. Internal War and "Gap" Hypotheses
Tables 4-6.1 to 4-9.1 report the estimates for Internal War.
Table 4-6.1 Regression of Internal War on Social Mobilization andGovernment Expenditure as Percentage of GNP: RatioInteraction Model (N=63)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:Internal War
Social Mobilization -0.24 -0.26 0.29 0.73Index
Governmental Expenditure 0.00 0.04 0.01 0.12% GNP
Social Mobilization/ -1.22 -0.08 4.64 0.07Governmental Expenditure
constant -0.07
R2
0.11 -2 0.07 F 2.49= R = =
89
Table 4-6.2 Regression of Internal War on Social Mobilization andGovernment Expenditure as Percentage of GNP: logMultiplication MOdel (N=63)
parameter standardized standardindependen t variable estimate (B) estimate(B~ta) error of B F
dependent variable:log Internal War
log Social Mobiliza- -0.04 -0.06 0.10 0.17tion Index
log Governmental 0.17 0.10 0.23 0.57Expenditure % GNP
constant -0.79
R2 = 0.01-2
-0.02 F = 0.31R =
Table 4-7.1 Regression of Internal War on Social Mobilization andGovernment Responsiveness: Ratio Interaction Model (N=8l)
parameter standardized standardindependent variable estimate (B) estimate(Beta) error of B F
dependent variable:Internal War
Social Mobilization -0.05 -0.05 0.17 0.08Index
Governmental Respon-siveness Index -0.35* -0.36 0.17 4.12
Social Mobilization/ 0.002 0.04 0.01 0.15Governmental Respon-siveness
constant -0.05
R2 0.16 -2 0.13 F 4.89= R = =
* starred(*) estimate is significant at < 0.05a =
90
Table 4-7.2 Regression of Internal War on Social Mobilization andGovernmental Responsiveness: log Multiplication Model(N=81)
parameter standardized standardindependent variable estimate (B) estimate(Beta) error of B F
dependent variable:log Internal War
log Social Mobilization -0.01 -0.02 0.08 0.02Index
log Governmental 0.16 0.18 0.10 2.55Responsiveness Index
constant -0.25
R2 0.03 -2 0.01 F 1.31= R = =
As shown in Tables 4-6.1 through 4-7.2, neither of the estimates
for ratio terms nor the ones for the log multiplicative specifications
support the gap hypotheses. Hence, the test rather unambiguously
demonstrates that Deutsch's (Social Mobilization - Capacity and Respon-
siveness of Government) gap hypotheses are of no significant utility
in our search for the causes of Internal War.
The interaction term of Social Mobilization and Political
Institutionalization has a significant parameter estimate in Tables 4-8.1,
indicating that the ratio hypothesis wbuld possibly have a degree of
validity on the direct effect of imbalance between Social Mobilization
and Political Institutionalization upon Internal War. However, the
result of log multiplication estimate cautions us not to make any positive
conclusion on this in view of the fact, (1) that the estimates are
Table 4-8.1 Regression of Internal War on Social Mobilizationand Po1jtica1 Institutionalization: Ratio InteractionModel (N=81)
91
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:Internal War
Social Mobilization -0.69* -0.74 0.21 0.57Index
Political Institutiona1- -0.04 -0.06 0.13 0.12ization Index
Social Mobi1ization/ 1.00* 0.52 0.47 4.62Political Institiona1-ization
constant 0.25
2 -2 0.13 F = 4.96R = 0.16 R =
<* starred (*) estimates are significant at a = 0.05
Table 4-8.2 Regression of Internal War on Social MObilization andPolitical Institutionalization: log MUltiplicationModel (N=81)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:log Internal War
log Social MObi1iza- -0.02 -0.03. 0.08 0.07tion Index
log Po1itical 0.003 0.002 0.20 0.00InstitutionalizationIndex
constant -0.29
R2
0.001 -2 -0.02 F 0.03= R = =
92
insignificant, and; (2) that the signs are reversed from the expected
directions, and; (3) that the R2 values drop drastically as we move from
the additive and ratio interaction model to the log multiplication model.
Turning to the imbalance hypothesis of participation-institution-
alization on Internal War (Tables 4-9.1 and 4-9.2), we find that, though
the parameter estimate for ratio term is significant, both the ratio term
and the log multiplicative term do not have signs in the predicted
direction. The ratio term also has very high correlations29 with both of
the other two variables, indicating that multicollinearity is a definite
problem in this result. In addition, both estimates for the log model is
insignificant. Thus, we conclude that the gap hypotheses are rejected for
explaining Internal War, and only the main additive variables are to be
retained for further analyses in the next chapter.
Table 4-9.1 Regression of Internal War on Political Participation andPolitical Institutionalization: Ratio Interaction Model(N=67)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable: Internal War
Voter Turnout -0.01 -0.10 0.01 0.37Political Institution- -0.55* -0.75 0.18 9.13alization IndexVoter Turnout/Political -0.03* -0.64 0.01 4.80Institutionalization
constant 2.87R2 = 0.26 -2 22 F 7.20R = =
starred (*) estimates are significant at a ~ 0.05
as follows:2 3
67 6767-0.12
0.54 -0.81
29Intercorrelations between the three variables are1
1) Voter Turnout2) Political Institutionalization Index3) Ratio term (Voter Turnout/Institutionalization)
93
Table 4-9.2 Regression of Internal War on Political Participation andPolitical Institutionalization: log Multiplication Model(N=67)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:log Internal War
log Voter Turnout 0.20 0.07 0.38 0.28
log Political 0.02 0.01 0.22 0.01InstitutionalizationIndex
constant -l.18
R2 0.004 -2 -0.03 F = 0.14= R =
c. Provoked Repression and "Gap" Hypotheses
Tables 4-10.1 to 4-13.2 report regression estimates for Provoked
Repression variable cluster. The ratio term of Social Mobilization to
Government Expenditure has a significant parameter estimate in Table 4-10.1.
However, the log specification shows that the estimates are very low and
signs are at odd. Tables 4-11.1 and 4-11.2 also disconfirm the validity
of Mobilization-Responsiveness imbalance thesis.
Huntington's hypotheses are also denied in view of poor results in
Tables 4-12.1 to 4-13.2. In sum, for this dimension of political
violence, none of the imbalance hypotheses are supported by our data.
Thus, our conclusion is that we need not go beyond the additive model.
94
Table 4-10.1 Regression of Provoked Repression on Social Mobilizationand Government Expenditure as Percentage of GNP: RatioInteraction Model (N=63)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:Repression
Social Mobilization -0.81* -0.81 0.31 6.87Index
Governmental Expenditure% GNP 0.01 0.16 0.01 1.66
Social Mobilization/ 11.43* 0.70 5.00 5.23Governmental Expenditure
constant -0.38
R2 0.11-2
0.07 2.49= R = F =
* starred(*) estimates are those where parameter estimates aresignificant at a ~ 0.05
Table 4-10.2 Regression of Provoked Repression on Social Mobilizationand Government Expenditure as Percentage of GNP: logMultiplication Model (N=63)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:log Repression
log Social Mobilization -0.05 -0.04 0.18 0.07Index
log Governmental 0.50 0.16 0.42 1.39Expenditure % GNP
constant -1.93
R2 = 0.02 R:2 = -0.01 F = 0.70
95
Table 4-11.1 Regression of Provoked Repression on Social Mobilizationand Government Responsiveness: Ratio Interaction Model(N=8l)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:Repression
Social Mobilization 0.01 0.01 0.19 0.004Index
Government -0.24 -0.23 0.20 1.48Responsiveness Index
Social Mobilization/ 0.01 0.15 0.01 1. 79Government Responsiveness
constant -0.04
R2 0.07 -2 0.03 F 1.91= R = =
Table 4-11.2 Regression of Provoked Repression on Social Mobilizationand Government Responsiveness: log Multiplication Model(N=8l)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:log Repression
log Social Mobilization 0.003 0.002 0.15 0.00Index
log Government Respon- -0.06 -0.04 0.19 0.11siveness Index
constant -0.48
R2 0.001 -2 F = 0.06= R =-0.02
96
Table 4-12.1 Regression of Provoked Repression on Social Mobilizationand Political Institutionalization: Ratio InteractionModel (N=81)
independent variable
dependent variable:Repression
Social MobilizationIndex
Political Institutionalization Index
parameterestimate (B)
-0.09
-0.20
standardizedestimate (Beta)
-0.09
-0.26
standarderror of B
0.24
0.15
F
0.13
1.89
Social Mobi1ization/ 0.32Political Institutionalization
1.16 0.54 0.36
constant
R2 = 0.04
0.66
-2R = 0.01 F = 1.20
Table 4-12.2 Regression of Provoked Repression on Social Mobilizationand Political Institutionalization: log MultiplicationModel (N=81)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
dependent variable:log Repression
log Social Mobilization 0.01 0.01 0.15 0.01Index
log Political Institution- 0.88* 0.27 0.36 6.12a1ization Index
constant -1.38
2 -2 F 3.06R = 0.07 R = 0.05 =
*starred(*) estimate is significant at a ~ 0.05
97
Table 4-13.1 Regression of Provoked Repression on Political Participation and Political Institutionalization: Ratio InteractionModel (N=67)
independent variableparameterestimate (B)
standardizedestimate (Beta)
standarderror of B F
dependent variable: Repression
Voter Turnout
Political Institutionalization Index
Voter Turnout/PoliticalInstitutionalization
constant
-0.003
-0.14
0.001
0.66
-0.06
-0.18
0.03
0.01
0.22
o.o~
0.01
0.42
0.01
R2 = 0.04 -2R = 0.003 F = 0.93
Table 4-13.2 Regression of Provoked Repression on Political Participationand Political Institutionalization: log MultiplicationModel (N=67)
parameter standardized standardindependent variable estimate (B) estimate(Beta) error of B F
dependent variable: log Repression
log Voter Turnout -0.56 -0.10 0.70 0.64
log Political Institution- 0.83* 0.25 0.40 4.34a1ization Index
constant 1.072 _ -2 2.85R - 0.08 R = 0.05 F =
*starred (*) estimate is significant at a < 0.05
D. Political Restrictiveness and "Gap" Hypotheses
Regression estimates of the imbalance variables on Political
Restrictiveness dimension are reported in Tables 4-14.1 through 4-17.2.
Social Mobilization/Government Expenditure term (Table 4-14.1) has a
barely significant estimate, while its logarithmic specification
(Table 4-14.2) does not prove it.
98
Table 4-14.1 Regression of Political Restrictiveness on SocialMobilization and Government Expenditure as Percentageof GNP: Ratio Interaction Model (N=63)
independent variableparameterestimate (B)
standardized standardestimate (Beta) error of B F
dependent variable:Political Restrictiveness
Social Mobilization Index -0.75*
Governmental Expen- 0.01*diture % GNP
Social Mobilization/ 4.92*Governmental Expenditure
-1.02
0.19
0.41
0.18
0.01
2.93
17.45
3.58
2.83
constant
R2 = 0.44
1.39
F = 15.35
* starred(*) are those whose parameter estimates are significant ata ~ 0.05
Table 4-14.2 Regression of Political Restrictiveness on SocialMobilization and Government Expenditure as Percentageof GNP: log Multiplication Model (N=63)
independent variableparameterestimate (B)
standardizedestimate (Beta)
standarderror of B F
dependent variable:log Political Restrictiveness
log Social MObilizationIndex
log GovernmentExpenditure % GNP
constant
-0.02
-0.03
0.53
-0.05
-0.03
0.05
0.12
0.15
0.06
R2 = 0.004-2R = -0.03 F = 0.14
99
Table 4-15.1 Regression of Political Restrictiveness on SocialMobilization and Government Responsiveness: RatioInteraction Model (N=8l)
independent variableparameter
estimate (B)standardizedestimate (Beta)
standarderror of B F
dependent variable:Political Restrictiveness
Social Mobilization -0.27*Index
Government Respon- -0.23*siveness Index
Social Mobilization/ -0.004Government Responsiveness
-0.37
-0.30
-0.09
0.11
0.11
0.004
6.08
4.07
1.07
constant
R2 = 0.42
1.66
-2R = 0.40 F = 18.41
* starred (*) are those whose parameter estimates are significantat a ~ 0.05
Table 4-15.2 Regression of Political Restrictiveness on SocialMobilization and Government Responsiveness: logMultiplication Model (N=8l)
independent variableparameterestimate(B)
standardizedest imate (Beta)
standarderror of B F
dependent variable:log Political Restrictiveness
log Social Mobilization -0.02Index
log Government Respon- 0.04siveness Index
-0.05
0.08
0.04
0.05
0.22
0.50
constant
R2 = 0 01.
0.45
F = 0.39
100
The fact that the R2 values drop drastically as we move from the
ratio interaction model to the log multiplicative specifications in
Table 4-14.1 to 4-15.2 indicates that, while variables have powerful
individual effects on the dependent variable, the interaction effects
do not add anything new to the simple additive specifications of the two
variables. Such a drastic change in R2 is not shown in Tables 4-16.1 to
4-17.2. However, when we closely examine the results, it is apparent
that high R2 values in Tables 4-16.2 and 4-17.2 are not due to the ratio
interaction effects but largely reflect a very powerful negative effect
of the Political Institutionalization on our dependent variable.
Table 4-16.1 Regression of Political Restrictiveness on SocialMobilization and Political Institutionalization: RatioInteraction Model (N=81)
independent variableparameterestimate (B)
standardizedestimate (Beta)
standarderror of B F
dependent variable:Political Restrictiveness
Social Mobilization -0.13 -0.18 0.12 1.14Index
Political Institution- -0.37* -0.63 0.08 24.35alization Index
Social MObilization! 0.07 0.05 0.27 0.07Political Institutional-ization
constant 2.82
R2 -2= 0.55 R = 0.53 F = 30.87
<* starred (*) estimate is significant at a 0.05
101
Table 4-16.2 Regression of Political Restrictiveness on SocialMobilization and Political Institutionalization:log Multiplication Model (N=81)
independent variableparameterestimate(B)
standardizedestimate (Beta)
standarderror of B F
dependent variable:log Political Restrictiveness
log Social MobilizationIndex
log PoliticalInstitutionalizationIndex
constant
-0.02
-0.65*
1.11
-0.07
-0.73
0.03
0.07
0.75
86.93
R2 = 0.53 F = 43.76
* starred(*) estimate is significant at a ~ 0.05
Table 4-17.1 Regression of Political Restrictiveness on PoliticalParticipation and Political Institutionalization:Ratio Interaction Model (N=66)
independent variableparameterestimate (B)
standardizedestimate (Beta)
standarderror of B F
dependent variable:Political Restrictiveness
Voter Turnout
Political Institutionalization Index
Voter Turnout/PoliticalInstitutionalization
constant
-0.004
-0.30*
0.01
2.63
-0.10
-0.51
0.29
0.01
0.11
0.01
0.53
6.80
1.65
R2 = 0 55. R? = 0.53 F = 25.52
* starred(*) estimate is significant at a ~ 0.05
102
Table 4-17.2 Regression of Political Restrictiveness on PoliticalParticipation and Political Institutionalization: logMultiplication Model (N=66)
independent variableparameterestimate (B)
standardizedestimate (Beta)
standarderror of B F
dependent variable:log Political Restrictiveness
log Voter Turnout -0.17 -0.11 0.13 1.53
log PoliticalInstitutionalizationIndex
-0.66* -0.74 0.08 73.49
constant 1.85
R2 = 0.53-2R = 0.52 F = 36.77
<* starred(*) estimate is significant at a 0.05
Both insignificant and incorrect signs of log transformed Social
Mobilization Index and Voter Turnout, and high co1linearity30 render
additional support that the additive effects are the main explanatory
variables, rather than interaction effects.
E. Summary and Implications for a More Complete Causal Model
One clear message emerging throughout our analyses in the present
chapter is that the gap hypotheses operationalized and tested in
accordance with the Deutsch-Huntington theory have, in general, very
limited utility for explaining political violence at the cross-national
3
8181
0.79
2
81
1
0.760.88
30Intercorrelations between variables in Table 4-16.1 are asfollows:
1) Social Mobilization Index2) Political Institutiunalization Index3) ratio term (Mobilization/Institutionalization)
103
level. However, this finding does not mean that the theory is wholly
incorrect or that the conclusion derived above is uniformly true of
particular polities. Our generalization is also limited to the 1960's.
If we were able to manipulate the imbalance variables in an exper
imental setting, we might find that some of them have considerable
effects on our political violence measures. However, neither were we
in such a position, nor is it our main concern. Consequently, the con
clusion of this chapter should be taken to indicate that, given the
empirical data at our disposal and the ranges of the variables we have
analyzed in the nonexperimenta1 setting, the imbalance structure observed
in concrete systems of current time have no important causal impacts on
the variations of political violence across countries.
As reported in the various tables, the result of analyses show
relatively strong bivariate effects of the "main" variables to dependent
variables. What is apparently evident is that the interaction effects-
both the ratio and the log multiplicative formu1ations--do not add
significantly to the bivariate additive effects of the main factors. This
brings us to examine the result of our foregoing analyses in terms of
broader causal sequences. We now turn to fit these results into a more
complex causal model in the following chapter.
CHAPTER V
TOWARD A MULTIEQUATION CAUSAL MODEL
Introduction
We will attempt to examine a complex causal relationship in this
chapter. Of course, we should not, at this preliminary stage, pretend
that the model to be tested includes all of the potentially important
factors. Nevertheless, integrating the various results of the two
preceding chapters will simplify our analyses to follow. The primary
reason for doing so has to do with a possible causal ordering among
the variables we have analyzed so far. In the preceding chapters we have
assumed that all the independent variables are in a single causal struc-
ture. Thus, we have examined the effects of economic development and
various imbalance interaction effects among social mobilization,
political participation, and political institutionalization on each of
our dependent variables separately, whereas this assumption is incon-
sistent with the theoretical orientations specified by Deutsch and
Huntington.
1. Theoretical Orientation
Mass participation into politics, according to Deutsch, is primarily
the result of economic growth and its concomitant social mobilization. l
Where people have the right to vote, the effects of socialmobilization are likely to be reflected in the electoralstatistics. This process finds its expression both through
IDeutsch, ~. cit., p. 393.
105
a tendency towards a higher voting participation of thosealready enfranchised and through an extension of thefranchise itself to additional groups of the population.
Similarly, Huntington's theory, by and large, asserts that rapid
increase in social mobilization and political participation--the
principal results of economic development--are responsible for the
"deterioration of political institutionalization" and, in turn, produce
"political decay" in developmental processes. 2 This suggests that
political institutionalization is an intervening variable which com-
prises Deutsch's concepts of capacity and the will of a political
authority to produce desired political goods and to cope with demands and
needs of a society. Thus, we may subsume these intervening variables--
participation, capacity and responsiveness of government, political
institutionalization--under the broadly defined term of political per-
formance. The overall causal sequence implied in the Deutsch-Huntington
theory can then be reconstructed in Figure 5-1.1.
In the following analysis we will deal with the question more simply
by not specifying any particular causal. ordering among the intervening
variables, instead focusing on the direct effect of each variable on
political violence indicators, controlling for the effects of the
variables exogenous to the sub-system specified within the dotted box.
This procedure will allow us to eliminate from the subsequent
analyses those intervening variables lo1hich have relatively insignificant
bivariate effects on any of the political violence indicators. The main
2See Huntington, "Political Development and Political Decay,"World Politics, 17 (April, 1965), pp. 405-411, and Political Order,pp. 32-78.
Figure 5-1.1. An Extended Causal 1100el of Deutsch-Huntington Theory
•
I-----------------~-------------------------------iI ,
Economic' Government I
Development : /!. Capacity(X3) t
t; (Xe )~ Political t ... · '7': )"\_, Govemment ~, ~ Participation : V /'Responsiveness '
SoCiaJ.~ ,(X2) ~ Political (X5) I
Mobilization: Institutionalization(X4)'t (Xm) !---------------------- 1
Independent IVariables
tSocioeconomicDeveloument•
tPoliticalPerformance
PoliticalVioleJlce
~y)
iDependentVariables(Y)
tPoliticalViolence
key: )
(------~
-----)
causal path
concomitant, relationship or equivalent causal structure
plausible feedback effects which are not specifled in thetheory but need to be considered.
~0\
107
justification for this strategy is that in the present context our main
concern is to examine main determinants of the dependent variables among
the intervening variables rather than to establish detailed causal
sequences among the intervening variables.
This procedure would lose most of its validity if our research
were to find out the causal structure among the intervening variables
in Figure 5-1.1.
This task, however, is very cumbersome, if not impossible. Nor
does it constitute our primary research purpose. In addition, in a
nonexperimental situation like ours, there is a considerable degree of
multicollinearity problem between the intervening variables. 3 Multi-
collinearity in such a situation implies that there are few instances
where such variables as mass political participation, political
3The correlations between the intervening variables introduced inFigure 5-1.1 are as follows:
Variables N 1 2 3 4
l. Voter Turnout as % of GNP (X2) 67 52 67 67
2. Government Expenditure as % 63 0.41** 63 63of GNP (X3)
3. Polical Institution-alization Index (X4) 81 -0.12 -0.02 81
4. Government Respon- 81 0.29* 0.17 0.69**siveness Index (X5)
* is significant at p = 0.05** is significant at p = 0.001
108
institutionalization, government capacity and responsiveness diverge
markedly. Thus, there is little opportunity for a theoretically postulated
causal reciprocity and sequential structure to show up in empirical
analyses. If we can experimentally manipulate these variables so that
there is little correlation between, for example, political institution-
a1ization and government respensiveness, then we would be able to observe
the relationship more satisfactorily.
The problem of limited data base we have also do not allow us to
conduct such a sophisticated causal analyses involving both the complex
feedback processes and causal sequences among the intervening variables
specified in Figure 5-1.1. The problem of the causal inference4 involves
more compounded empirical criteria--such as time precedence, experimental
manipulation of the data, etc.--than a mere logical deduction of the
relationships which is loosely defined in the theory we adopt. The data
we have do not sufficiently satisfy any of these empirical criteria.
Therefore, it should be noted that simplifying the research procedure as
we have done on the basis of its overall purpose and of nonexperimenta1
setting is not meant to reject the theory, but only denies its utility
in explaining existing causal relations with data-based regression
analyses, given the limited data base made available to us.
4For more detailed discussions on the structure and empiricalrequirements of causal inferences, see Arthur L. Stinchcombe, ConstructingSocial Theories (New York: Harcourt, Brace &World, 1968), Chapters 2 and3; and Hubert M. Blalock, Jr., "Theory Building and Causal Inferences,"in H. M. Blalock and A. B. Blalock, eds., Methodology in Social Research(New York: McGraw-Hill, 1968), Chapter 5; Blalock, "Causal Inferences,Closed Population and Measures of Association," APSR Vol. LXI, no. 1(March, 1967), pp. 130-136.
109
Thus, it is assumed that in our procedure to follow, due to the
nature of data limitations, the several intervening variables constitute
one complex causal process of reciprocity which cannot easily be un-
raveled empirically or by means of their joint capacity to "move
together" or both. 5 Such a postulation enables us to revise the extended
causal model of Figure 5-1.1 into a simplified version of Figure 5-1.2,
which is more manageable and parsimoniously tuned to actual non-
experimental data with a minimum dissociation from the original theory.
In the following sections, we will first examine bivariate effects
of the intervening variables on each dependent variable. Next, we will
also examine the bivariate relationships between the level of social
mobilization and each dependent variable. Finally, we will integrate
the results we have uncovered through the last three chapters into a
more complex causal sequence, following the model outlined in Figure
5-1.2.
2. Bivariate Effects of Intervening Variables on Political Violence
Now that we have been assured in the last chapter that the inter-
action effects of the intervening variables on our measures of political
violence are insignificant, a straightforward additive specification of
these variables will allow us to estimate the relative importance of the
bivariate effects of the intervening variables on dependent variables.
The equation is:
5ThiS implies, in consequence, that the four intervening variablesin Figure 5-1.1 are indicating different dimension(s) of politicalperformance.
Figure .5 -1.2 A Revised Causal ~todel of Political Violence
l'PoliticalViolence
ion (X2) ..-7\ PolitiCalY (X
J) .. Violence
n- riveness /. ..,(X5) .._--
• DependentVariables
l'PoliticalPerformance
tSocio-EconomicDevelopment
Economic Development7
Political Participa1.~ (Xe) Governmental Capacit4
Social MO~~izationXm) Political Institutio
alization (X4)
Governmental Respon~
InterveningVariables
variables,+.,
,theoreticalstructure
""concept ---)-
•
........o
111
where: YX2X3X4~e
measures of political violenceVoter Turnout as % of ElectorateGovernment Expenditure as % of GNPPolitical Institutionalization IndexGovernment Responsiveness Indexstochastic disturbance
Step-wise regression model is applied to estimate parameters for
the equation. The model stepwisely tests whether, for example, mass
political participation (X2) exerts a significant bivariate effects on
the level of Internal War (Y), controlling for the additive effects of
Governmental Capacity (X3), Political Institutionalization (X4), and
Governmental Responsiveness to mass welfare needs (X5). If all of the
intervening variables have significant direct effects on dependent
variable, all of the parameter estimates (b l , b 2 , b3 and b4) should be
successively included in the step in the order of their relative importance
and be significantly different from zero. On the other hand, if the
effect of Governmental Capacity (X3) can be either solely mediated by
Governmental Responsiveness (X5) or the direct effect of the former, if
any, is negligible compared to that of the latter, then we should expect
that the estimate of b2 is not significantly different from zero, while
that of b4 is significantly different from zero. In any case, if such
a result holds true , we may conclude that X3 does not have any reason
to be included in our subsequent steps to complete the causal specifica-
tions.
Tables 5-1 to 5-3 report the least-squares estimates for equation
(5-1) for each measure of political violence. None of our intervening
variables turned out to have significant effect on Provoked Repression.
Thus, the table for this dimension of political violence is not reported
112
here. Only Voter Turnout as a percentage of total electorate exerts a
direct negative effect on Protest when considered in conjunction with
three other variables (Table 5-1). In interpreting this result, it
should be noted that the bivariate effect of Voter Turnout on Protest
is of only moderate strength (R2 = 0.12). Both Government Responsiveness
Index and Voter Turnout had significantly independent effects on Internal
War, explaining jointly 22 percent of its variance (Table 5-2). The
regression result of Table 5-3 demonstrates that only the level of
Political Institutionalization have a significant and direct negative
impact on our measure of Political Restrictiveness. At the same time,
the impact of Political Institutionalization on Political Restrictiveness
is quite strong, as indicated by the highest amount of variance explained
(R2 = 0.54).
In order to evaluate the overall causal model specified in Figure
5-1.2, we also have to analyze the bivariate effects of social mobi1iza-
tion on various measures of political violence. We now turn to this
problem.
3. Bivariate Effects of Social Mobilization on Political Violence
A straightforward specification of direct effects of Social
Mobilization on political violence is an equation (5-2).
(5-2)
where:
Y = a + b1~ + e
Y = measures of political violenceXm = Social Mobilization Indexe = stochastic disturbance
Table 5-1 Stepwise Regression for Determinants of Protest (N=52)
A. Variable in the Equation (F ~ 2.50, or a < 0.05)
113
independent variableparameterestimate (B)
standardized standardestimate(Beta) error of B F
Voter Turnout -0.02* -0.35 0.01 7.13
constant 1.59
R2 = 0.12
B. Variables not in the Equation
independent variable Beta in Partial Tolerance F
Government Responsiveness 0.07 0.07 0.91 0.25Index
Political Institutionaliza- 0.03 0.03 0.99 0.05tion Index
Government Expenditure 0.18 0.18 0.83 1.58
114
Table 5-2 Stepwise Regression for Determinants of Internal War (N=52)
A. Variables in the Equation (F ~ 2.50, or a < 0.05)
parameter standardized standard Findependent variable estimate (B) estimate (Beta) error of B
Government Responsiveness -0.31 -0.32 0.13 5.85Index
Voter Turnout -0.01 -0.27 0.01 4.14
constant 1.06
R2 0.22 -2 0.19 F 7.05= R = =
B. Variables not in the Equation
independent variable Beta in Partial Tolerance F
Political InstitutionalizationIndex
Government Expenditure
-0.07
0.20
-0.05
0.20
0.41
0.83
0.12
2.07
115
Table 5-3 Stepwise Regression for Determinants of PoliticalRestrictiveness (N=52)
A. Variable in the Equation (F ~ 2.50, or a < 0.05)
independent
Political Institutionalization Index
parameterestimate (B)
-0.43
standardizedestimate (Beta)
-0.73
standarderror of B F
0.06 58.56
constant 3.00
R2 = 0 54.
B. Variables not in Equation
independent variable Beta in Partial Tolerance F
Voter Turnout 0.03 0.05 0.99 0.13
Government Responsiveness -0.17 -0.18 0.53 1.66Index
Government Expenditure 0.04 0.07 1.00 0.21
116
If we follow the Deutsch-Huntington argument ~ toto,6 the sign of
relationship between social mobilization and political violence is
expected to be both positive and significant. Both Deutsch and Hunting-
ton say that social mobilization is a concomitant of economic growth,
implying that the relationship between economic growth or social
mobilization and political stability is primarily a linear positive
function.
However, there are good reasons for anticipating the effect of
social mobilization to political violence to be nonlinear. As we have
demonstrated in Chapter I, the dominant relationships between the level
of economic development and political violence were, if any, mostly
curvilinear. Thus, since the social mobilization is posited to be
concomitant with economic development, and the level of economic deve1op-
ment were curvilinearly related to political violence, then it logically
follows that the relationship between social mobilization and political
violence should be also curvilinear. Apart from the logical reason, the
nonlinear relationship also has a reasonable interpretation in its sub-
stantive meaning, implying that the beginning stages of increasing social
mobilization are more critical than later ones in regard to developmental
6Consider the following statement by Deutsch: "The increasing numbers of the mobilized population, and the greater scope and urgency oftheir needs for political decisions and governmental services, tend totranslate themselves, albeit with a time log, into increased politicalparticipation. This may express itself informally through greaternumbers of people taking part in crowds and riots, in meetings anddemonstrations, in strikes and uprisings, or, less dramatically, asmembers of a growing audience for political communications, written orby radio, or finally as members of a growing host of organizations."Deutsch, ~. cit., p. 393.
117
processes of polities. At the same time, as a society approaches higher
levels of social mobilization, the effects of social mobilization on
political violence may vary in their characteristic modes, as well as in
the magnitudes. Finally this argument is also consistent with the
"threshold" hypothesis of political development, suggesting the presence
of a threshold beyond which the impact of further social mobilization on
democratic performance is not so pronounced. For example, Deane E.
Neubauer argues: 7
certain levels of 'basic' socio-economic development appearto be necessary to elevate countries to a level at which theycan begin to support complex, nationwide patterns of politicalinteraction, one of which may be democracy. Once above thisthreshold, however, the degree to which a country will 'maximize'certain forms of democratic performance is no longer a functionof continued socio-economic development. (Emphasis added.)
The relative merit of the linear versus the curvilinear hypotheses
can be evaluated in the same way as we have evaluated the relationship
between economic development and political violence in Chapter III.
Thus, we specify the following curvilinear equations:
(5-3)
(5-4)
where:
Index.
2Y = a - blXm + b2 (Xm)·· + e
Y = a - bllnXm
1nXm is logarithmic transformation of the Social Mobilization
If the linear hypothesis is correct, the estimate of b2 in equation
(5-3) will not be significant, and the degree of fitness (variance
7Deane E. Neubauer, "Some Conditions of Democracy," APSR, Vol. 61,(Dec., 1967), p. 1007. See also Charles F. Cnudde and D.~Neubauer,"New Trends in Democratic Theory," in Cnudde and Neubauer, eds.,Empirical Democratic Theory (Chicago: Markham Publishing Co., 1969),pp. 511-533.
118
explained: R2) in (5-3) and (5-4) will not be significantly greater
than that from (5-2). If the nonlinear model is correct, both bl and
b2 in (5-3) and (5-4) will be significant, and, at the same time, the
relative size of R squared derived by (5-3) and (5-4) will be greater
than that of (5-2). The difference between (5-3) and (5-4) is such that,
if (5-3) fits better, the dominant relationship is the one which typically
entails an exponentially declining or increasing level of political
violence beyond some threshold, rather than a mere "flattening out"
tendency at higher level of social mobilization.
Regression estimates of linear and curvilinear hypotheses are
reported in Table 5-4 to Table 5-7. Table 5-4 clearly dem:lUstrates that
Protest has little to do with the level of social mobilization, although
the direction of the relationship is consistent with the Deutsch
Huntington hypothesis in all of our estimates. Note that the logarithmic
specification improves the goodness of fit criterion somewhat, but it
fails to reach an acceptable level of significance. Social mobilization
also failed to explain Provoked Repression in all of our three
specifications (Table 5-5). Social mobilization has rather significant
impacts on both Internal War and Political Restrictiveness (Table 5-6
and Table 5-7). However, in both cases the direction of the relationship
is negative, contrary to the Deutsch-Huntington argument. Note also
that curvilinear specifications do not provide better results. This
implies that, in these two particular dimensions of political violence,
the criteria of goodness of fit and parsimony compel us to reject the
utility of curvilinear arguments.
How can these results be best integrated into the overall causal
model suggested in Figure 5-1.2. We now are ready to answer this question.
119
Table 5-4. Linear and Curvilinear RegressioIlE of Protest onSocial MObilization Index (N=81)
parameterindependent variable estimate (B)
Social Mobilization Index 0.08
constant 0.001
standardizedestimate (Beta)
0.08
standarderror of B F
0.11 0.54
Social Mobilization Index
Social MobilizationIndex, squared
constant
R2 = 0.03
log Social MobilizationIndex
constant
R2 = 0.04
0.04
0.16
-0.12
0.17
0.06
0.04
0.16
R:2 = 0.005
0.20
0.12
0.12
F = 1.19
0.10
F = 3.16
0.11
1.83
3.16
120
Table 5-5. Linear and Curvilinear Regressions of Provoked Repressionon Social MObilization Index (N=81)
parameter standardized standardindependent variable estimate(B) estimate (Beta) error of B F
Social Mobilization Index -0.15 -0.15 0.11 1.72
constant -0.002
R2 = 0.02
Social Mobilization Index -0.14 -0.14 0.12 1.48
Social Mobilization Index, -0.01 -0.02 0.11 0.02squarred
constant 0.01
R2 0.02 -2-0.004 F 0.86= R = =
log Social MobilizationIndex
0.04 0.04 0.10 0.15
constant 0.01
R2 = 0.002
Table 5-6. Linear and Curvilinear Regressions of Internal War onSocial Mobilization Index (N=8l)
121
independent variableparameterestimate (B)
standardized standardestimate(Beta) error of B F
Social Mobilization Index -0.31* -0.33 0.10 9.65
constant -0.005
R2 = 0.11
Social Mobilization Index -0.29* -0.32 0.10 8.20
Social Mobilization Index -0.04 -0.04 0.10 0.14squarred
constant 0.03
R2 0.11-2
0.09 F 4.84= R = =
log Social Mobilization 0.12 0.15 0.09 1. 70Index
constant 0.04
R2 0.02-2 0.01= R =
* starred (*) estimates are significant at a ~ 0.05
122
Table 5-7. Linear and Curvilinear Regressions of PoliticalRestrictiveness on Social Mobilization Index (N=81)
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
Social Mobilization Index -0.46* -0.62 0.07 49.10
constant 1.68
R2 = 0.39
Social Mobilization Index -0.47* -0.63 0.07 46.50
Social Mobilization Index, 0.03 0.04 0.07 0.20squarred
constant 1.65
R2 0.39 -20.37 F = 24.38= R =
log Social Mobilization -0.05 -0.09 0.07 0.57Index
constant 1.67
R2 0.01-2
-0.005 0.57= R = F =
<* starred (*) estimates are significant at a = 0.05.
123
4. Toward Multiequation Specifications
A. Provoked Repression
In order to put our analyses into a broader theoretical perspective,
it would be helpful to integrate what we have found in the preceding
chapters in line with the causal model outlined in Figure 5-1.2. In
addition, if we can specify provisional models out of the various results,
it will help to unravel the basic causal processes underlying the data.
In Chapter III, we found that the level of economic development has
no systematic and direct bivariate effect on the Provoked Repression.
We found in Chapter IV that none of the imbalance specifications add any
empirical elements to our analysis. Analyses reported in Chapter V also
demonstrated that none of the four intervening variables was significantly
related to the Provoked Repression. Similarly, Social Mobilization
failed to have any direct impact on the Repression. Therefore, we shall
have to look elsewhere for an explanation of the Provoked Repression.
B. Protest
Energy Consumption per capita and Social Mobilization Index had no
systematic direct effects on Protest. Neither any of the imbalance
specifications exerted any systematic effect on it. However, we find
that Protest has a moderately negative relationship with Voter Turnout
as a percentage of total electorate population (Table 5-1), though with
none of the remaining variables included in Figure 5-1.2. Thus, the
provisional8 path model of Protest block can be specified as Figure 5-2.
8The model is "provisional" in that this and following path modelsmake no pretense to cover all other potentially important factors. Itonly starts toward such a direction.
124
Figure 5-2. Provisional Path Model of Protest (N=67)
Voter Turnout(X2) >a: path coefficient (standardized regression coefficient) in this
case is zero-order correlation.
b: 87.75% of variance is unexplained for Protest.
C. Political Restrictiveness
Figure 5-3.1 is a summary of findings derived from the foregoing
analyses. Note that our analyses so far is incomplete until we link
Energy Consumption per capita and Social Mobilization to Political
Institutionalization, which is postulated as an intervening variable.
The introduction of the intervening variable also poses a possible
problem of "spurious,,9 relationships between Energy Consumption per
capita or Social Mobilization with Political Restrictiveness. To
complete the model, we will first look into the bivariate relationships
of Energy Consumption per capita and Social Mobilization with Political
Institutionalization. Then, we will further test the spuriousness
hypotheses to see if the bivariate relationships of Energy Consumption
per capita and Social Mobilization with Political Restrictiveness dis-
appear when considered in conjunction with the intervening variable.
9Spurious relationship is defined as a relationship between twovariables, X and Y for example, in which X's correlation with Y issolely the result of the fact that X varies along with some othervariable(s), Z for example, which is indeed the true predictor of Y.In such case, controlling for the effect of Z on Y (or held constant),Y no longer varies with X.
Figure 5-3.1 Recapitulation of Analyses on Political Restrictiveness
Political.:Restrictiveness
(Ypr)
"7'\,/'
r=r- 7'
(Table .5-3)'"
curvilinear: loganthmic (-).- ------(Table 3-2)
. -) Political~ Institutionalization
(X4)
~ (Tab!e 5-7)
linear (-)
,,,Social Mobilization'
(X )m
Energy Consumptionper capita (X ) ,
e "
['.
•
keys Tables in parentheses indicate sources of findings.Dotted arrows are unanalyzed parts.Arrows denote direction of causal sequences.Symetric arrow denotes concomitant relationship •
t-ANVI
126
In order to examine the effect of economic development and social
mobilization on our dependent variable, the following regression equations
are postulated. IO
(5-5)
(5-6)
(5-7)
linear hypothesis
curvilinear hypothesis
curvilinear hypothesis
~ Energy Consumption per capita (Xe), Social Mobilization Index (Xm)
X4 Political Institutionalization Index
e stochastic disturbance
Regression estimates of the Political Institutionalization Index for
the three specifications are reported in Tables 5-8 and 5-9. Political
Institutionalization is best represented by the logarithmic function of
Energy Consumption per Capita (Table 5-8), indicating that as economic
development proceeds beyond a certain level, its effect on political
institutionalization "flattens out," though it does not become negative.
The relationship between Political Institutionalization and Social
Mobilization best fits a polynomial specification (Table 5-9). The
result suggests that, while the relationship is highly positive up to a
certain level, it becomes gradually negative beyond the threshold level.
Therefore, we conclude that the linear hypothesis is rejected and that
the data fit the curvilinear thesis.
10Note that the linear versus non-linear arguments discussed insection 3 of the present chapter is valid to this relationship, sincedefinitional and empirical constructs of "democratic performance" of Dahl,and Neubauer obviously include institutionalization, participation, andresponsiveness of government to mass welfare demands. See Robert A. Dahl,Preface to Democratic Theory (Chicago: University of Chicago Press, 1956),and Neubauer, E£.. cit.
127
Table 5-8. Linear and Curvilinear Regressions of PoliticalInstitutionalization on Energy Consumption per capita(N=81)
independent variable
Energy Consumptionper capita
parameterestimate (B)
0.0004*
standardizedestimate (Beta)
0.60
standarderror of B F
0.0001 43.36
constant 2.57
R2 = 0.35
Energy Consumption 0.0008* 1.35 0.0001 43.63per capita
En~rgy Consumption -0.00* -0.83 0.00 16.36per capita, squarred
constant 2.32
R2 0.47-2
0.45 F 34.08= R = =
log Energy Consumptionper capita
0.51* 0.72 0.06 87.39
constant -0.12
R2 = 0.53
* starred (*) estimates are significant at a ~ 0.05
128
Table 5-9. Linear and Curvilinear Regressions of PoliticalInstitutionalization on Social Mobilization Index (N=81)
Social Mobilization Index
parameterestimate(B)
0.96* 0.76 0.09
F
108.17
constant 3.07
R2 = 0.58
Social Mobilization Index 1.03* 0.82 0.09 124.12
Social MObilization Index, -0.25* -0.20 0.09 7.37squarred
constant 3.27
R2 0.61 -2 0.60 F = 62.14= R =
log Social Mobilization 0.04 0.03 0.12 0.10Index
constant 3.07
R2 = 0.001
* starred (*) estimates are significant at a f 0.05.
Difference of R2 between polynomial (R2 = 0.61) and linear (R2 = 0.58)is significant at a = 0.05 (F = 6.0).
129
Now that the bivariate effects of the variables included in
Figure 5-3.1 are all known, we now proceed to complete a path model of
Political Restrictiveness by looking into the possibility of spurious
relationships of two socioeconomic development variables to Political
Restrictiveness, when the intervening variable Political Institutionaliza-
tion is taken into consideration. Since Political Institutionalization
is construed as a form of political performance, it is to be represented
as causally prior to the dependent variable, but preceded by the two
independent variables. ~t the same time, the theory provides no causal
ordering between the two independent variables, since they are viewed as
theoretically equivalent concomitant variables or alternative empirical
indicators of socioeconomic development. If these arguments are valid,
the provisional path model for Political Restrictiveness has a two-
equation recursive structure involving the following specifications:
(5-8.1)
(5-9.1)
Ypr = a - bllnXe - b2Xm b3X4 + e
X4 = a + bllnXe + b2Xm - b3 (Xm)2 + e
key: Ypr Political RestrictivenesslnXe log Energy Consumption per capitaAll other terms are defined before.
Note that, in line with analyses done so far, equation (5~8.l)
includes all the variables which have direct bivariate effects on
Political Restrictiveness so that all possible paths i~plied by the
theory they are specified in this initial model. ll Following the causal
Ilsigns are also adjusted according to the results reported inTable 3-2 (Energy Consumption per capita), Table 5~8 (Social Mobilization),and Table 5-3 (Political Institutionalization).
130
assumption we have discussed, Political Institutionalization is forced
to enter into the first step and no ordering is specified between the
two independent variables. 12 Parameter estimates of the model derived
by such a procedure will enable us to test for direct effects, develop-
mental sequences via indirect effects, and possible spuriousness 0f our
bivariate results. If, for example, the effects of Energy Consumption
per capita and Social MObilization on Political Restrictiveness are
wholly indirect (mediated entirely by Political Institutionalization),
the estimates of bl , b2 in equation (5-8.1) would be insignificant.
Such a result, in other words, indicates that Political Institutionaliza-
tion mediates all of the effects of socio-economic development on
Political Restrictiveness. If, however, all the parameter estimates are
significant, including b3 , this will imply that the direct and indepen-
dent effects of two independent variables remain significant even if we
control for the mediating effects of Political Institutionalization.
Also following the results of prior analyses, the equation (5-9.1)
specifies the effect of socioeconomic variables on Political Institution-
alization as curvilinear functions--logarithmic relationship of Energy
Consumption per capita (Table 5-8) and polynomial relationship of Social
MObilization (Table 5-9). This specification will test whether or not
the two socioeconomic development variables have non-spurious independent
impacts on Political Institutionalization. In line with the established
l2This is to examine whether any or both of the two socioeconomicdevelopment variables exert non-spurious additional impacts on thedependent variable after the direct impact of the intervening (PoliticalInstitutionalization) variable on Political Restrictiveness is controlledfor.
131
causal assumption, the estimate for the Political Institutionalization
(equation 5-9) is derived by stepwise regression analysis.
Regression estimates for two equations are reported in Table 5-10
and Table 5-11. While each of the socioeconomic development variables
had significant bivariate effects on Political Restrictiveness, these
direct effects disappear altogether when Political Institutionalization
is taken into account (Table 5-10). Among the independent variables,
log Energy Consumption per capita also drops below our significance
level (Table 5-11). Thus, out of the result of two tables, we draw the
following conclusions:
(1) The impact of socioeconomic development variables on Political
Restrictiveness is primarily indirect and mediated by Political
Institutionalization, and, therefore;
(2) The bivariate effects of these independent variables revealed in
prior analyses become spurious once the effect of the intervening
variable is taken into account.
(3) Social Mobilization in its curvilinear specification is a prime
causal variable for Political Institutiona1ization--that is, while
social mobilization exerts a powerful positive impact on political
institutionalization up to a certain threshold point, its effect tends
to decrease afterwards.
(4) By the corollary of (1), (2) and (3), the developmental causal
assumption of Huntington's theory is generally confirmed by our data,
but only for Political Restrictiveness dimension. That is, socioeconomic
development in general and social mobilization in particular constitute
a powerful inhibitive source of structure-oriented political violence
132
Table 5-10. Stepwise Regression for Determinants of PoliticalRestrictiveness (N=80)
A. Variable in the Equation of (F ~ 2.70 or a < 0.05)
intervening variable
Political Institutionalization Index
parameterestimate (B)
-0.43
standardizedestimate (Beta)
-0.73
standarderror of B F
0.04 91.36
constant 3.00
R2 = 0.54
B. Variables not in the Equation
independent variable Beta in Partial Tolerance F
log Energy Consumption -0.18 -0.18 0.47 2.60per capita
Social Mobilization -0.15 ~0.14 0.42 1. 61Index
Table 5-11. Stepwise Regression for Determinants of PoliticalInstitutionalization (N=81)
A. Variables in the Equation (F ~ 2.70, or a < 0.05)
133
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
Social Mobilization Index 1.03 0.82 0.09 124.12
Social Mobilization Index, -0.25 -0.20 0.09 7.37squared
constant 3.27
R2 = 0.61 R2 = 0.60 F = 62.14
B. Variable not in the Equation
independent variable
log Energy Consumptionper capita
Beta in
0.14
Partial
0.10
Tolerance
0.20
F
0.77
134
mainly through the increased level of "p1uralism,,13 in political
institutions and the procedures.
These arguments can be more parsimoniously represented in a path
model if we revise the above two equations by removing the "over
identifying" variables. Thus, we remove two independent variables from
the equation (5-8.1), and Energy Consumption per capita from (5-9.1) so
that they would not exert any spurious impacts on respective variables
being predicted. Thus, we revise (5-8.1) and (5-9.1) as follows:
(5-8.2)
(5-9.2)
Ypr = a - b1X4 + e
X4 = a + b1
Xm
- b2
(Xm
)2 + e
Path coefficient (standardized regression coefficient) for (5-8.2)
becomes, since it contains no third variable, zero-order correlation
between Political Institutionalization and Political Restrictiveness.
Combining it with the estimation of (5-9.2), we revise Figure 5-3.1 and
derive a path model of Political Restrictiveness in Figure 5-3.2.
D. Internal War
Figure 5-4.1 recapitulates our bivariate analyses for Internal War
reconstructed in line with Figure 5-1.2. Following the same procedure as
we have followed in regard to Political Restrictiveness, we will first
analyze the relationship between socioeconomic variables and the two
13Note that the prevailing understanding of political institutionalization as centralization, structural unity or integration is not whatI mean as political institutionalization. Our measure of politicalinstitutionalization (see Chapter IV, Section 2, c) is closer to whatHuntington originally purports to measure--that is, political pluralism-but not what he referred to as "institutionalized" polities or parties.Therefore, our result is to be read; the more pluralism in politicalorganizations and their procedures, the less political restrictiveness.
'. ""- -....... - .~re 5-3.2 Provisional Path Model of Political Restrictiveness (N=80)
. :
,., b~
Ilog.' Energy Consumptionper" capita (lnX )
e
Social Mobllization (Xm) 0.63c 0.68
~:: MobU1""t10n.~ P01£Oal -0.13 ~ PO[t10alsquared (XJIl)2 .,11 Institutionalization Restrictiveness
.
keYI al zero-o:rder (unanalyzed) correlation.
bl weak (insignificant) causal link.
CI the residual. path coefficients (coefficient of alienation) are
calculated by the fOrmulal; 1 _ R2 .0
• 1', otis Dudley Duncan. "Path AnalysiSI Sociological Examples." inAmerican JOUDlal of Sociologl. Vol. 72.PPu 1-16. reprinted in Blalock. ed,
'ICausal Models in the Social Sciences (Chicagol Aldine-Atherton. 1971) ....
w"'"
Figure 5-4.1 Recaptu1ation of Analyses on Internal War
Internal War
(Yi )
linear (-)
(X2)
{Table 5-6
curvilinear: polynomial (-)
- (Tab1e)-2)
Energy Consumption -------:,.
(
per capita (Xe
) "'. //1
".J' "
. " ~Social Mobilization -------~
(Xm) \
keYI Tables in parentheses indicate sources of findings.Dotted arrows are unanalyzed parts.Arrows denote direction of causal sequences.Symetrlc arrows denote concomitant (or reciprocal.) relationships•
•
~
\oJ0\
137
intervening variables which remained significant in our prior analysis.
This will be followed by a test of the spurious relationship of the
independent (socioeconomic) variables so that the model can be established
parsimoniously.
Since we postulated that all of the intervening variables are
possible measures of "democratic" political performance, the linear
versus nonlinear arguments are to be tested in a manner similar to our
prior analysis. Thus, the specifications of the arguments are as
follows:
(5-10) Xj = a + b1X
i+ e ------------ linear hypothesis
(5-11)2
X· = a+ b1Xi - b2 (Xi ) + e - curvilinear hypothesisJ
(5-12) Xj = a+ b 1nX + e ---------- curvilinear hypothesis1 i
Xi Energy Consumption per capita (Xe), Social Mobilization Index (Xm).Xj Voter Turnout (X2), Governmental Responsiveness (X5)e stochastic disturbance
Tables 5-12 and 5-13 are the results of linear and curvilinear
regression estimates. The relationship between Energy Consumption per
capita and Voter Turnout disconfirms Deutsch-Huntington's linear
hypothesis. The data are more consistent with threshold thesis of
Neubauer, although the overall explanatory power is rather weak (R2 = 0.08).
It should also be noted that once a certain threshold is reached, the
degree to which a country will experience mass political participation is
a rapidly decreasing function of further industria1ization. 14 Figure
14This is inferred by the fact that, while the Voter Turnout showsan increasing tendency in relation to corresponding level of EnergyConsumption per capita (positive regression coefficient for Energy Consumption per capita), it drops rather rapidly as countries approach tothe highest level of industrialization (negative regression coefficientfor exponential function of Energy Consumption per capita). According toFigure 5-4.2 the "threshold point" is around 4600 kilograms per capita asof 1965.
138
5-4.2 shows this pattern more visually.
The Social Mobilization Index, however, has no significant
estimates for any of three specifications, implying that it has little
to do with Voter Turnout directly (Table 5-13). This prompts us to
establish the path of Energy Consumption per capita + Voter Turnout,
derived from Table 5-13, which is non-spurious even when Social MObiliza
tion is taken into consideration.
Table 5-12. Linear and Curvilinear Regressions of Voter Turnout onEnergy Consumption per capita (N=67)
independent variablesparameterestimate (B)
standardized standardestimate(Beta) error of B F
Energy Consumption per capita 0.001 0.12 0.001 1.01
constant 76.07
R2 = 0.02
Energy Consumption per capita 0.01* 0.69 0.002 5.31
Energy Consumption per capita,-O.OO* -0.61 0.000 4.26squarred
constant 73.54
R2 -2= 0.08 R = 0.05 F = 2.66
log Energy Consumption 1.03 0.10 1.22 0.71per capita
constant 71.1
R2 = 0.01
<* starred (*) estimates are significant at a = 0.05.
-:l'"~+>Col
~W
....~::.~0
~
IIIIII.,::J0
f.,alot
:l0>. -
.'w'
Figure 5-4.2: Scatter Diagram of Voter Turnout across Energy Consumotion per Capita: 1965 (N=67)
.+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+----+ ...._-+.I, 99.60+ • +
1'" .* .... 11 . J
·1* ... • II.. '" J92 ••~ + *. +. I. l
1 e It I1 I1 .. * • 1
e5"2~+ • ... +1 ... '" • J
.I. I; I • ¥ • I
1 ... I.,q.'.,.... • +.V.... .... I
I . I1 1Il CI • --.Canada t
"''' * ,7«:.96+ '" ... +I 2'" II .. ,1 ... 11* "'... 163.80+ +1 1
. I I1 ,jl. 1I. !
5~.64 + • +I 1I * J1" ... . I1 • ,
69.48+ +I I1 III I1 I1 J
42.32 + +1 ' ,I ,1 . I1 $ J
15.16 + • +I 1I '" I
• 1 t1 . !
28.0n .4l . +
..----+---~----~----.----+----+_---+----~---+----+_---+----~---+----~---4---_t_---+---_t_---+·---•.O.C 939.0 1~~~.~ !7~7.C 372A.O 455~.O 5584,~ 6~13.0 7••~.O e~71." ;~oc.o
(Energy Consumption per capita in 1965: kilograms) ~W\0
•
140
Table 5-13. Linear and Curvilinear Regressions of Voter Turnout onSocial Mobilization Index (N=67)
independent variable
Social Mobilization Index
parameterestimate (B)
1.06
standardizedestimates (Beta)
0.06
standarderror of B F
2.18 0.24
constant 77.50
Social Mobilization Index 0.18
Social Mobilization Index, 3.11squarred
constant 75.04
R2 = 0.03
0.01
0.18
R2 = 0.003
2.25
2.21
0.01
1.97
log Social Mobilization 0.63 0.04 1.88 0.11
constant 77.70
Tables 5-14 and 5-15 are estimates of the three equations for the
Government Responsiveness Index. The results, by and large, suggest
that, for both Energy Consumption per capita and Social Mobilization,
polynomial specifications best capture the pattern of relationships.
It is also indicated that the effect of social mobilization on govern-
ment welfare performance is a positive exponential function beyond a
certain threshold level (positive regression coefficient for squared
Social MObilization Index), while the case is not true for Energy Con-
sumption per capita (negative sign for squared Energy Consumption per
capita).
141
Table 5-14. Linear and Curvilinear Regressions of GovernmentResponsiveness on Energy Consumption per capita (N=81)
independent variable
Energy Consumption percapita
parameterestimate (B)
-0.0004*
standardizedestimate (Beta)
0.84
standarderror of B F
0.00003 187.50
constant -0.63
R2 = 0.70
Energy Consumption 0.0007* 1.53 0.00006 147.83per capita
Energy Consumption -0.00* -0.76 0.0 36.30per capita, squarred
constant -0.80
R2 -2F = 153.79= 80 R = 0.79
log Energy Consumption 0.43* 0.81 0.03 152.81
constant -2.77
R2 0.66 -2 0.65 F = 152.81= R =
* starred (*) estimates are significant at a ~ 0.05.
Table 5-15. Linear and Curvilinear Regressions of GovernmentResponsiveness on Social Mobilization Index (N=8l)
142
parameter standardized standardindependent variable estimate (B) estimate (Beta) error of B F
Social Mobilization Index 0.75* 0.80 0.06 140.50
constant -0.10
R2 = 0.64
Social MObilization Index 0.71* 0.76 0.06 122.10
Social Mobilization Index, 0.13* 0.14 0.06 4.24squarred
constant -0.21
R2 0.66 -2 0.65 F 75.25= R = =
log Social MobilizationIndexconstant
2R = 0.02
0.12
-0.07
0.15 0.09 1.71
* starred (*) estimates are significant at a ~ 0.05
Difference of R2 between linear and curvilinear (polynomial)regression is significant at a = 0.05 (F = 4.4).
143
In the light of these results, we now test for direct effects,
indirect effects, and possible spuriousness. Since Voter Turnout and
Government Responsiveness are construed as different forms of political
performance, they are to be represented as causally prior to the dependent
variables. Given at the same time that they are viewed as theoretically
equivalent, there is no theoretical rationale for specifying a causal
ordering between Voter Turnout and Government Responsiveness. Thus, the
complete model has a three-equation recursive structure involving the
following specifications:
(5-13.1) Yi = a - b X + b (X ) 2 - b X - b X - b X + e1e 2 e 3m 42 55
(5-14.1) X2 = a + b1Xe - b2 (Xe )2 + b3X5 + e
(5-15.1) X5 = a + b1X
e- b
2(X
e) + b
3X
m+ b
4(X
m)2 + b
5X
2+ e
Note that in both (5-14.1) and (5-15.1), the estimates also control for
the effects of the other intervening variables (Government Responsiveness
(X5) in equation for Voter Turnout (X2)' and Voter Turnout in equation
for Government Responsiveness) which are construed as reciprocally
related to each other. Social MObilization is not included in equation
(5-14.1), since it is demonstrated1y (Table 5-13) unrelated to Voter
Turnout.
Consistent with established causal order, the regression procedure
called intervening variables to enter prior to the independent variables.
The results of estimation are reported in Table 5-16, 5-17 and 5-18.
None of the independent variables exert significant effects on Internal
War when the two intervening variables are controlled for (Table 5-16).
This result prompts us to conclude that, when the intervening variables
were taken into account, the bivariate relationships of Energy Consumption
144
Table 5-16. Stepwise Regression for Determinants of Internal War (N=67)
A. Variables in the Equation (F ~ 2.30, or a < 0.05)
parameter standardized standardintervening variable estimate (B) estimate (Beta) error of B F
Government Responsiveness -0.31 -0.32 0.11 7.64Index
Voter Turnout -0.01 -0.27 0.01 5.40
constant 1.06
R2 0.22 -2 0.20 F 9.21= R = =
B. Variables not in Equation
independent variable Beta in Partial Tolerance F
Energy Consumption per capita -0.04 -0.02 0.28 0.03
Energy Consumption per capita, 0.04 0.03 0.55 0.06squared
Social Mobilization Index -0.18 -0.12 0.33 0.88
per capita and Social Mobilization to Internal War that we have uncovered
before become spurious. This means that, in general the developmental
causal assumption implicit in Deutsch's theory--the view that socio-
economic development operates as an inhibiting source for political
violence mainly through the mediating mechanisms of political participa-
tion and increased responsiveness of government on mass we1fare--is
warranted by cross-national data on this dimension of political violence.
When the complete specification in line with equation (5-14.1) is
estimated, Energy Consumption per capita drops out of significance, while
145
Table 5-17. Stepwise Regression for Determinant of Voter Turnout (N=67)
A. Variables in the Equation (F ~ 2.70, or a < 0.05)
parameter standardized standardvariables estimate (B) estimate (Beta) error of B F
intervening variable
Government Responsiveness 9.18 0.49 2.84 10.42Index
independent variable
Energy Consumption -0.00 -0.30 0.00 3.97per capita, squared
constant 80.47
R2 0.14 -2 0.11 F 5.22= R = =
B. Variable not in the Equation
independent variable Beta in Partial Tolerance F
Energy Consumption per capita -0.19 -0.05 0.06 0.15
its exponential function remains significant (Table 5-17). We may, thus,
infer that the main direct source of variation in Voter Turnout across
countries i.s their performance in the form of increased general welfare
which is posited as an alternative form of political performance. The
negative sign for an exponential function of Energy Consumption per
capita further indicates that, controlling for the effect of Governmental
Responsiveness, countries at the highest level of economic development-
notably USA and Canada15_-tend to experience a typically declining
l5See Figure 5-4.2.
146
pattern of voting participation. Governmental Responsiveness seems to
have the most complex causal structure. All but one specification
(exponential function of Social Mobilization) are included in the
equation (Table 5-18). Note that direct effect of Voter Turnout on this
variable is not as strong as those of independent variables. The
result, by and large, suggests that, (1) high amounts of wealth available
in society conjoined with high social mobilization is a rerequisite for
a responsive government in meeting general welfare demand, and (2)
countries of the highest level of economic development, however, do not
necessarily warrant a corresponding level of performance in terms of their
welfare functions.
We now are ready to draw a path model of Internal l\Tar by eliminating
the spurious variables for equations (5-13.1) to (5-15.1). They become
respectively:
(5-13.2)
(5-14.2)
(5-15.2)
Yi = a - b l X2 - b2X5 + e
X2 = a - bl
(Xe
)2 + b2
X5
+ e
X5 = a + blXe - b2 (Xe )2 + b3~ + b4X2
By estimating respective paths, we transform Figure 5-4.1 into a path
model of Internal War drawn in Figure 5-4.3.
Table 5-18. Stepwise Regression for Determinants of GovernmentalResponsiveness (N=67)
A. Variables in the Equation (F > 2.30, or a < 0.05)
147
parameter standardized standardvariables estimate(B) estimate (Beta) error of B F
intervening variable
Voter Tumout 0.01 0.15 0.00 7.63
independent variables
Energy Consumption 0.001 1.08 0.00 33.03per capita
Energy Consumption -0.00 -0.51 0.00 11.62per capita, squared
Social Mobilization 0.24 0.25 0.09 7.53Index
constant -1.23
R2 0.83-2
0.82 76.98= R = F =
B. Variable not in the Equation
independent variable
Social MObilization Index
Beta in
0.01
Partial
0.03
Tolerance
0.52
F
0.04
0.78
Figure .5-4.3 Provisional Path Model of Intemal War (N=67)
0.41Energy Consumption~8 .f'per capita (X ) '" ~ GoveIllJllent 0.88
to.91 e -'0. 51/1 Res~~:~vTSS~ C
r.: ' 10.49 1°.15 ~per capita. squared -0.39 ~0.27
~
\1' (x)2 Voter Turnout~0.61 e . 0.2.5 • _ - -" (X
2) t..
0.93Social Mobilization
(xm)
a I zero-omer (unanalyzed) correlation.
, -' '.-. - .- Dotted arro'NS are 'Neak (insignificant) causaJ. link.
....~co
PART III. TOWARD A NEW THEORY OF POLITICAL VIOLENCE
Introduction
This part begins with a synopsis of findings reported in the preced
ing part. This will be done by means of a schematic depiction of the
problems &~d shortcomings of the causal model we adopted in Chapter V,
in order to set an analytical base for an alternative formulation of the
model.
The alternative model proposed is selectively adopted from the
power and conflict paradigm of political performance and political action.
As with any model in social sciences, the alternative model is an
abstraction, purporting to represent reality, whose test of validity is
not whether it constitutes a true mirror of a particular political system,
but rather whether it provides a framework more useful for analysis of
the "hidden mechanisms" and forces that shape the process of political
performance in any political system than other rival models. As we
proceed along such a theoretical task, it becomes evident that a modeling
of the empirical world is intricately linked with a particular philosoph
ican judgment on "what is politics and political process?" Therefore,
the synopsis of our foregoing analyses is immediately followed by an
explication of such a "world view" implicitly adopted in the rival
models, namely, functionalist vs. power and conflict models. A series of
hypotheses will be derived thereafter as a step toward building an
alternative model of political violence.
The results of empirical evaluation of the key hypotheses
established by the alternative model are reported in Chapters VII and
150
VIII. The final chapter will integrate the analyses of Parts II and III,
synthesizing the cross-cutting and complementary explanatory powers of
the two perspectives in such a way to improve our scientific knowledge
on the problem addressed in the present research.
CHAPTER VI
SOME CHALLENGING HYPOTHESES
1. Preliminary Observations
Several conclusions may be drawn from the results of our prior
analyses. We will review them in order to set an analytical stage for
our subsequent inquiry.
First of all, we find that the overall explanatory power of the
model proved to be of limited predictive power, except in regard to
explaining the Political Restrictiveness dimension of political violence.
As we have noted before, none of the explanatory variables postulated
according to the model had any significant effect on Provoked Repression.
Protest turned out to be related to only one of the performance variables
--Voter Turnout--with a moderate degree. We have also demonstrated that
socioeconomic development has a negative causal impact on Internal War,
but only indirectly through increased political participation (Voter
Turnout) and Government Responsiveness. However, for both Protest and
Internal War, the overall explanatory power of the model proved to be
rather weak. l Particularly damaging to the validity of the Huntington-
Deutsch theory is the fact that it is conceptualized to explain mainly
extra-institutional or mass political violence, which largely constitute
our measures of Protest and Internal War. Yet, it is for these dimensions
of political violence that the theory proved to be of limited empirical
validity.
IConsider moderate magnitudes of R2 or very high coefficients ofalienation for both Protest and Internal War that are reported in thelast chapter.
152
The findings of Chapter V lend additional credence to the second
problem of the model, namely the uni-dimensional conception of political
violence. Theories and hypotheses examined in Part II did not provide
any conceptual base by which we can distinguish such concepts as political
protest, radicalism, political violence, and revolution. Description of
the empirical observations in Huntington's work, for example, obscures
the point by speculating that these phenomena unilinearly constitute a
continuum of "political instability." It was never explored whether
different dimensions of political violence may derive their respective
origins from different sources, depending upon the social, economic and
political environments and conditions in a political system.
Finally, the proportion of the explained variance (R2 value) is very
high when the model is evaluated against Political Restrictiveness,
which largely measures the structural characteristics of political control
and coercion imbedded therein. Such a result indirectly leads us to
recognize another shortcoming of the model which is largely due to the
misspecification2 or omission of significant causal influences. Note that,
except perhaps Voter Turnout,3 all the intervening variables are specified
in terms of either the "will" and "capacity" of elite to better perform
2Misspecification or specification error of a model refers to animproper delineation of the causal structure among a set of variables.For example, if variables that should have been included have been leftout or vice versa, the analysis leads to biased estimate of the parametersthat cause incorrect causal inferences.
3Voter Turnout may be construed as a performance variable whichprovides the people with a "choice" in selecting political leaders andinstitutions.
153
politically (i.e., Political Institutionalization and Government
Expenditure as a percentage of GNP), or the benefit rendered by govern
ment to help "the people in need of welfare" (i.e., Government Responsive
ness to welfare demands). This seems to point to a serious source of
the explanatory weakness and the incompleteness of the model we have
examined.
Socioeconomic change has typically affected the political system
through the increased political participation and the institutional
transformations. The one prompted the people to place demands upon
government and the other increased capacity of the government for a
"better political performance"--that is, sharing political power and
economic resources among them to the extent that they are sufficiently
equitable to be generally accepted. Our finding that Political
Institutionalization is a very powerful determinant of Political
Restrictiveness explains that high levels of institutionalization do
warrant the evolution of mechanisms for sharing political power and,
thus, constitute a powerful inhibitive factor for structural violence,
mainly initiated by the agents of elite strata of a political system.
If otherwise, the government more often than not imposes severe
mechanisms upon the system to restrict opposing groups' demands for
sharing the power or possible resort to extra-institutional demands,
which typically result in mass types of political violence. However,
our analysis indicates that this may be only a part of the while political
process, and the model is mute on the question of another half of political
performance, namely, the sharing of the economic resources within
political systems with an acceptable degree of equity.
154
The only variable specificated in the mode14 that can be construed
as the economic performance of a political system, except perhaps the
"will" and the "capacity" to perform better in distributing economic
resources, is Governmental Responsiveness, which is proposed by Deutsch
to index the welfare function of the government. However, our measure-
ment of the variable, which was operationa1ized in close parallel to
Deutsch's original formulation, constitutes largely a measure of
correcting past and present inequity or redistribution of income, of
which the political effect rarely reaches beyond the marginal sector of
the population.
It has been well known in history that the population of the most
destitute stratum in society is not the wellspring for violence and
revolutions. A high level of political consciousness or political
information, which is considered to be the prerequisite for radicalism,
is generally beyond the reach of the poorest stratum in a diverse
society. The big-city lumpenproletariat and industrial workers in modern
societies sometimes serve as a passive or even conservative political
force, but they are not more likely to be "the stuff out of which
revolution is made." Huntington, in apparent contradiction to his
theory, observes that:5
The true revolutionary class in most modernizing societiesis, of course, the middle class. Here is the principal sourceof urban opposition to government. It is this group whosepolitical attitudes and values dominate the politics of thecities. • The city is the center of opposition within the
4Refer to Figure 5-1.2, Chapter v.
5Huntington, Political Order, pp. 289-290.
155
country; the middle class is the focus of opposition withinthe city; the intelligentsia is the most active oppositionalgroup within the middle class; and the students are the mostcoherent and effective revolutionaries within the intelligentsia.
Yet, these important observations were not built into his theory. Instead,
he speculates that there may be an inverse correlation between political
instability and the rate of urbanization: 6
Rapid urbanization leads to social dislocation and politicalinstability in the cities. These, however, are minor socialand political ills compared to what would result in the countryside in the absence of such urbanization. Urban migration is,in some measure, a substitute for rural revolution. Hence,contrary to common belief, the susceptibility of a country torevolution may vary inversely with its rate of urbanization.(emphasis added)
The implication of the above statement is that political instability
--loosely defined to subsume such concepts as regime instability,
political violence, political radicalism, revolutionary movements--are
direct responses to large-scale structural changes. This leaves us
wondering whether Huntington actually attributes the cause of political
instability to structural changes (i.e., urbanization) rather than to
political institutionalization, or how he sees the locus of his postulated
intervening variables (political participation and institutionalization)
in such a relationship. In short, the net effect of such a confusion
leaves us with a lost sense of the political consequences of structural
changes which should have been incorporated into the structure of
political performance variables.
It is argued in the following sections that the substantive "out-
come" of political performance is not likely to be an automatic result
6Ibid., p. 229.
156
consequenced merely by an increased "capacity" and "will" of government.
At the same time, governmental responsiveness, mainly defined as a
welfare function, does not sufficiently meet the measurement criterion
of the substantive values. It is to be measured in terms of the con-
crete achievement of the substantive values (the "outcome") as well as,
but not limited to, institutional safeguards and procedures necessary to
achieve them.
2. The Logic of Political Performance: Perspectives of Rival Models
A. Functionalism vs. Power and Conflict Model
Functionalists assume that it is possible to achieve a balanced
allocation of power and resources between the elite and the mass within
the institutionalized framework of political process, if the system is
all~wed for "pluralistic" actors to cooperate, compete and bargain.
The "pluralistic" actors are, in turn, postulated as a concrete reality
in the political process,7 or, otherwise, an impending possibility in a
world-wide scale. 8 Sociologists Kingsley Davis and Wilbert Moore9 also
predict that political positions and social roles are distributed in
accordance with the principle of the functional importance or "indispen-
sability" to society at large, and that these roles are rewarded in
proportion to their relative contribution to the common good.
7Robert A. Dahl, Who Governs? (New Haven: Yale University Press,1961).
8Gabriel A. Almond and James S. Coleman, eds., The Politics of the
Developing Areas (Princeton: Princeton University Press, 1960).
9Davis and Moore, "Some Principles of Stratification," AmericanSociological Review, Vol. X, No. 2 (1945), reprinted i.n Melvin M. Tumin,ed., Readings on Social Stratification (Englewood Cliffs: Prentice-Hall,1970), pp. 368-377.
157
Such a judgment tends to reduce the problems of freedom and social
justice to a rhetoric of a competitive market principle,lO thus failing
to specify what constitutes an unacceptable degree of social inequality.
Instead, as we see in the liberal paradigm of the economic sciences,
equity considerations are put off until such problems disappear supposedly
when the societies get richer. ll The preferred political design offered
by the functionalist argument is to isolate political power from economic
power so that economic power does not necessarily yield political power.
It finds such a solution in holding periodic elections of leaders while
preserving the institutional safeguards for "pluralistic" democracy,
which allow for the formation of interest groups, widespread participation
by concerned publics, and representative institutions which conform to
democratic principles.
By examining the counter arguments offered by power and conflict
theorists, which were raised mainly in opposition to the functionalist
thesis, we can illuminate the value positions of an alternative model whose
blunt thesis is (1) that the democratic process, whatever it may mean, is
valuable only in so far as it leads to the maximization of the substantive
values, and (2) that institutional safeguards and procedural elements
of politics cannot substitute for such values.
lOrf. Ralf Dahrendorf, "Market and Plan," in Dahrendorf, Essays inthe Theory of Society (Stanford: Stanford University Press, 1968), pp.217-231.
llrhe argument goes on to prescribe that to eliminate the problemof economic inequality is to concentrate on economic growth without, forthe time being, worrying about the current distribution of economicresources. Implicit to this argument is the assumption that today'sinequality is justified in terms of its contribution to economic growth.
158
Two assumptions of the functionalist model that a harmony of
interests will develop over time in a pluralistic society, and that
distribution of social positions follow the principle of functional
indispensability for economic and political development underlie an
implicit theory of the rise of power of one over the other social
strata in modern industrial society. That is, the social and political
group "indispensable" for the major functions of the political and social
order is assumed to constitute the next ruling group. However, conflict
theorists argue, such an assumption ignores the nature of the political
process and the relations of political power to social stratification.
For example, if the relative contribution of one's social role to the
common goods of the society is all that matters politically, the
"indispensable" former slaves should have held positions of power, since
they were not less llindispensab1e" than were the officials and
aristocrats in the building of modern society. Contrary to Marx's
dialectical conflict theory, industrial workers have not risen to power
in any part of the contemporary world except, perhaps, for the Soviet
Union.
What is also missing in the functionalist's belief is that such a
prediction may truly happen only if the political process can be so
organized that it will ensure equal bargaining positions between
different segments of population or interest groups, a condition which
is rare in practice. Mancur Olson finds that small, resourceful, and
well-organized groups often defeat the wishes of numerically superior
but unorganized masses. 12 MOreover, some marginal groups are likely to
12Mancur Olson, The Logic of Collective Action: Public Goods andthe Theory of Groups (Cambridge: Harvard University Press, 1965),Chapters 1 and 2.
159
be completely or almost completely kept away from bargaining and negotia-
tion altogether by means of what Bachrach and Baratz call the "mobiliza
tion of the institutionalized bias.,,13 In a study of anti-poverty policy,
they found that the poorest groups found more institutional barriers
than other groups of Baltimore community in seeking negotiation and
bargaining and in having their demands heard into the political system.
Also, the poorest groups reportedly found it more difficult than others
to overcome the problem of what is referred to as "non-decision making."
Studies on the sociology of law also confirm that "the poor are
less likely than the rich to enjoy the benefits and protections accorded
by the law" in various aspects of civil justice. Jerome E. Carlin and
his associates report: 14
• • • that the poor no less than the rich have legal problems,that they are even more likely than the rich to suffer injustices resulting from the operation of our economic and governmental systems. • • • that many of these abuses experienced bythe poor arise from institutionalized practices, and that thesecollective problems are often unaffected by, if not exacerbatedby, traditional legal control.
Recent studies in economics similarly indicate that economic growth
does not guarantee an egalitarian distribution, and that much more
equality can be achieved before growth factors--incentive to work, to
13peter Bachrach and Morton S. Baratz, Power and Poverty:Theory and Practice (New York: Oxford University Press, 1970).
14Jerome E. Carlin, Jan Howard, and Sheldon L. Messinger, "CivilJustice and the Poor: Issues for Sociological Research," in Law andSociety Review, Vol. 1, No.1 (November, 1966), p. 85.
160
invest, etc.--wou1d be adversely affected. 15 In the U.S. case, Lester
Thurow reports that:
Both high progressive at the top and a negative income tax atthe bottom seem compatible with economic growth. The presentdegree of inequality cannot be justified as functionallynecessary to promote economic growth. Substantial equalizationcould occur before growth would be adversely affected. 16
Turning. our attention to the international perspective, quantitative
data as well as analytical arguments are frequently offered as reasons to
fear that there would be a widening gap between the governing elites
and the masses, leading the world into an increasing degree of "ungovern
ability,,17 and violence. Social inequality tends to be further promoted
by the new sources of political power generated during the process of
modernization. In particular, governments in the Third World are
increasingly controlled by the modern sector, which furthers its
interests by foreign exchange controls, high tariffs, and so forth.
The imported life style of a minority, often oppressing egalitarian
forces by means of brutal physical forces or external security reasons,
leads the government to rely increasingly on non-participatory and
authoritarian means of political control so as to overcome mounting
15Herbert J. Gans, More Equality (New York: Pantheon Books, 1973);Arthur M. Okun, Equality and Efficiency (Washington, D.C.: The BrookingsInstitution, 1975).
l6Lester Thurow, "Toward a Definition of Economic Justice,"The Public Interest, No. 31 (Spring, 1973), pp. 76-77.
17K• W. Deutsch, "On Inequality and Limited Growth," InternationalStudies Quarterly, Vol. 19, No.4 (December, 1975).
161
internal tensions. In the end, as we see in Asia and Latin American
political systems, a number of such regimes have been overthrown by
military uprisings, and the elite strata have become "increasingly
inclined to seek shelter behind regimes of armed force."lS
Power and conflict theorists contend that deficiencies of the
functionalist arguments can only be overcome by developing a more open
model of political performance, based on a more realistic understanding
of the relationship between the political process and social equality.
We will attempt to derive several prepositions from the power and con-
flict model, after a close examination of the logic behind it, mainly
in reference to the problem of social equality.
B. Politics and Social Equality: Perspectives from Conflict Paradigm
A fundamental argument of the conflict roodel is that the distribution
of income and wealth can be directly manipulated by political inter
vention. 19 Therefore, it is assumed that the nature of a distributive
system in a polity is largely a function of power. The problem of how
one prescribes the role of political power in achieving a "just"
distribution further divides the conflict model into two different types
of political theory. The socialist model or what may be called a "purist
model of conflict paradigm" sees that the only way to achieve a "just"
lSunited Nations, 1967 Report on the World Social Situation (NewYork: United Nations), p. 50.
19To what extent the distributive mechanism is in fact manipulatablein different settings is open to question. This consideration, however,is not as important for conflict theorists as it is the fact that it isat least potentially subject to direct political manipulation.
162
order is to reconstruct the social composition of political power from
the beginning so that the majority (or the mass) has a complete control
over the power, and that the power is never to be distributed unequally.
Marx's original formulation and the political ideals pursued in early
Soviet Russia and contemporary China claim to best approximate this type.
Summarizing the main arguments of the pure conflict model as they
are related to the study of violence and revolution, the model predicts
that:
(1) The political institutions and administrative agencies based on
the unequal distribution of power or controlled by a small minority of
the power elite tend to become increasingly closed to mass demands.
(2) Institutionalized decision-making under such system tends to be
disproportionally responsive to the needs and interests of the elite
structure at a corresponding cost to the needs and interests of the
masses.
(3) The course of the political process under such conditions tends to
create a disposition for future political processes to reinforce the
existing social inequality in favor of the dominant political structure
and the social class.
(4) The dominant class will seldom give up voluntarily even a relatively
small quantity of their resources in order to achieve a collective aim.
(5) In addition, political and economic activities which generate
external benefits in the political systems will tend to neglect the
subordinate groups, and any cost caused by external sources will adversely
affect the underprivileged population.
163
(6) This will lead the subordinate class, voluntarily or by external
inducements, to ultimately form a coherent organization, policies and
objectives, and to wage an organized revolution against the dominant
class.
(7) A "just" distribution of political power and resources is possible
and an impending reality in human history.
The other version of the conflict paradigm, which will be referred
to hereafter as Eower analysis, focuses more on the human uses made of
the unequal distribution of political power. It shares the fundamental
assumptions of the conflict paradigm in that the political process is
seen as basically a tension-inducing mechanism and that conflict, not
consensus, is the nature of the political process. However, unlike
the purists, power analysts posit that an existence of the unequal
distribution of power is a less significant area of study than the
political uses made of such power. Therefore, the argument is often
reduced, instead of calling for a radical redistribution of power,
whether the use of political power is justifiable in terms of its
consequence, namely, the "common good" for which the political power is
instrumental. 20
20It seems that, broadly speaking, the following authors and worksbelong to this school.
C. Wright Mills, The Power Elite (New York: Oxford UniversityPress, 1956); Harold Lasswell, Politics: Who Gets What, When, and How?(Cleveland: World Publishing Co., 1958); Dahrendorf, Class and ClassConflict in Industrial Society,.2£.' cit.; Christian Bay, The Structureof Freedom (Stanford: Stanford University Press, 1965); Olson, ££. cit.;Gerhard Lenski, Power and Privilege: A Theory of Social Stratification(New York: McGraw-Hill, 1966); Irving Louis Horowitz, Three Worlds ofDevelopment: The Theory and Practice of International Stratification(New York: Oxford University Press, 1966); Gunnar Myrdal, Asian Drama:An Inquiry into the Poverty of Nations (New York: Pantheon Books, 1968);Bachrach and Baratz, EE.. cit.
164
It is the latter school of thought from which we can derive several
propositions so that the sources of error of the model which we examined
in the preceding chapter can be detected and the analysis can be more
exhaustive. Power analysts posu1ate that politics, insofar as it con-
sists of a struggle for power and resources among diverse groups and
interests, involves the processes of conflict and bargaining. They
further recognize that diverse participants in the political process
are unequal in their command over resources and bargaining positions21
and that therefore, if left unintervened by politics, the society will
become increasingly unequal. However, the perspective of power analysis
is significantly different from that of the pure conflict model in the
following several respects.
Contrary to the purist model, the power analysts share the function-
alist believe that, by means of institutional arrangements that formalize
the "rules of the game," the disposition of increasing social inequality
under the conditions of natural political processes can be made reversible.
However, they depart from the functionalist model in that the
content of the "rules of the: game" goes much beyond the provision of the
"market princip1e.,,22 It is argued that the content of the "rules of the
21For example, Bachrach notes, "the dominant political ideology,established channels and modes of access to decision-makers, andtraditional procedures and rules may operate to exclude certain groups-even large segments of its popu1ation--from participating in the systemor benefiting from it." Peter Bachrach, "A Power Analysis: The Shapingof Antipoverty Policy in Baltimore," in Public Policy, Vol. 8, No.2(Winter, 1970), p. 155.
22Consider Lasswell's definition of politics as the process bywhich values are "allocated" (or reallocated) in an "authoritative" mannerthat is "legitimate" in the sense of fitting the beliefs of the parties whomay be "in conflict" with one another in their interactions.
165
game" should be applied equally to both the dominant and the subordinate
groups, and the substantive content of the rule should be continuously
modified so that the unequal bargaining positions of the subordinate
groups can be improved or, at least, not be adversely affected by the
course of political processes. In addition, power analysis sharply
distinguishes "promise" from "performance" and does not consider that
the former necessarily may bring about the latter. Instead, it says
that "promise" can be equally betrayed as it can be kept, and therefore
the criteria of "authoritativeness" and "legitimacy" cannot be dependent
solely upon "promise" without a due consideration of concrete "outcomes."
Applying the arguments offered by this perspective to our problem,
such concepts as political institutionalization and governmental capacity
as the primary measures of political performance mislead us by assuming
that the "will" and "capacity" of government automatically ensure the
promotion of an acceptable "collective goods" equally beneficial for
every member of a political system. The arguments further signify (1)
that the study of "will" and "capacity" is only a beginning step in
analyzing political performance, and (2) that the essence of political
performance should be the concrete achievement of government measured
by the provision of "collective goods."
The term "collective good" is synonymously used by Olson with the
"common good," "public good," and the benefits accrued from public
policies and institutions which are equally beneficial to all members of
a society.23 For the purpose of our study, however, we define the
230lson, ~. cit., pp. 14-16.
166
"collective good" mainly in terms of three concepts and related indica
tors purported to measure them. The first provision of collective good
is defined as social welfare, which we have already operationalized by
Governmental Responsiveness, following Deutsch's suggestion. The second
component of the collective good is defined as the extent of "choice"
made available to non-elite members of a political system to select
their leaders and to monitor political institutions so that the "promise"
is less easily subjected to a betrayal. It will be, in turn, indicated
by our analyzed variable of Voter Turnout. The last measure of the
collective good constitutes the concept of social equality. We will
operationa1ize and analyze the relationship of social equality and
political violence in subsequent chapters, after we revise the model
specified in Chapter V by means of introducing a series of hypotheses
derived from the conflict and power analysis.
3. Social Inequality and Political Violence: Empirical Hypotheses
Recapitulating our discussion so far, we have identified and
reduced the error of misspecification of intervening variables in regard
to political performance in the model we tested in Chapter V by
clarifying the value judgments, assumptions and perspectives which lie
behind each of the rival models of political process. We now turn to
formulate several research propositions.
How can the logic of political process and political actions, as
conceptualized by power analysis help us to improve the study of political
violence? The answer to the question may be pursued by evaluating the
empirical validity of the major predictions made available to us by the
model.
167
Power analysis predicts that if the "rules of the game" prescribed
in formal institutional procedures of conflict-resolution fail to
"allocate" (or reallocate) the "collective goods" properly in such a
way to convince rival political actors that they are "authoritative"
and "legitimate" outcomes, subordinate groups' political actions seeking
to bring substantial changes in the distribution of values will tend to
be increasingly tension-inducing and conflict-oriented. If subsequent
political decisions and institutionalized performance mechanisms fail to
resolve these conflicts non-violently, the system is likely to suffer
from more overt types of political actions, namely, political violence.
Although the above statement does not distinguish mass violence
from elite-initiated coercion and assumes the two types are interactive,
it may be inferred, in so far as our purpose is concerned, that "overt
types of political action" primarily refer to non-elite reactions against
institutionalized agents of the dominant groups. Nevertheless, it is
our task to see whether the revised model in fact significantly improve
our ability to account for mass political violence, while not substantially
altering our findings in Part II in regard to elite-initiated political
violence. Of course, we should also note that the scope and extent of
non-elite reactions to the institutional structure of a political system
are not limited to overt political violence. They may range from a
simple withdrawal and retreat to one's perceived fate out of alienation,
to petty crimes and uncoordinated violent actions of individuals, to
non-violent competition among non-elite for elite positions, as well as
to collective violence directed against members of the elite or their
agents, or even to an all-out social revolutionary movement. The limited
168
scope of our inquiry, however, excludes behavior which merely annoys
elites but poses no serious politically salient threat to their power
or wealth.
Non-elite reactions to the institutionalized structures of a
political system may depend upon several conditions in a political
system. The first condition is the extent to which a political system
has successfully adjusted to improve the conditions and bargaining
positions of non-elite groups by means of promoting "collective goods."
Apart from the general social welfare aspect of governmental performance
and the extent of "choice" provided to non-elite groups in the form of
political participation, we will operationa1ize the concept of social
equality to measure a full range of "collective goods."
The second condition is related to the extent to which rival groups
and the population at large are politicized by active campaigns for
egalitarian movements. Precise measurement of egalitarian political
campaign is very difficult. The problem of measuring active political
movements for an egalitarian social goal is also compounded by the fact,
as discussed before, that radical political actors and their leaders
are usually not the most destitute but are more likely to be members of
~he middle class or intellectuals in terms of their relative social
positions. It may be argued, therefore, th~t a salient proxy variable
for egalitarian political socialization is th~ size and strength of the
socialist party movements whose ideology is explicitly committed to the
egalitarian social movements. 24
24Lenski also suggests that labor unions as well as socialist partymovements have contributed to achieving more egalitarian societies. For
169
It may also be argued that the extent of social inequality and the
strength of egalitarian political movements would have a multiplicative
effect on political violence. Historically, it has been the emergence
of socialist political movements that has enabled issues regarding
inequality to gain support through more overt and violent political
movements. Theoretically, this suggests that the conjunction of the
higher extent of inequality with a more widespread ideological conscious-
ness for egalitarian social goals would produce a multiplicative impact
on mass political violence, beyond the additive effects of the two
"main" variables.
Finally, it seems that the explanation of international politics
by such a tool of power analysis may also be possible in a metaphorical
sense. The conflict paradigm in general and power analysis in particular
predict that political and economic activities which generate external
benefits in the political system tend to neglect subordinate groups.
On the other hand, any cost from external sources is postulated to be
adversely affecting the underprivileged population. This suggests, for
example, that the accumulation of income and wealth derived from foreign
trade, aid, and profits of multinational corporations are more likely to
be beneficial to the central business sector, the governmental elite,
those who are in professional or intellectual occupations, the central
cities, etc., than they are to the agricultural and so-called peripheral
sectors, the masses, those who are engaged in menial jobs, the rural
example, he argues that differences in the strength of the unions andthe socialist party in Sweden and the United States may consitute one ofthe main causes of more social equality in the former than in the UnitedStates. (See Lenski, .2.l?. cit., pp. 319-322.) However, due to the unavailability of current union data, we are not in a position to evaluatethis argument.
170
communities, and so on. The argument can be equally applied to an
international perspe~cive. That is, the subordinate countries in the
international system will pay higher costs but draw less benefits from
the existing arrangements of international system than the dominant
powers.
Based upon such a postulation, authors such as Myrdal, Galtung,
and Frank25 theorize that international systemic constraints, namely,
dependency, affects inversely on social equality and this, in turn, tends
to produce higher level of political violence. Such a prediction forces
us to reexamine the assumption we followed so far with regard to the
nature of our unit of analysis; that is, sovereign states develop,
behave and perform autonomously and are independent of international
influence. Evaluation of the above proposition also requires us to
establish a developmental causal link of dependency (independent variable)
~ political performance (intervening variable) ~ political violence
against the pOSSibility of a non-spurious contribution of dependency on
measures of political violence. For these reasons and others, the
dependency thesis deserves a separate treatment in a later chapter. We
now will state various research hypotheses derived from our conceptual
explication in accordance with the power analysis.
Translating the model into researchable propositions, we derive
the following two main propositions, whose related hypotheses can be
subjected to a systematic empirical evaluation:
25See Gunnar Myrdal, Economic Theory and Under-Developed Regions(London: Gerald Duckworth & Co., 1957); Johan Galtung, "A StructuralTheory of Imperialism," Journal of Peace Research, Vol. 7, No.2 (1971),pp. 81-118; James D. Cockcroft, Andre Gunder Frank and Dale L. Johnson,Dependence and Underdevelopment: Latin America's Political Economy (NewYork: Anchor Books, 1972), Part I.
171
Main Proposition 1
The extent of structural coercion and, particularly, of masspolitical violence in a political system is a function of the followingconditions:
(i) the degree to which a political system has been successful inreducing the level of political tensions arising out of the misuse ormis-allocation of the collective goods. Since the most conspicuous "outcome" of the misuse and mis-allocation of the collective goods is,according to both the pure conflict theorists and power analysts, anincreasing social inequality, this condition will be operationa1ized interms of the extent of observed social inegua1ity within politicalsystems.
(ii) the extent to which the ideology of egalitarianism is pervasiveamong rival political groups and the population. The strength of thesocialist party movements is our measure of this concept.
(iii) the extent to which the above two conditions are co-existent inthe form of a multiplicative interaction effect.
This proposition enables us to test the following hypotheses so
that our analysis in Part II can be finally integrated into a coherent
model.
Research Proposition 1-1
Controlling for the effects of the intervening variables for eachdimension of political vio1ence26 (Part II, Chapter V), mass politicalviolence (Protest and Internal War) is more likely to be correlatedsignificantly than elite violence (Provoked Repression and PoliticalRestrictiveness) with:
26Note that the performance (intervening) variables to be controlledare respectively, Voter Turnout for Protest, Voter Turnout and GovernmentResponsiveness Index for Internal War, Political InstitutionalizationIndex for Political Restrictiveness, and none for Provoked Repression.(See Chapter V.)
Note also that hypotheses 1-1.1 to 1-1.4 are formulated to fit forpartial correlational analyses. This is justified on the ground that thetheory we adopted in Part II and the subsequent inquiry following arevised model provide no curvilinear arguments on the relationshipsbetween the performance (intervening) variables and the dependent variables.Scatter diagram analyses conducted by the present researcher on therelationship between equality variables and the violence indicators alsofailed to support any particular inductive argument in favor of thecurvilinear argument systematically. These scattergrams are not reportedin this research because they are too lengthy.
(i)(ii)
(iii)
the extent of social inequality;the strength of the socialist party movements, and;the multiplicative function of the above two terms.
172
Hypothesis 1-1.1
Controlling for the effect of Voter Turnout, there will stillbe significant positive correlations between the level of Protest and:
(i)(ii)
(iii)
the extent of social inequality;the strength of the socialist party movements; andthe multiplicative function of the above two terms.
Hypothesis 1-1.2
Controlling for the effects of both Voter Turnout and GovernmentRespons~.veness, there will be significant positive correlations betweenthe InLernal War and the above (i),(ii), and (iii).
Hypothesis 1-1.3
The correlations between Provoked Repression and the above (i),(ii), and (iii) are not likely to be significant statistically.
Hypothesis 1-1.4
Controlling for Political Institutionalization, correlationsbetween Political Restrictiveness and the above (i),(ii), and (iii)are not likely to be significant.
Research Proposition 1-2
The "will" and "capacity" variables for political performance arenot likely to be stronger predictors for indicators of mass politicalviolence than the above (i),(ii), and (iii), while they tend to remainas stronger predictors for elite-initiated political violence than (i),(ii), or (iii).27
27Note that hypotheses 1-2.1 to 1-2.4 are formulated to fit amultiple regression analysis. This is to test the additional argumentof the power and conflict model that, for the mass political violence,the "will" and the "capacity" variables are less salient performanceindicators than the actual "outcome" indices of political performance.
173
Hypothesis 1-2.1
Voter Turnout is less likely to be a strong predictor to Protestthan (i), (ii), or (iii).
Hypothesis 1-2.2
Both Voter Turnout and Government Responsiveness are less likelyto predict to Internal War than (i), (ii), or (iii).
Hypothesis 1-2.3
Provoked Repression is not likely to be explained by either of(i), (ii), or (iii).
Hypothesis 1-2.4
Even when jointly analyzed with the above (i), (ii) and (iii),the Political Institutionalization index is likely to remain as thestrongest predictor to Political Restrictiveness.
Main Proposition 2
A country's political performance is negatively related with theeffects of international systemic constraints, which is defined as itslocation in the structure of the international division of labor, powerand status; and this, in turn, is likely to cause higher level ofpolitical violence.
The concept of dependency is our major analytical tool in evaluating
this prediction. This general proposition is operationa1ized as the
following two research propositions. The Research Proposition 2-1 below
is to be tested by a series of bivariate hypotheses which link the
independent variable (dependency) to intervening (political performance)
and dependent (political violence) variables, respectively. Research
Proposition 2-2 is to test the possibility of spurious relationship
postulated in Hypothesis 2-1.2. Such a test will complete the causal
structure among the three sets of variables--namely, independent,
intervening and dependent variables.
174
Research Proposition 2-1
The higher the effects of dependency on the political performanceof a country, the higher the level of domestic social inequality in thecountry and, thus, the higher the level of political violence.
Hypothesis 2-1.1
The higher the dependency of a political system, the higher thelevel of domestic social inequality.
~pothesis 2-1.2
The higher the dependency, the higher the level of politicalviolence.
Research Proposition 2-2
The effect of dependency on political violence (dependent variables)is likely to be primarily indirect through its adverse impact on politicalperformance (intervening variables). That is, controlling for directeffects of the variables measuring the collective goods or the egalitarian political campaign on political violence, the relationship observedin the above Hypothesis 2-1.2 is likely to be spurious.
Formulation of concrete hypotheses for Research Proposition 2-2
will be put off until we test the ones preceding it. In the following
chapter, we will evaluate various hypotheses derived from the Main
Proposition 1. Chapter VIII will be devoted to examining the hypotheses
followed by the Main Proposition 2.
CHAPTER VII
SOCIAL INEQUALITY AND POLITICAL VIOLENCE:
AN EMPIRICAL RESEARCH
1. A Note on the Problem of Data
Comparing social inequality across countries presents a familiar
dilenuna in social research. The concept of equality involves unavoid-
able differences of opinion attached to its meaning and measurements.
Reliable quantitative data are lacking for most countries. In addition,
the various forms of social inequality cannot be reduced to a single
conunon denominator, thus, no single measure can fully express the extent
of inequality in political systems.
The limitations of data, especially in regard to personal income
distribution, poses a vexing problem of a particular sort. l First of all,
the income concept used by individual countries falls far short of the
comprehensive definition, and measurement of income distribution is sub-
jected to various error of non-scientific sources, even when the concept
is properly defined. For example, the highest income fraction of the
population is likely to under-report its income deliberately for
lFor some further highlights on difficulties of measurements andcomparisons of income distribution, see Simon Kuznets, .9£.. cit., pp.10-12; Montek S. Ahluwalia, "Income Inequality: Some Dimensions ofthe Problem"; Chenery, et a1., .9£.. cit., pp. 4-6; Elias Gannage, "TheDistribution of Income in Underdeveloped Countries," in Jean Marchal andBernard Ducros, eds., The Distribution of National Income: Proceedingsof a Conference held by International Economic Association (New York:St. Martin's Press, 1968), pp. 344-345.
176
political or tax considerations. A comparison of rural and urban income
is difficult due to wide variation in prices for different consumer
groups. Many farm products--fuel, food, etc.--especially in less developed
countries, are not monetized and, thus, are not included in rural income
figures. For these reasons, the income levels of the rural sector are
typically underestimated. Secondly, since income distribution data are
often derived from sample surveys, the estimation procedure from the
sample for total population does not always solve the problems of ac
curacy, representativeness, and other sources of error, such as inadequate
sample designs or implementation. Thirdly, the degree of reliability
and validity of the income data is not unrelated to the level of general
socioeconomic development. Thus, data on income distribution in under
developed countries are, "at best, approximations of the underlying
distribution we wish to measure.,,2 Lastly, estimations of income: data
are typically based on noncomparable data sources, making inter-country
comparisons and even inter-temporal comparisons for the same country
very difficult. Therefore, we are cautioned that the available data
are not satisfactorily presented as reliable or even "best" estimates.
These problems often produce an extreme response on the part of the
comparative analysts, who reject any use of the available data for a
rigorous analytical purpose. Nevertheless, it is believed that the
differences in social inequality in the area of land ownership, personal
income and occupation structure are so great among different systems
that it is possible to make even rough but still meaningful comparisons.
2Ahluwalia, .£2.. cit., p. 5.
177
At the same time, we assume that a cautious use of existing data will
yield important insights and perspective on the nature of social
inequality and its relationship to political violence. For these
reasons and others, various supplementary indicators will be operation
alized, if the data are available. To keep any systematic source of
errors from being compounded in constructing composite indices, the
indicators will be analyzed separately.
2. Measurement of Variables
In order to test our hypotheses, we have selected three types of
social inequality. They are (1) inequality of income among different
occupational activities across political systems, (2) inequality of
wealth and property ownership, indexed by land ownership and distribution,
and (3) inequality in the distribution of personal income. Relevant
indicators for the three types of social inequality are operationalized
and explained below.
A. Sectoral Disparity in Income Distribution
To measure income disparity between different occupational sectors,
the following two variables are used:
1. Per capita income in the agricultural sector as a percentage of
per capita GNP in the rest of economy (per capita Agricultural Income
as % of Others). The agricultural income is defined as the amount of
GNP per capita derived from agricultural sources, including forestry
and fishing. The income data comprise an average of the three years
nearest to 1960, and the population statistics used to calculate this
178
variable are the number of economically active (male and female)
persons. 3
2. Gini index of sectoral income distribution (Gini: Sectoral In-
equality). The Gini index is one of the most commonly accepted measures
of inequality. It is defined as the proportion of the geometric area
which falls above a Lorenz curve on which the percentage of total
aggregate income is arrayed along the vertical axis in order from the
lowest income units (i.e., agricultural sector) to the highest (i.e.,
manufacturing sector), with various units are arrayed along the horizon-
tal axis. Perfect equality would result in points along the 45° line; if
one sector had all the income, the bottom and right straight lines would
result (Gini index = 1). Actual curves fall in between, and the closer
to the diagonal, the less the inequality; the larger the area between
the 45° line and the line of the actual distribution, the higher the
Gini index and, thus, the moreunequal the distribution of income among
different sectors of national economy.4
The following eight categories are used as basis for measuring the
Gini index of income inequality across occupational sectors:
3A few countries' income data of which GNP were not available weresubstituted by GDP. Referent population statistics for severalcountries are not exactly corresponding to the years of income data dueto the unavailability of the population data. A detailed footnote onthis variable is referred to the source. Source: U.N., Department ofEconomic and Social Affairs, Social Policy and the Distribution of Incomein the Nations (New York: United Nations, 1969), pp. 134-135.
4This can be explained as the following chart and formula: reproduced from James Morgan, "The Anatomy of Income Distribution," The Reviewof Economics and Statistics, Vol. XLIV, No.3 (Aug., 1962), p. 281:
179
(a) Agricultural, forestry, hunting, and fishing
(b) Mining and quarrying
(c) Manufacturing
(d) Construction
(e) Electricity, gas, water, and sanitary services
(f) Commerce, including banking, insurance, and real estate
(g) Transportation, storage, and communication
(h) Public and private services
The data are selected from the years 1960 to 1965. When it was
impossible to obtain data for all sectors separately, two or more
sectors were lumped together. 5
B. Inequality in Land Distribution
In order to measure inequality in wealth and associated property,
data for the following two variables are collected:
=
G=(% of income)y .-----------------::-rareq. between curve and diagonal
area under diagonal
0.5 - area under curvearea under diagonal
= 1 - (area under curve x 2), or
G = 1 - E(B - A x c; D ) 2
= 1 - E(B - A) (C + D)
A B (units ofincomesector
5See pp. 211-214 and 263-265 of Handbook (1972) for detailedproblems and footnotes of this variable. Data for the following countriesare drawn f:a:om Jackman's report: Colombia, Barbados, New Zealand, Ceylon, Taiwan, Morocco. Sources: Handbook, and Jackman, ~. cit., p. 210.
180
1. Number of holdings owned by the holder or in owner1ike possessionas percentage of total number of holdings (Equality in LandOwnership)
"Holdings owned" is defined as individual units of land "over which
the holder possesses title of ownership and consequently the right to
determine the nature and extent of its use, as well as the right of
transfer," "Owner1ike possession" includes land (a) "operated under
perpetual lease, hereditary tenure, and under long-term lease usually
ranging from 30 to 99 years, and the rent of which is sometimes only
nominal;" (b) "which, without legal title of ownership nor of a long-
term lease, has been peacefully and uninterruptedly operated by the
holder for a period of over 30 years without payment of rent;" and (c)
property held in an arrangement "under which a villager receives
possession of a plot, rent free, from ejidal or other communal land
and retains it as long as he keeps it under cultivation by his own
labor and that of his family and under which he cannot sell or mortgage
his ho1ding.,,6 The data for the variable pertain to 1960 for most
countries.
2. Gini index of land distribution (Gini: Land Holding Inequality)
Data for the following countries were taken from Russett, et a1.,
World Handbook of Political and Social lndicators: 1964; France (1948),
Switzerland (1939), Greece (1930), Canada (1931), Bo1iva (1950), Chile
6F•A.0. and I.L.O., Progress in Land Reform (New York: UnitedNations, 1970), p. 329. Data for the following countries were calculated from Russett, et a1.,Haridbook (1964): Denmark (1949), Finland(1950), Sweden (1944), Switzerland (1944), Greece (1944), Argentina(1952), Bolivia (1950), E1 Salvador (1950), Puerto Rico (1959), India(1931), Iraq (1958), Israel (1950), Jordan (1953), Libya (1960). Datafor remaining countries are drawn from Progress in Land Reform.
181
(1936). Others are drawn from Taylor and Hudson's data set reported
in the Handbook: 1972. Data are generally for 1960.
C. Inequality in the Distribution of Personal Income
In general, I have attempted to collect all available estimates
of income shares accruing to the 20 income groups ranging from the
poorest 5 percent to the richest 5 percent, as well as the Gini index
which comprises a single summary measure of overall inequality in
income distribution. Technically, however, separate analyses for all 20
income groups are theoretically not very meaningful. On the other hand,
the Gini index tends to be over influenced by the in-between income
groups at the two extremes7 and, therefore, is less sensitive to the
relative shares of the poorest and the richest groups. To overcome
these problems, I disaggregated distribution of income data into three
groups and into one summary Gini index.
The primary source of data is a compilation from various national
and international sources which was prepared as a staff report of the
IBRD. 8 Individual sources for country data used in the report are
indicated in the Appendix 3. The indicators used in the analyses are
reported below.
7For a useful reference of the different meanings and associationsbetween alternative indicators of income inequality, see, Hayward R.Alker, Jr., Bruce M. Russett, "Indices for Comparing Inequality," inRichard L. Merritt and Stein Rokkan, eds., Comparing Nations: The Useof Quantitative Data in Cross-National Research (New Haven: YaleUniversity Press, 1966), pp. 349-372.
8prepared by Shail Jain, "Size Distribution of Income: Compilationof Data," Staff Working Paper, No. 190 (November, 1974), InternationalBank for Reconstruction and Development.
182
1. Amount of national income shared by the poorest 40 percent ofthe population group as a percentage of total national income(Income Equality: Poorest 40% Share)
2. Amount of national income shared by middle 40 percent (41-80%)population group as a percentage of total national income(Income Equality: M1dd1e 40% Share)
3. Amount of national income shared by the richest 5% (96-100%)of the population group as a percentage of total national income(Income Inequality: Top 5% Share)
4. Gini index of size distribution of income calculated on thebasis of 20 income groups (Gin.i: Personal Income Inequality)
D. Strength of the Egalitarian Political Campaign
In order to construct a single index of the concept, the following
operational procedure is adopted after raw data are compiled for two
indicators:
1. The estimated membership size of Communist Party membership aroundthe year 1965.
The data originally estimated by u.S. Department of State and
reported by Benjamin and Kautsky,9 were transformed into the following
scale:
"1" 0 5,000
"2" 5,001 10,000
"3" 10,000 20,000
"4" 20,000 50,000
"5" 50,000 and above
9World Strength of the Communist Party Organizations (Washington,D.C.: Bureau of Intelligence and Research, 1965). The data are adoptedfrom Roger W. Benjamin and John H. Kautsky, "Communism and EconomicDevelopment," in American Political Science Review, Vol. LXII, No.1(March, 1968), pp. 110-123. The following countries'data are estimatedon the basis of DON, No. 65: Afghanistan, South Korea, Taiwan, andThailand.
183
2. Membership of the Communist Party as a percentage of workingagelO population.
The data, drawn from the Benjamin and Kautsky report, were
transformed into the following scale:
"1"
"2"
"3"
"4"
o %
0.01
0.05
0.20
0.049%
0.19%
0.99%
"5" 1. 00 or more %11
3. Strength of the egalitarian political campaign (Egalitarianism)
The final index of Egalitarianism was derived by averaging the
two indicators for each country.12 This procedure is justified on the
ground that the index should take into account the proportion of
population involved, as well as the absolute size of the party member-
ship.
10Working-age is defined as age 15-64. The figures for workingage population were reportedly obtained from United Nations StatisticalYearbook (New York: United Nations, 1963). See Benjamin and Kautsky,,2£.. cit.
llHighest was 4.19% for Italy.
l2Index for 15 countries in which data for the percentage membership of the working-age population is unavailable are based on onlythe membership size. By this way, index for 70 countries is securedfor the analysis. The correlation between the two indicators amountsto 0.66, with 56 countries of available data for both indicators.The final index explained over 80% of variances for both of theoriginal indicators.
184
E. Interaction Effects of Inequality and the Extent of EgalitarianPolitical Campaign
The multiplicative effect variables between the extent of observed
social inequality and the level of political egalitarianism are oper-
ationa1ized as the following:
(a) Interaction Effects of Sectoral Inequality and PoliticalEgalitarianism
1. Disparity of agricultural vs. the rema~n~ng sector interactingwith political egalitarianism (Inequality of Agriculture-Othersx Egalitarianism)
In operationa1izing this variable, values of per capita Agricultural
Income as % of Others is first reversed so that countries are arrayed
f th 1 t h h · h . th d . . 1 13rom e owest 0 t e ~g est scores ~n e ~spar~ty sca e.
then multiplied by the Egalitarianism index defined above.
It is
2. Sectoral inequality interaction with political egalitarianism(Sectoral Inequality x Egalitarianism)
This variable is derived by a straightforward multiplication of
the Gini index of sectoral inequality and Egalitarianism.
(b) Interaction Effects of Inequality in Land Distribution andPolitical Egalitarianism
1. Ownership inequality interacting with political egalitarianism(Ownership Inequality X Egalitarianism)
Equality in Land Ownership is first reversed by means of a formula,
(100 - Equality in Land Ownership) so that the low score will indicate
high equality and the high score high inequality. It is then multiplied
by the Egalitarianism index.
13Technica11y, it is transformed by the formula: (125 - per capitaAgricultural Income as % of Others). 125 is adopted in consideration ofthe highest value of the original variable which was 123% in the case ofAustralia.
185
2. Land holding inequality interacting with politicalegalitarianism (Holding Inequality X Egalitarianism)
The Gini index of land holding inequality is multiplied by the
Egalitarianism index to derive this variable.
(c) Interaction Effects of Inequality in Size Distribution of Incomewith Political Egalitarianism
1. Income inequality for the poorest 40% of the populationinteracting with political egalitarianism (Inequality-Poorest40% X Egalitarianism)
The values for the share of the poorest 40 percent income group
defined above is reversed by the formula, (100 - Income Equality:
Poorest 40% Share) so that the resulting values will vary from most
unequal to the least. It is then multiplied by the Egalitarianism
index.
2. Income inequality for the middle 40% of the populationinteracting with political egalitarianism (Inequality Middle 40% X Egalitarianism)
The same operationalization as for the poorest 40% share is con-
ducted to derive this variable (100 - Income Equality: Middle 40%
Share X Egalitarianism index).
3. Income inequality for the richest 5% of the populationinteracting with political egalitarianism (Inequality - Top5% X Egalitarianism)
This variable is a straightforward multiplication of the Income
Inequality: Top 5% Share and the Egalitarianism index.
4. Gini index of size distribution of income interacting withpolitical egalitarianism (Gini-Personal Income Distribution XEgalitarianism)
This variable is derived from multiplying the Gini index by the
Egalitarianism index.
186
3. Empirical Evaluation of the Hypotheses
A. Testing Research Proposition 1-1
To test the series of hypotheses generated from the Research
Proposition 1-1, partial correlations are produced between each of the
political violence indicators and the social inequality (or equality)
variables. The results are reported in Table 7-1.
The table indicates that inter-sectoral inequality (Gini: Sectoral
Inequality) is associated with less protest activities, while the higher
proportion of income shared by the middle 40% of the population group
tends to result in higher level of such activities. The Protest is also
rather highly associate~ °ith the level of political egalitarianism
and many of the interaction variables. The substantive interpretation
of the table is that, controlling for Voter Turnout, Protest tends to
be a function of: (1) higher levels of income equality rather than
inequality; (2) higher levels of political campaigns toward more
egalitarian social goals; and, (3) the interaction effects of the above
two conditions.
The pattern of association between the equality variables and
Internal War is not the same as in the case of Protest. Internal War
is positively associated with the sectoral disparity between agriculture
and other sectors, monopoly of land ownership by smaller portion of the
population, and the overall inequality in the distribution of personal
income. The significant and consistent directions of other remaining
partials render additional support to conclude tentatively that,
controlling for Voter Turnout and Government Responsiveness to mass
welfare needs, Internal War is most likely in polities in which (1)
187
table 7-1 Partial Correlations Between Pol1t.lcal Violence and ~oclal'Inequallt.:y. Egall~IDd Hul.~lpl1cl,tlon E:ffects ' ,
,Zero-o:l!.erCorrelation
Controlled for,. Cove=eont. PoliticalResponsiveness Instltutlon-" V,t.er allzatlonTur.1.out
VoterTuxnout.
H.l-l.l
Protest
I\. YaJ:1ables to be •
" ."" eontrolled for.
"\.Hypothesis No.
Variables entered forPari.1aJ.1JI&'
•Concepts of
Social
Inequa11t:y H. 1-1.2 H. 1-1.4 I H. '1-1.3
I Pro'/o~cd iInt..u:nal liar Political I Rep::-e'sslon I
Restrlctive- i~ +- +-__...:.,-- ..:;n~es~s:.-__+- ,· ' ,SectoraJ. Disparity per capita Asrtcultuxal -.09 ".35 -.10 -.1~ I
in Incoce InCO/ole as %of Qthers (4)' (42) (.5l) (53) ,
D1atribution Cinl, ,Sectoral IneqU2l1t:y -.27* .24 .02 .19 I......................................... ~ :!~~~ : {~2•......:!.••!~~ ~ .. ~!~~ .~ .Inequality in
Laz1d Distribution
Equality in LandOlIDel:shlp
Cinl, Lend HoldingInequal1t.:y
, -.20(49)
•93(43)
.17(42)
-.12(61)
-.01(62)
•.33(54)..................................................................................................
Inequality in
Size Distribution
of IncOJ:le
Incocle Equality, Poorest40 %Share
Incon;e Equality, Middle40 %Shan
IncOll.8 Inequa1ity,Top 5 " Share
G1n11 Personal IncomeInequal1t.:y
.1'(52)
....25
(52)
-.19(52)
-.OB(48)
-.17(51)
-.14(51)
.14 .(51)
•.29(41)
•04(64)
.00(64)
.05(64)
.04(56)
-.11(65)
-.15(65).21·
(65)
.19(57)..................................................................................................
Egalltartan Egal1tarianisc
PoliticalCam~ ,••••...•........•• ..........•...........•..• .........•.~ .............•...••••••••••••
.01(48)
-.10(54)
.05(48)
-.13(48)
-.12(56)
-.22·(68)
-.10(56)
-.04(56)
-.10(48)
.02~5)
.18(53)
.12(47)
.08(67)
.10(!l-7)
~;~~
~ -.01.(47)
.23(42)
.28-(42)
.24(42)
•.30(:38)
•.39(41)
.30()7)
'..29(53)
.lio·(42)
.17(39)
.10(40)
....33
(54)
•.32. ()6)
Inequalit.:y of Agr1culture-others x Egalitar1an1sm
SectoraJ. Inequality xEgalitar1anisQ
OlIDershlp Inequal1t:y xEgal1tarlanlsm
Holding Inequallt.:y xEgalitar1anisl:l
InequitJ,it:y-Poorest 40 "x E6311tarian1S1ll
Inequal1t:y-Hlddle 40 %x Egalitarianism
Inequallt:y-Top 5 "x Eplltar1anlsm
Ginl-PersonaJ. IncO:lle
DUitrlbutlonx Egalitarian1sm
Interaction
Effects of
Inequality and the
Extent 01'
Egalitarian
PoliticalCampa1an
te," (12
) Staned (...) correlations are s1e;nll'lcant at p =.0.5.() In parenthesis are No. of cases.
188
structural patterns of social inequality exist, (2) there is a moderate
to high level of egalitarian political campaigns among the people so
that, (3) the two conditions reinforce each other.
Turning our attention to elite-initiated political violence, we
find none of the variables remain significant for Political Restrictive
ness, once the effect of Political Institutionalization is partialled
out. The inequality of land distribution and high concentration of
income among the richest 5 percent of the population is positively
associated with Provoked Repression, while the existence of an overt
egalitarian political movement is negatively related to repressive
political violence. These results clearly confirm Hypothesis 1-1.4,
while some ambiguity still remains as regards the validity of Hypothesis
1-1.3. In fact, considering our finding that the Provoked Repression is
a type of political violence where mass violence and governmental
coercion merge together (section 4, Chapter II), it is not surprising
to find such a result. In general, therefore, we are inclined to con
clude that, in consistence with our hypotheses, the equality issue is
less salient for the explanation of elite violence and governmental
coercion.
On the other hand, the data support our first proposition, derived
from the power and conflict model. In other words, social inequality
is a predictor to mass political violence, which are independent from
the effects of performance variables that we have already analyzed in
Part II.
In addition, we find that the interaction specifications in general
are more powerful factors of mass political violence than the "main"
189
variables of inequality. In most cases, the magnitudes of coefficients
are consistently higher for multiplicative specifications than for the
"main" variables. We are not able to include all of these interaction
variables in the subsequent analysis due to the fact that the number of
valid cases for these variables is too small for a rigorous generaliza-
tion. However, the substantive and theoretical insights drawn from the
interaction hypothesis should be incorporated in any future attempt to
build a better model of political violence. Serious efforts to secure
more reliable and comprehensive data seem to be a most urgent task.
In the following analysis, we l.nll proceed as if the multiplicative
effects were negligible. Such an "as if" basis, however, is only
justified by the lack of more COmprehensive data and should not be
understood as an effort to discount our finding on the importance of
the interaction effects.
B. Testing Research Proposition 1-2
Are these equality variables, in fact, better predictors of mass
political violence than the "will" and "capacity" variables? This
question will be tentativelyl4 answered if we examine the Research
Proposition 1-2. We will now evaluate the relative importance of the
two sets of variables--the "will" and the "capacity" versus the "out-
come"--in determining the level of mass political violence across
different political systems.
141 say it "tentatively," because the final answer would requirean examination of the interaction specifications after a more comprehensive data are secured.
190
As Table 7-1 shows, the problem of missing data is a serious
problem that handicaps ,our efforts to find relationships between
variables. The inclusion of large number of variables in a regression
equation will result so few degrees of freedom that our inference would
be unreliable. One way to cope with this problem would be to choose
only those variables with as little missing data as possible. Of course,
this procedure would rule out many variables whose interrelations might
be more significant than the ones retained, thus losing considerable
amounts of available information that might be useful theoretically.
Herein, we shall attempt to make a conservative use of the avail-
able data rather than to limit the scope of our generalizability by
getting result from limited number of countries. 15 Thus, a somewhat
arbitrary decision is made to report the results based on two separate
analyses, with differing sample sizes. Analysis is first conducted only
for variables in which the regression will yield at least 50 valid
units of observation, or approximately two thirds of the total sample
size, thereby dropping all the interaction specifications and five main
variables. The result is an analysis of only four main variables for
Protest and five main variables for Internal War.
In order to broaden our perspective for future studies, a second
set of analyses is conducted with variables which have been assembled
for at least 40 countries, that is, a half of our total sample size.
This criterion provides us six equality variables for Protest and five
l5If we include all the variables whose partial correlations aresignificant, it turned out that the regression analysis will be based onless than a half of the total sample (N=8l).
191
for Internal War, all of which have significant partials in Table 7-1.
The variables chosen by these criteria are reported in A and B of
Table 7-2. The three variables remained significant for Provoked
Repression (Table 7-2.C) will also be analyzed.
Note that the first sets of test constitute a conservative use of
the available data, because we drop variables which are demonstratedly
more important predictors than the ones we have adopted. The primary
problem we address through such an analysis is to see whether even the
most conservative use of the data yield a result as we have hypothesized;
that is, equality variable corrects the misspecification of the model
tested in Chapter V. If the result indicates that equality variables
exert significant contributions in explaining the two types of mass
political violence independently from the "will" and the "capacity"
variables, we are in a position to conclude (1) that our revised theory
of political violence, in fact, has "detected" and "reduced" the errors
found in the model tested in Chapter V and, thus, (2) that evidence in
favor of the revised theory is demonstrated.
The second sets of test, which use fewer countries but theoretically
more salient variables for our analysis, will enhance the confidence
level of our arguments. For example, if the joint parameter estimation
reveals that the independent effects of the "willll and Ilcapacityll
variables disappear entirely when the Iloutcomell (equality) variables are
taken into account, we would conclude (1) that the evidence in support of
the Deutsch-Huntington model is likely to be reduced further, if a
comprehensive set of data were made available; and, (2) that we should
stick to the power and conflict model in order to explain the_variations
of mass political violence across countries. An alternative possibility
Table 7-2. Equality Variables Selected to Test Research Proposition 1-2
A. variables chosen to estimate Protest
set 1: No. of cases > 501
1. Income Equality: Poorest 40% Share2. Income Equality: Middle 40% Share3. Income Inequality: Top 5% Share4. Egalitarianism
B. variables chosen to estimate Internal Warset 1: No. of cases > 50
1. Equality in Land Ownership2. Income Equality: Poorest 40% Share3. Income Equality: Middle 40% Share4. Income Inequality: Top 5% Share5. Egalitarianism
set 2: No. of cases ~ 402
1. Gini: Sectoral Inequality2. Income Equality: Middle 40% Share3. Egalitarianism4. Ownership Inequality x Egalitarianism5. Inequality-Poorest 40% x Egalitarianism6. Inequality-Middle 40% x Egalitarianism
set 2: No. of cases ~ 40
1. per capita Agricultural Income as % of Others2. Equality in Land Ownership3. Gi~i: Personal Income Inequality4. Egalitarianism5. Ownership Inequality x Egalitarianism
C. variables chosen to estimate Provoked Repression (N=47)
1. Gini: Land Holding Inequality2. Income Inequality: Top 5% Share3. Egalitarianism
1 Variablessignificant or
2Variables
for this set are selected regardless of whether the partials in Table 7-1 arenot.
for this set are confined to those whose partials in Table 7-1 are significant at p < 0.05
I-'\0!',J
193
may also be tenable, where all or any combination of the "will," the
"capacity" and the "outcome" variables would have independent impacts,
respectively, on mass political violence. In such incidences, we would
have to conclude: (1) that the two models share their independent
explanatory competence in a way to complement each other toward a better
approximation to the truth and, thus, (2) that the two rival models
must either be synthesized into a fuller one or, at least, share an
equal scientific merit. We now turn to evaluate these arguments in
terms of the data available to us.
The procedure taken to test our proposition is a stepwise multiple
regression technique. In searching for predictors to Protest, we
included Voter Turnout in the same equation with two sets of equality
variables identified above, since Voter Turnout was the only significant
predictor of the Protest reported in Chapter V. For Internal War we
include, in line with prior findings, both Voter Turnout and the Govern
ment Responsiveness Index. Finally, Provoked Repression includes only
the three equality variables which were significant in Table 7-1.
The results for Protest are reported in Tables 7-3.1 and 7-3.2.
Voter Turnout remains the most significant predictor to Protest in
both Table 7-3.1 and 7-3.2, suggesting that when non-elites have a
chance to choose the leadership and the institutional arrangements of
a country, the result is a lessening of demonstrations and rioting in
the streets. Controlling the Voter Turnout, the egalitarian campaigns
inculcated in a political system is positively associated with Protest.
194
In Table 7-3.1 the Tolerance16 of the three equality variables
which falls barely below the confidence level (p = 0.05) are all high.
This may suggest that the result of Table 7-3.1 is an artifact of our
decision to maximize the size of the sample at the expense of choosing
variables for their theoretical importance. A comparison of the results
in Tables 7-3.1 and 7-3.2 suggests to us that the true world is more
like the latter, although we are prohibited to draw too strong·an
inference out of it, since it is limited to only half of our sample.
Not only are the Tolerance levels of the variables remarkably reduced
but the R2 value is much higher in Table 7-3.2 compared to 7-3.1.
In Table 7-3.2, Egalitarianism turns out to be statistically
insignificant when its interactive effect with Land Ownership is
introduced in the model; but Income Equality: Middle 40% Share, in
contrast, is a more significant predictor than its interaction specifi-
cation. Thus, there is support for the importance we attached to the
interaction effects, though a more conclusive evidence for it should wait
until more comprehensive data are available to us.
The inequality of ownership as an issue of egalitarian political
campaigns and relatively large share of national income by the middle
l6Tolerance of a predictor variable not in the equation statistically indicates the proportion of the variance of the predictor notexplained by the variables already included in the regression equation.Thus, the value of "0" means that a given variable is a perfect linearcombination of others included in the equation. Tolerance of 0.96indicates that 96% of Income Equality: Poorest 40% Share is unexplainedby the two variables already entered. In other words, all the threeequality variables are relatively uncorrelated with the other two intervening variables in the equation. This is understandable in view of thefact that we dropped many variables that are more significantlycorrelated with the Protest due to a limited number of observations.
Table 7-3.1 Step~'ise Regression on Determinants of Protest (N=55)
A. Variables in the Equation* (F ~ 2.40 or a ~ 0.05)
195
parameter standardized standardintervening variable estimate(B) estimate (Beta) error of B F
Voter Turnout -0.02 -0.37 0.01 9.17
Egalitarianism 0.23 0.30 0.09 6.39
constant 1.17
R2 0.22-2
0.19 F = 7.36= R =
* Variables are arrayed in the order of entrance.
B. Variables not in the Equation
intervening variable Beta in Partial Tolerance F
Income Equality: 0.20 0.21 0.86 2.28Middle 40% Share
Income Equality: 0.16 0.18 0.96 1.74Poorest 40% Share
Income Inequality: -0.15 -0.17 0.95 1.46Top 5% Share
196
Table 7-3.2 Stepwise Regression on Determinants of Protest (N=40)
A. > >Variables in the Equation* (F 2.25 or a = 0.05)
parameterinterveni~g variable estimate (B)
Voter Turnout -0.03
Ownership Inequality % 0.01Egalitarianism
Income Equality: Middle 0.0540% Share
standardizedestimate (Beta)
-0.58
0.43
0.31
standarderror of B F
0.01 14.94
0.001 9.45
0.02 4.73
constant
R2 = 0.35
0.55
-2R = 0.30 F = 6.48
* Variables are arrayed in the order of entrance.
B. Variablef 'Lot in the Equation
intervening variable Beta in Partial Tolerance F
Gini: Sectoral Inequality -0.11 -0.10 0.60 0.37
Egalitarianism -0.03 -0.03 0.50 0.03
Inequality-Poorest 40% X -0.19 -0.16 0.46 0.90Egalitarianism
Inequality-Middle 40% X -0.18 -0.15 0.45 0.80Egalitarianism
197
40 percent of the population seem to indicate the salience of the middle
class in political process. If it is a valid inference, the fact that
the interaction specification of Ownership Inequality with Egalitarianism
and Income Equality measured by the proportion of national income shared
by middle 40 percent of the population group are both significant pre-
dictors of Protest, along with Voter Turnout, may suggest that Gamson's
finding in American political process has some degree of validity in
international perspective too. 17 In other words, the data seem to
indicate that controlling for Voter Turnout, Protest grows more likely
from a political base of relatively well-to-do middle class character-
istics and possibly remarks "an impatience born of confidence and a
sense of rising power" on the part of the non-elite, or even "as much .,.
symptom of success as a cause," but occurs less likely in politics with
severer sectoral inequality or the political bases of the poorest
stratum in nations. 18
Two sets of regression estimates for Internal War are reported in
Tables 7-4.1 and 7-4.2. When variables used for the larger sample of
l7Having found that the use of violence tactically through. suchmeans as strikes, bargaining and propaganda turned out to be quitesuccessful in gaining specific objectives of subordinate politicalgroups, Gamson concluded that violence is "the spice of protest," though"not the meat and potatoes." William A. Gamson, "Violence and PoliticalPower: The Meek Don't Make It," Psychology Today (July, 1974), p. 39.
l8Again, this statement is to be understood as a plausible impression of a likelihood, but not as a hard fact conclusively demonstratedby the data. Consider also the following statement found in Bachrachand Baratz, .2£. cit., pp. 105-106. "More or less permanent shifts in themobilization of bias, and the value-allocation that flows from it, arebrought about primarily because the previously disfavored persons andgroups have gained additional resources of power and authority, usuallyfrom movements or institutions outside the polity in question."
198
Table 7-4.1 Stepwise Regression of Determinants of Internal War (N=5l)
A. Variables in the Equation* (F ~ 2.20 or a ~ 0.05)
parameterintervening variable estimate (B)
Government Responsiveness -0.41Index
Egalitarianism 0.17
Voter Turnout -0.02
Equality in Land -0.01Ownership
standardizedestimate (Beta)
-0.41
0.25
-0.30
-0.22
standarderror of B
0.14
0.10
0.01
0.004
F
7.97
3.10
5.22
2.91
constant
R2 = 0 33.1. 27
F = 5.68
* Variables are arrayed in the order of entrance
B. Variables not in the Equation
intervening variable Beta in Partial Tolerance F
Income Equality: Poorest -0.10 -0.11 0.88 0.5840% Share
Income Equality: Middle -0.02 -0.02 0.69 0.0140% Share
Income Inequality: Top 0.08 0.09 0.80 0.365% Share
199
Table 7-4.2 Stepwise Regression of Determinants of Internal War (N=4l)
A. > <Variables in the Equation* (F 2.20 or a = 0.05)
parameter standardized standardintervening variable estimate (B) estimate (Beta) error of B F
per capita Agricultural -0.01 -0.42 0.004 9.38Income as % of Others
Equality in Land -0.01 -0.31 0.004 5.27Ownership
Voter Turnout -0.02 -0.30 0.01 4.77
constant 2.58
R2 0.37-2
0.32 F = 7.30= R =
* Variables are arrayed in the order of entrance.
B. Variables not in the Equation
intervening variable Beta in Partial Tolerance F
Government Responsive- -0.17 -0.19 0.80 1.31ness Index
Gini: Personal Income 0.07 0.07 0.57 0.17Inequality
Egalitarianism 0.004 0.01 0.97 0.001
Ownershi~ Inequality X 0.002 0.001 0.37 0.00Egalitarianism
200
countries are entered in the regression, the predictive power of the
model is increased (R2 = 0.33 as compared to R2 = 0.22 in Table 5-16 in
Chapter V). Thus, the equality variables explain more variance in
Internal War, though we cannot say yet they constitute better predictors
than Government Responsiveness and Voter Turnout. Both Voter Turnout;
and Government Responsiveness index remain as the most important
predictors to the dependent variable; at the same time, the existence of
egalitarian political campaigns and the monopoly of land in the hands of
a small minority appear to increase the likelihood of Internal War.
When theoretically more important equality variables are introduced
at the expense of reduced sample size, the Government Responsiveness
index and Egalitarianism are no longer included in the equation.
Disparity between the agricultural sector and the rest of economy, in
turn, becomes most significant predictor. At the same time, compared to
Table 7-4.1, R2 for Table 7-4.2 is improved significantly in statistical
term, indicating that the welfare function of the government may be a
less salient aspect of the "outcome" variables than the equality
variables. Unlike Protest, Voter Turnout is a less important predictor
of the dependent variable; the main and the interaction specification of
Egalitarianism are less important predictors of Internal War than are
the main equality variables. In general, these results suggest that
Internal War is most likely to be brought about in politics where
inequality is a structured pattern of political economic conditions in
which the masses are permanently or semi-permanently trapped due to the
institutionalized inertia of the power groups to achieve a factual and
moral order, binding on all, within the framework of instrumental
201
collectivism and mechanisms for peaceful resolution of inter-group
hostility, In such instances, egalitarian political campaigns seem to
exert potentially more formative influence on the political perceptions
and awakening of the non-elite subordinate class than it stimulates the
actual political activities in an overt fashion.
Finally, turning to the estimate of Provoked Repression in Table
7-5, we find that only Gini: Holding Inequality falls within our !eve1
of significance (a ~ 0.05). Therefore, we will retain this variable as
a predictor to Provoked Repression, as has been identified for the first
time in our analysis.
In sum, the data generally confirm the first proposition which we
have derived from the power and conflict model. Introduction of social
equality variables into the model have improved our overall explanatory
power significantly. In addition, the data also indicate that the
"outcome" of political performance is far more important in predicting
mass political violence than "will," "Capacity" or "re~oonsiveness"
variables. Thus, we are led to conclude that a straightforward reliance
on political institutions, as advocated by the consensus model, is
inadequate. The argument of power and conflict model that a safeguard
for a fruitful analysis of political process is to be armed with an
initial skepticism on the "promises" and "claims" of the dominant
groups and a sympathy toward possible victims of political processes is
partially warranted by empirical evidence.
However, at the same time, we cannot entirely reject the function
alist model in favor of the alternative modeL The "choice,:' and
"responsiveness" constitute independent sources of political order
202
Table 7-5 Stepwise Regression of Determinants of Provoked Repression(N=47)
A. Variable in the Equation (F ~ 2.76 or a ~ 0.05)
intervening variable
Gini: Land HoldingInequality
parameterestimate (B)
0.02
standardizedestimate (Beta)
0.33
standarderror of B
0.01
F
5.41
constant -1.34
R2 = 0 11.
B. Variables not in the Equation
intervening variable Beta in Partial Tolerance F
Egalitarianism -0.23 -0.24 1.00 2.69
Income Inequality: 0.09 0.08 0.82 0.31Top 5% Share
203
insofar as they inhibit mass revolts. Moreover, a high level of
pluralism in political institutions and procedures appears to be a
sine qua non of Political Restrictiveness, possibly suggesting that
institutionalization is the first and most important step toward
sharing political power. In the final analysis, a polity can only
become stable and effective as well as equitable if it can reach a high
level of institutionalization.
The final import of our research is that the extent of non-elite
political participation, indicated by Voter Turnout, remains as a
significant predictor to mass political violence throughout our analyses.
Thus, in countries where masses are actively involved in institution
alized methods for choosi~g their leaders and institutions, there are
less appeals to the use of brute physical force on the part of the non
elite.
For these reasons, our next theoretical step seems to lie in
synthesizing the functionalist model with the power analysis into an
integrated perspective so that the "will," "responsiveness," "choice,"
and "outcome" can all be elaborated into future studies of political
order. We will develop such an integrated perspective after we examine
the final set of variables of our model in Chapter VIII.
CHAPTER VIII
DEPENDENCY, INEQUALITY AND POLITICAL VIOLENCE
1. Introduction
So far in our analysis, we have implicitly assumed that the
international system consists of a set of autonomous individual
countries from which our units of observation can be selected indepen-
dently of one another. Yet, there are many irrefutable arguments that
posit the international system as a structure of interdependence or a
stratified system of interactionl and not merely as a set of indigenous
sovereign actors.
The whole history of colonialism, imperialism, dependency, domination
and exploitation, for example, presupposes that national political
systems, their institutions and patterns of development are "non-
independ ent" and "non-indigenous." Multitudes of trade and aid as well
as alliance and security treaties denote further evidence of an "inter-
dependence" of nations, with a process of historical and cultural
diffusion in the international context.
These international systemic factors usually operate as external
constraints on policy-making and political performance in domestic
contexts, directly or indirectly via institution-building. Ignoring
these facts also obscures how the development of some country may cause
lSee Galtung, E.P.. cit., and Peter Heinz, The Future of Development(Switzerland: Hans Huber Publishers, 1973).
205
2tmderdeve10pment of the others. Moreover, as we have noted in Chapter
VI, the fact that nations are not independent units of analysis by them-
selves violates the assumption employed so far in this study. As a
result, our analysis may have yielded a biased result due to an omission
of certain important explanatory variables, which constitute a systematic
source of error that may be correlated with characteristics of the
international system structure. 3 Therefore, our final chapter purports
to improve the level of confidence in our findings up to this point by
minimizing such a possibility.
Proposition 2 identified in Chapter VI postulates that dependency
is an independent variable whose impact may be conspicuous on both the
intervening (political performance) and the dependent (political
violence) variables. In testing the proposition, the question of
dependency will be examined mainly in economic terms, since it is believed
that, so far as international politics is concerned, a nation's economic
2Consider the argument made by underdeveloped cotmtries calling forthe "new world economic order," of which one of the most vigorous appealsis to remove the external constraints which prevent them from achievingtheir potentials.
3Note that the notion of the stochastic error in causal analysisassumes that the error term (unexplained variance of the dependentvariable) is not correlated with any of the explanatory variables inequations. Other sources of error except a stochastic component mayinvolve the measurement procedures. Other basic assumptions about theerror term are: (1) that it is normally distributed about the mean ofzero, (2) that the residuals are randomly distributed arotmd the fittedvalues of the dependent variables, as well as across different levels ofdevelopment, and types of political systems, etc., and (3) that it has aconstant variance for different values of an explanatory (independent)variable (the assumption of homoscedasticity). cf. Blalock, "A CausalApproach to Non-Random Measurement Error," American Political ScienceReview, Vol. 64 (Dec., 1970), pp. 1099-1111; Blalock, Causal Inferencesin Non-Experimental Research, ,2£.. cit., pp. 14-26, 44-50; Herbert B.Asher, Causal Modeling (Beverly Hills: Sage University Paper, Series No.07-003, 1976).
206
status is correlated so closely with power and status that the former
can be taken as a representative index for identifying the most and
least advantaged actors in both power and status. We now translate the
concept into empirical variables.
2. Measurement of Variables
A. Vertical Trade
Following Johan Galtung and James caporaso's4 works in measuring
the concept of external dependence, we operationalize the concept in
terms of: (1) Vertical Trade Index, (2) Trade Partner Concentration
Ratio, and (3) Trade Commodity Concentration Ratio.
Galtung employed a Vertical Trade index to locate each country on
a continuum of the international structure of division of labor, mainly
in terms of whether it exports primary goods and imports manufactured
goods, or exports manufactured goods and imports primary goods. This
index, thus, measures the concentration of primary goods in the com-
position of a country's total trade relative to manufactured goods. The
formula derived by Galtung to tap this vertical structure of international
division of labor is:
Vertical Trade Index = ~(~a_+__d~)~-~(~b~+~c~)__(a + b + c + d)
where: a =b =c =d =
total value of raw materials importedtotal value of raw materials exportedtotal value of manufactured goods importedtotal value of manufactured goods exported
4Johan Galtung, ~. cit., and James Caporaso, "MethodologicalIssues in the Measurement of Inequality: Dependence and Exploitation,"in S. J. Rosen and J. R. Kurth, eds., Testing Theories of EconomicImperialism (Lexington: D. C. Heath, 1974), pp. 87-114.
207
The index locates a country which mainly imports raw materials
and exports manufactured goods on a higher value approaching to 1 and
one who exports larger amount of raw materials and mainly imports
manufactured goods on a lower value approaching to -1. The former are
construed as "top-dogs," "center states" or "exploitative" countries,
and the latter as "under-dogs," "peripheral states," or "exploited"
countries. After the data are collected, the scale is reversed so that
it is comparable with other indicators of dependency. As a result, the
lower scores actually mean relatively dominant actors in the international
division of labor and higher scores stand for subordinate actors.
Since Vertical Trade index is based on the assumption of balanced
trade and the traditional international division of labor, it is less
sensitive to the dependency trends in the international economy. In
many developing countries, imports exceed the exports or, otherwise,
the positive balance of exports over imports are largely construed from
the processed manufactures of low-level technology whose raw materials
are often imported from more developed countries. In contemporary
years, such raw materials as food and minerals are sometimes exported
from more developed economies to less developed countries. The index
also does not differentiate manufactured commodities of heavy industrial
products from those of lower level technology, indigenous vs. imported
technology, export earned from inducing foreign corporations or invest
ments. As a result, the scores for developing countries are likely to
be overestimates. The Trade Partner Concentration Ratio and the Trade
Commodity Concentration Ratio are used to overcome some of these short
comings.
208
B. Trade-Partner Concentration and Trade Commodity Concentration
Trade Partner Concentration is defined by the sum of the squared
proportion of each country's export to another countries to its total
exports, ~d measures roughly the extent to which a country's exports
are diversified or concentrated into a limited number of partners. The
scale may vary from 100, indicating a country's total exports go to one
partner, to a value approaching to but never equal to 0, indicating most
evenly diversified trading partner. The formula used to derive this
ratio is:
Partner Concentration Ratio = 100 x
where: EijTE in
= value of i's exports to j= total value of i's exports= number of trading partners
i's total trade.having 0.01% or more of
The Trade Commodity Concentration is calculated by a similar
formula to the Partner Concentration Ratio, and measures the extent to
which a country's export is dependent upon limited or diversified
categories of exportable commodities.
Commodity Concentration Ratio = 100
where: = value of i's export of commodity j to the rest of the world= total value of i's exports= number of commodity classification defined as three digits
in SITC
The data for the above three indicators are adopted from Robert D.
Wa11eri's dissertation research as indicated in the introductionary part.
All of the data are collected for the year 1965.
209
C. Composite Index of Dependency
Correlations between the three indicators of dependency were under-
standab1y quite high. Therefore t although we will report the analysis
of individual variables in correlational analysis, it seems simpler to
combine them into a single index of dependency for the purpose of making
the analysis more parsimonious. 5 The composite index of Dependency is
derived from averaging the values of three indicators for a country, after
6the unit of Vertical Trade Index were made equivalent to others.
3. Empirical Evaluation of the Hypotheses
A. Testing Research Proposition 2-1: Correlational Analysis
Table 8-1 will enable us to evaluate hypotheses about the relation-
ships between dependency and social inequality (Hypothesis 2-1.1), and
between dependency and political violence (Hypothesis 2-1.2).
5The correlations are as the following:
Variable No. Variable Name
1 Vertical Trade2 Partner Concentration3 Commodity Concentration
N 1
6768 .39**68 .66**
2
65
.32*
3
6565
* significant at p < 0.01 ** significant at p ~ 0.001Numbers in upper diagonal are number of cases for each correlation
6Note that size of correlations .39 and .32 is not large enough
to justify them for making a composite index of Dependency on a purelystatistical ground. However, it is justified for the reason that eachof the three measures has additive impact on the concept of dependencYtpossibly with different degrees of importance. Having no theoreticalguide currently available to judge whether t for example, the VerticalTrade is twice as important than the Partner or Commodity Concentration,I decided to weight them equally by means of averaging.
The formula used to transform Vertical Trade into an equivalentunit with others is: Transformed Vertical Trade = (100 + raw data of
Table 8-1 Correlations of' Dependency Variables with Social Inequalityand Political Violence
Hypo-
~Vertical Trade TradeTrade Partner Commodity Depen-
thesis intene~g varia~e Coneent- Concent- dencyNo. or dependent variable ration ration Index
* * * ..per capita Agrlcultu.."'a1 . -.32 -.27 -.27 -.JJIncome as %of Others (4J) (44) (44) 44
>.,
** ** •.58** **oj.> Geni:Sectoral Inequalit~ .62 .57 .70or! (44) (45) (45) (45)'d::s
H.2-1.1 go Equality: in Land .07 .06 -.12 .CO.!:i Distribution (52) (53) (53)g .54** .46** **Gini: Land Holding .20 •.508 Inequality (47) (48) (48) 48tr.I- .. .,..24* * -.42**lQ Income Equality: -.38 -.37CJ)
Poore:;t 40% Share (58) (.58) (.56) (58):anl
** ** ** **~ Income Equality: -.48 -.41 - •.51 - •.59> rUddle ~ Share (58) (.58) (.58) (58)bO
.44** ** ** .54**~ Income Inequality: .43 .43s::III Top % Share (58) (58) (.58) (58)~CJ)
.49** ** * **oj.> Gini: Personal .42 .41 •.55~ Income Inequality (50) (50) (50) (50)
* -.24* -.26*- Protest -.30 -.15lQ (67) (68) (68) (68)lIlCll
:a8 .24* .14 * *nl III Internal ~lar .33 .32H.2-1.2
"Q'd (67) (68) (68) (68)<\lor!»** * *
~';i/ Provoked Repression .Hi .37 .31 .35~~ (67) (68) (68) (68)s::+>
.26* **lIlori *P,,--I Political Res~rictive- ., .10 .37 .33lIlO'tip.. ness (67) (68) (68) (68)
-<* significant at p =0.0.5.** significant at p ~ 0.001.In parenthesis is no. of cases.
210
211
By and large, Hypothesis 2-1.1, which asserts an adverse re1ation-
ship between international systemic constr8ints and domestic political
performance, is quite strongly supported. Except in the case of land
distribution, all correlations are significant and in the expected
direction. Thus, we confidently conclude that the more dependent a
polity, the more inequa1 the distributiv.. .if resources within the society.
Turning to the effects of dependency on political violence, we find
Hypothesis 2-1.2 supported for all dependent variables, except that
Protest is inversely related to the level of dependency. Higher levels
of dependency are responsible for higher levels of Internal War, Pro-
voked Repression and Political Restrictiveness, but for a lesser incidence
in Protest. We will postpone any conclusive statement on direct causal
effects of dependency on measures of political violence, until we sub-
ject the results to a test of spuriousness.
B. Testing Research Proposition 2-2: Spurious Relationships
In the light of our findings so far, Research Proposition 2-2
identified at the end of Chapter VI can be evaluated by testing the
following hypotheses:
Hypothesis 2-2.1
(1) Controlling for Voter Turnout and Egalitarianism, the relationship between Dependency and Protest is likely to be spurious7 (forlarger N).
Vertical Trade x 100) / 2, where the raw data of Vertical Trade rangesfrom -1 (dominant actors) to +1 (su~ordinated actors).
7Note that, in Table 7-3 (Chapter VII), Voter Turnout and Egalitarianism are the only intervening variables included in the equation. Forthe relationship whose spuriousness will be tested, see Table 8-1.
212
(2) Controling for Voter Turnout, Ownership Inequality xEgalitarianism and Income Equality: Middle 40% Share, the relationshipbetween Dependency and Protest is likely to be spurious8 (for smaller N).
Hypothesis 2-2.2
(1) Controlling for Government Responsiveness, Egalitarianism,Voter Turnout and Equality in Land Ownership, the relationship betweenDependency and Internal War is likely to be spurious9 (for larger N).
(2) Controlling for per capita Agricultural Income as % ofOthers, Equality in Land Ownership and Voter· Turnout, the relationshipbetween Dependency and Internal War is likely to be spurious10 (forsmaller N).
Hypothesis 2-2.3.
Controlling for Political Institutionalization, the relationshipbetween De~endency and Political Restrictiveness is likely to bespurious. 1
Hypothesis 2-2.4
Controlling for Gini index of Land Holding Inequality, therelationship between Dependency and Provoked Repression is likely tobe spurious. 12
To test these hypotheses, partial correlations are produced be-
tween dependency variables and political violence indicators, controlling
for all the intervening (political performance) variables that remain
significant in our analyses of the preceding chapters. The result is
summarized in Table 8-2.
8Source for this hypothesis is Table 7-3.2 and Table 8-l.
9Source for this hypothesis is Table 7-4.1 and Table 8-l.
10Source for this hypothesis is Table 7-4.2 and Table 8-l.
11Source for this hypothesis is Table 5-10 (Chapter V) and Table 8-l.
12Source for this hypothesis is Table 7-5 and Table 8-1.
I
Table 8-2 Testing Spurious Relationship between Dependency and .Political Violence
Hypo- intervening variable dependent inde'Pendent variable (dependencv)thesis (political perfor- variable Vertical Trade Trade Depen-No. mance) "(politicaJ Trade Partner Commodity dency
~rolled f'or violence Concent- Concent- Index, ration ration
* -.18Voter Tuznout and Protest -.29 -.10 -.21Egalitarianism (.50) (.51) (.51) (.51)
~.2-2.l• • 0 ••••••••••••••••••• .•........ .........••....•.............. .......Voter Turnout, Protest -.22 .01 .02 -.06O..rnership Inequality (39) (J9) (39) (39)x Egalitarianism andIncome EqualitysBiddle 4(Jfo Share
Government Respon- Internal .10 .13 .19 .21siveness, Egalitari- War (46) (46) (46) (46)anism, Voter Tm:nout.and Equality i ..1 Land
H.2-2.2 O....nership ...•.....•...•...•........................................ ... .......per capita Agricul- .L.nternal .12 •06 .21 .19tuzal Income as %of' War (38) (39) (39) (J9)Others, Equality inLand Ownership andVoter Turnout
H.2-2.3 Political Political .04 -.16 .03 -.01Institutionalization Restric- (64) (6.5) (6.5) (6.5)
tiveness
*H.2-2.4 Gini: Land Holding Provoked .00 .:33 .18 .•23
Inequality Repre- (44) (4.5) (4.5) (4.5)ssion
* signif'icant at p ~ 0.0.,5.
213
214
Only Vertical Trade and Trade Partner Concentration are signif
icantly related to Protest and Provoked Repression, respectively, while
the partial correlations for both of the violence indicators with the
composite index of Dependency are not statistically significant. Other
wise, the four hypotheses are generally supported by our data.
Comparing partials for two sets of control variables in regard to
different sample size in analyzing Protest and Internal War, we find
that correlations for smaller samples are in general lower than those
for larger samples. Such differences again indicate the artifactua1
results of selecting variables Which yield larger number of cases.
More theoretically important variables further reduce the size of the
partial correlations. Therefore, we may conclude from Table 8-2 that
the developmental hypothesis is more congruent with data than the non
spuriousness hypothesis in regard to the relationship between dependency
and political violence. Thus, the data indicate that the independent
effects of dependency on political violence are not statistically
significant, when we control for system performance variables. That is,
the impact of dependency on political violence is indirect via its
adverse effects on the system's ability to adequately use, allocate,
or produce the collective goods.
Again, the severe problem of the quality and availability of equality
data hampers rigorous estimations of the regression coefficients of
various relationships we established in Part III. Neither the data base
permits us, nor the scope of this research requires us to test the
mechanisms by which dependency operates as an indirect cause for social
215
inequality via ma1deve1opment,13 institutional decay,14 or by means of
suppressing autonomous po1icies15 in developing countries. Thus, the
empirical investigation of the problem to which the present research is
addressed ~onc1udes at this point. In the conclusion to follow, we will
try to put major findings of the current inquiry into a broader theoretical
perspective, drawing some implications therefrom for future studies on
political violence.
13For example, economists explain that dependency indirectly causesinequality by means of imposing structural obstacles to the Third Worlddevelopment. See Raul Prebisch, The Economic Development of LatinAmerica and its Principal Problems (New York: United Nations, 1950);Albert Hirschman, The Strategy of Economic Development (New Haven:Yale University Press, 1958); Gunnar Myrda1, The Challenge of WorldAnti-Poverty Program in Outline (New York: Pantheon Books, 1970).
14For a useful source of hypotheses on this problem, refer to thefollowing case studies of Philippines by Robert B. Stauffer: liThePolitical Economy of a Coup: Transnational Linkages and PhilippinePolitical Response," Journal of Peace Research, Vol. 11, No.3 (1974),pp. 161-177; The Philippine Congress: Causes of Structural Change(Beverly Hills: Sage Research Papers in the Social Sciences, seriesno. 90-024, 1975); "Philippine Authoritarianism: Framework forPeripheral Development," (unpublished mimeo, University of Hawaii, 1977).
15For perceptive theoretical explorations on such linkage perspectives, see Douglas A. Chalmers, "Developing on the Periphery:External Factors in Latin American Politics," in James N. Rosenau, ed.,Linkage Politics: Essays on the Convergence of National and InternationalSystems (New York: The Free Press, 1969), pp. 67-93; Robert B. Stauffer,"Great Power Constraints on Political Development," in Studies inComparative International Development, Vol. VI, No. 11 (1970-1971), pp.231-251; also Stauffer, National-Building in a Global Economy: The Roleof the Multinational Corporations (Beverly Hills: Sage ProfessionalPaper on Comparative Politics, series no. 01-039, 1973).
CHAPTER IX
CONCLUSION: SUMMARY AND IMPLICATIONS
1. .An Overview of Maj or Findings
I have attempted in this research to specify and test major
hypotheses on the correlates and causes of variations in political
violence at the cross-national level. The main research strategy for
the task, given the absence of a well-developed theoretical structure
to integrate various hypotheses into a unified model, has involved an
eclectic and incremental approach to theory-building. The following
paragraphs sum up the major findings of this study.
The concept of political violence has been defined on the basis
of an eclectic perspective, borrowed from both the consensus model and
the conflict theories of society and politics. Four major aspects of
political violence-namely, protest, internal war, repression, and
coercion--are derived from the following definition of political
violence: an overt act of structural or physical force initiated by
political motives, whose effects depend upon (1) the existence or
procurement of large-scale organizations of which the principal objectives
are to evoke fear of violence; (2) the potential or actual threat to use
the means for physical force; and (3) the actual use of the physical
force. This definition, in turn, was operationalized by means of 18
variables. In a factor analysis of the 18 indicators, five empirical
dimensions of political violence were extracted, namely, Protest and
Internal War (which represent mass political violence), Provoked
Repression, Political Restrictiveness (that measure elite-initiated
217
political violence), and Coercive Resources and Organizations (which is
in discretion for elites to use). A consideration of conceptual and
empirical validity led us to exclude the Coercive Resources and
Organizations factor from our subsequent study of political violence.
Consequently, four composite indicators were selected to measure the
remaining four dimensions, and used in this study as the dependent
variables.
We began by examining the effects of economic development on political
violence. The evidence demonstrates that higher levels of economic
development, as measured by Energy Consumption per capita, lead to:
(1) no systematic and direct impact on Protest and Provoked Repression
activities; (2) curvilinear (logarithmic) and negative effects on
Political Restrictiveness and; (3) a curvilinear (polynomial of degree
two) relationship with Internal War. Thus, movement in a polity from
low to medium levels of economic development entails a decrease in
Political Restrictiveness and Internal War types of political violence,
while movement from medium to high levels is likely to bring about a
marginal decrease in Political Restrictiveness but an increasing tendency
toward Internal War. This finding contradicts the long-standing argument
that the logic of development ensures a linear developmental trend
toward more stable political order in modern societies. Instead, the
evidence indicates that, while the degree of both Political Restrictive
ness and Internal War in the poorer polities is relatively high,
wealthy nations are not any more likely to have lower levels of political
violence of such types than are those at intermediate levels of
development.
218
We have also tested various hypotheses of Deutsch and Huntington
regarding gaps between social mobilization, governmental capacity and
responsiveness, political participation and institutionalization, on the
one hand, and political violence, on the other hand. A rigorous
analysis uncovers no evidence to support the Deutsch-Huntington theory
that the levels of political violence and instability are higher in
countries where (1) the performance of government in meeting welfare
needs is outrun by the degree of social mobilization, and (2) the level
of political institutionalization is outstripped by rapid social
mobilization or mass political participation.
Taking the causal assumptions implied by the Deutsch-Huntington
model as a point of departure, we proceeded to integrate the empirically
observed bivariate relationships into a multivariate causal model.
Economic development and social mobilization, thus, are postulated as
two concomitant independent variables, while political participation,
governmental capacity and responsiveness, and political institutionaliza
tion become intervening variables that stand for a loosely defined
concept of political performance. Analyses of bivariate relationships
demonstrated (1) that Protest is a direct negative function of Voter
Turnout and that, controlling for Voter Turnout, none of the other
intervening variables posited by the Deutsch-Huntington model exert
direct impacts on Protest; (2) that Internal War is negatively related
to both Government Responsiveness and Voter Turnout; (3) that only
Political Institutionalization which measures the extent of pluralism
in political organizations and their procedures is a strong negative
correlate of Political Restrictiveness; and (4) that Provoked Repression
219
is not associated with any of the four intervening variables suggested
by Deutsch and Huntington. In addition, the bivariate effects of
Social Mobilization on measures of political violence reveals that (1)
Protest and Provoked Repression are unrelated to the level of Social
MObilization; (2) Internal War and Political Restrictiveness are
negatively related to Social Mobilization.
When Political Institutionalization was specified as a variable
intervening between two socioeconomic development variables (independent
variables) and Political Restrictiveness (dependent variable), the
independent effects of the socioeconomic development variables dis
appeared, indicating that Political Institutionalization mediates
all of the effects of socioeconomic development variables on Political
Restrictiveness. In addition, when placed within the larger model, only
Social Mobilization in its curvilinear (polynomial) specification retains
its impact on Political Institutionalization, indicating that Social
Mobilization is the key variable in determining the level of Political
Institutionalization and that high Political Institutionalization, in
turn, leads to lower level of Political Restrictiveness (see, Figure
5-3.2).
The analysis further indicates that the data are inconsistent with
another theory, namely, the argument that higher levels of economic
development lead to higher levels of democratic political participation
and more responsiveness in government toward satisfying welfare demands.
The beginning or intermediate stages of economic development tend to
bring increases in Voter Turnout and Government Responsiveness. However,
countries at the highest levels of economic development typically
220
experience a declining mass political participation and governments
less responsive in meeting welfare demands. In addition, we find no
statistically significant relationship between Social Mobilization and
Voter Turnout. Social Mobilization, taken by itself, exerts an acce1er-
ating impact on the level of welfare responsiveness of a government, but
it plays only a secondary role in predicting to welfare responsiveness
when placed within the larger model. These findings lead us to favor
the threshold hypothesis of democratic performance and to reject the
linear argument. Evaluation of these bivariate findings in accordance
with the causal inference adopted, however, demonstrates that Government
Responsiveness and Voter Turnout mediates the effects of socioeconomic
development variables on Internal War. This suggests that the re1ation-
ships of Energy Consumption per capita and Social Mobilization to
Internal War, though established by the bivariate tests, are spurious
when the intervening variables are taken into account.
The model tested in Chapter V does not correspond satisfactorily
with the observed data on two types of mass vio1ence--Protest and
1Internal War. Moreover, Provoked Repression is unrelated to
any of the variables postulated by the model. Accordingly, we
reformulated the model to incorporate hypotheses derived from con-
flict and power analysis. The argument put forward by dependency
theorists, positing that countries cannot generate policies and operate
institutions autonomously, is also built into the resulting
1See R2 values of the functionalist model in Table 9-1 below.
221
quantitative cross-national analysis. The result of the analysis in
Part III demonstrates that the revised model, in fact, enables us to
identify the most important variables, thereby minimizing the consequences
of the specification errors found in the functionalist theory. Moreover,
the explanatory power of the revised model is greater than that of the
functionalist model adopted in Part II. The two models examined in
Parts II and III are compared in Table 9-1. Proportions of the explained
variance, especially for mass political violence, are remarkably in
creased when the assumptions and specifications of the original
(functionalist) model are modified in line with the perspectives drawn
from power analysis. With respect to elite-initiated political violence,
however, the findings in Part II are basically unchanged. Therefore,
we concluded in Chapter VII: (1) that the two models deserve equal
theoretical merit in the sense that each constitutes an independent
source of explanation for different types of political violence and
(2) that, by incorporating the complementary perspective into a new
theory of political violence, we achieve a better approximation to the
data.
By way of conclusion, we now suggest an eclectic model of political
violence. Although suggested by the findings herein, this model requires
validation through future studies.
2. Implications for Further Studies
The problem of quality and availability of data, particularly in
regard to inequality, does not permit broad generalizations. However,
in view of the nature of the findi~Lgs, we can suggest a model on the
major cross-national determinants of political violence, which may serve
Table 9-1 Major Predictors of Political Violence, Functionalist Model vs. Power Analysis
,lleviseo. 110del (Power Analyois)Functionalist Model
dependent larger N, conservative smaller lit prospectiveTypes estimation likelihoodvariables
predictors R n2 predictorsR R2 predictors R R2
(11) 50) (N ~ 40)
Protest Voter Turnout -.')1' .12 Voter .Tumout .47 .22 Voter Turnout .59 .35(N" 67) Egalitarian Ownership
(N=55) Inequality xEgalitarianism
Income Equal-l-
Masa ty,l1iddle 40%Share
Political (N=40)Violence
• ••• c ••••••• ...... .. "" . .... .... .. .............. .. ... .... ............... • •• •• II ••
Internal Wax Government .47 .22 Government .58 .'J'J per capita .61 .')?Responsive- Ilesponsive- Agriculturalness ness Income as %
Voter Turnout Egalitarianism of Others
(1I=6?) Voter Turnout Equality inLand Owner-
EqUality in shipLandOwner- Voter Turnout
;ship(l/='il ) (N=41)
Provoked none .00 .00 Gini index 01· .JJa.11
Repression Land HoldingStructure Inequality
of ............. .......... (N=56)............ .............. ... ..... .. ... .... ... .. .....•..•Coe:x:clon Political Political _.Va .54
Restrictive- Institution-ness alization
(N=80)
a, zero-oxder correlationsAll other Rs. are multiple correlationssignificance level, p~. 0.05
l'.:li..:>
'"
223
as a conceptual guide for future studies. Figure 9-1, a diagrammatic
form of the model, can be summarized verbally as' '_lows.
First of all, political violence is a direct negative function of
political performance. Political performance, in turn, is related to
two independent sets of variables, namely, socioeconomic development
and external constraints on system performance. Socioeconomic develop
ment contributes to an increased level of political performance, while
dependency operates to inhibit political performance.
Secondly, the effects of two independent sets of variables on
political violence are mediated primarily through three intervening
variables: (1) governmental efforts to increase the level of
institutionalization and the capacity and responsiveness to meet general
welfare demands; (2) the extent of non-elite participation to choose
leaders and institutions, and effectiveness of the participation to
increase sense of political efficacy; and (3) the extent to which
equality in the distribution of resources reduces the level of political
tensions and inter-group hostilities within a society. In addition,
there is a nonlinear relationship between socioeconomic development and
measures of political performance.
Thirdly, each type of political violence is typically associated
with different aspects of political performance. Higher levels of
institutionalization are associated with reduced political restrictiveness.
Increased political participation, possibly with an increase in the
sense of political efficacy, and a more equal distribution of material
resources are most powerful sources for reducing the extent of mass
violence directed against the agents of elite structures.
Figure 9-1 A Model of Political Violencea A Synthetic View
,.......i socioeconomic developme~~_~~nOn-linear)~ -~ political performanc - .~ external,constraints ~\.. e' (o --.political violence
I I (linear) I I ,\I • I I ,\
I • I ' ~,. - - -~ "~-
~ Institutionalization - )Political Restr1ct-~(Will) iveness ~
... : structure of coercion. . ~I ~ ~ .
: lpartiCi- Provoked Repression'" iI pation ~,(-) ":' . ~ tl: (choice) : .~ J,
J, :.- . ~ +'. ~ Collective Equality~ InternaJ. War I mae. po1itioaJ. v101ence
- Goode (outcome~ r /I ..I'Welfare. /1-.~ : T
(respon- Political Protestsivenesa)
Dependency(internationaJ. st~cture)
:. ;--- - I a • , "\, , . : ' \
Economic Development" , \(material resou:rce~j
Social Mobilization(human resources)
,.......
~1ii~Q)lQ
.g~
- .. '
keya---t main pathslanalyzed
i:==i possible pathsaassumed~ .rectprocaJ. pathsa~anaJ.yzed
postulated rule of correspondence~
~.
~i
225
Provoked Repression is the least satisfactorily explained
phenomenon in this study, thus indicating a major shortcoming in this
study. A static evaluation of the model, due to the use of cross-
sectional data, has made us unable to examine the reciprocal causal
structure among the endogenous variables (political violence). Consider-
ing the fact that Provoked Repression mainly refers to governmental
responses to mass uprisings, an analysis of the model in a dynamic time-
series perspective might explain such political violence more satisfactor
ily. While we have ju~tifiab1e reasons2 to defend the cross-sectional
data base adopted in this study, an attempt to incorporate the dynamic
implications of the model is an important avenue for future analysis.
In addition, we found that Protest is more of a symptom of
"political health" rather than of "abnormal politics." We found that
Protest is consistently associated with (1) an equal distribution of
material resources; (2) polities in which the non-elite members and
groups are restricted as to participation in the political processes;
(3) higher levels of egalitarian political consciousness and activities
to achieve such a social goal; (4) polities in which the middle class is
relatively better off in terms of its share of national income; and
(5) countries that are less subject to dependency in international
contexts.
2The primary scope and objective of this study, as noted in theintroductory part, involve long-term effects of the exogeneousvariables on the dependent variables. Note also that all of ourexplanatory variables are not easily subject to short-term fluctuations.
226
A more conclusive statement on this hypothesis requires further
validation by means of a more refined research design. In securing
more comprehensive and reliable data as well as applying the model
to a more policy-oriented perspective, a micro-analysis with a cross
national scope would appear to be useful direction in the next generation
of comparative research.
•
APPENDIX 1. FACTOR ANALYSIS OF 18 'PROPOSED' INDICATORS OF POLITICAL VIOLENCE (OBLIQUE ROTATION)
Factor l':atrix Using Principal Factor. No Iterations
VARIABll COJ1~-ronALITY FACTOR 1 FACTOR 2 FACTOR ;3 FACTOR 4 FACTOR ..5" .' .
Demonstration 0.89846 0.,54510 0.45010 -0.40211 0.~11 -0.34164Riots ." 0.87210 0.68190 0.:39299 -0.41427 0.00645 -0.285661,0. of Deaths • 0.92024 0.82239 0.00014 -0.:31820 -0.2;3691 0.29418Armed· Attacks ~ 0.81793 0.76.501 0.:31516 -0.:364:35 -0.03:306 0.24319Gov'.t· Sanction 0.8;241 0.77142 0.1.1589 -0.41781 0.19689 . -0.114611'0. of Coups . 0.41183 0.57871 0.0;3610 0.04515 -0.27911 0.04<)55'Demo/capita 0.85218 0.51911 0.:33002 :-0.5.5499 0.16780 -0.37169Riot/capita 0.84975 0.58221 0.24;368 0.51566 -0.24079 -0.24908Deaths/capita " 0.88882 0.80294 ..·0.04129 0.07087 -0.28424 0.39571Attack/capita
,0.818)2 . 0.74)29 0.22115 0.:35268 -0.149.52 0.)6045
Sanction/capita 0.8192) 0.61808 0.0)407 0.,56159 -0.10170 -0.16057Gov •t Expenditure 0.75991" , 0.09117 -0.0.5440 0.24910 0.77485 0.293.58Defense Expenditure 0.77885 0.44777 -0.14046 -0.171.51 0.71628 0.1270)Internal Security Forces 0.58422 0.2,5457 -0.00774 0.48410 0.50929 0.16009 .Press Freedom 0.81579 -0.45224 0.15'1:7 0.07243 -0.12084 0.U774Electoral Competition 0.708.51- . -0.41)14 .0.72172 0.044)2 0.08480 0.08538Power Distribution 0.81343. -0.47485 0.74185 0.05906 0.14610 0.11225Freedom of Oppositlon 0.78734 -0.3)875 0.'79621 -0.06227 -0.080)4 .. 0.16922.ElgenvaJ.ue 6.21 3.00 . 2.18 " 1.92 " 1.08Pet of Var .
.~.S 16.1 12.1 10.6 6.0•Cum Pet ;34-.S .51.1 '63.2. : 1).9 79.9.
•
After Rotat:1 on Hith Kaiser Normalizatlon
FACTOH PA'lvl'EHN
FACTOR 1 !i'ACTOH 2 }i'AC'l'OR 3 l1'Ac'rOR 4 FACTOR .:2
Demonstration -0.10269 0.11565 0.13025 0.07308 -0.95245·Riots 0.15367 0.04161 0.14867 -0.18189 -0.83988No. of Deaths 0.82797 -0.1475.5 -0.16408 -0.06668 -0.2.5186Armed Attack 0.71148 0.lL~180 -0.13632 0.0.5485 -0.47147Gov't Sanction 0.19274 -0.2019.5 0.0210.5 0.05L~8 -0.77689No. of Coups 0.4.5667 -0.11789 0.21919 -0.1.5l I-93 . -0.08655Demo/capita -0.14417 0.04903 0.878Ln 0.1.5116 -0.26094Riot/capita 0.160l1-6 -0.004H3 0.85891 -0.13025 -0.02385Deaths/capita 0.90729 -0.12379 0.06412 0.03866 0.09219Attach/capita 0.80704 0.14043 0.33219 0.1932.5 0.12968Sanction/capita 0.21143 -0.19523 0.76424 0.04822 0.01411Gov't Expenditure -0.00501 0.04400 -0.05790 0.88303 0.05168Defense Expenditure 0.05581} -0.22280 -0.18604 0.6870.5 -0.40134Internal Security Forces 0.0.5178 0.00288 0.29646 0.66502 0.12768Press Freedom 0.02689 0.886.50 0.02726 -0.10991 0.06902Electoral Competition -0.071.55 0.82655 0.0075.5 0.0.51.51 -0.04164Power Distribution -0.10066 0.87376 -0.01827 0.11l~}0 -0.02067Freedom of Opposition 0.13110 0.89877 -0.07195 -0.07.581 -0.9.5425FACTOR NAME Internal Political Provoked Coercive Protest
Har Restrictive- Hepression Resourcesness
FACTOH CORRELATIONS 1 (81)2 0.26 (80)3 0.:33 0.04 (81)4 0.00 0.09 0.13 (81) l'V
l'V.5 0.36 0.07 0.09 0.09 (81) (Xl
•
•FACTOR STRUCTURE
.
FACTOR 1 FACTOR 2 FACTOR 3 FACTOR 4 FACTOR 5
Demonstration 0.25544 0.06261 0.18249 0.16963 -0.92.517Riots 0.49660 -0.04784 0.24626 -0.0866.5 -0.88818No. of Deaths ... 0.90292 -0.;6912 0.1)220 -0.0.5108 -0.54170Armed Atta.ck 0.'79940 -0.07726 0.14)48 0.06809 . -0.71248Gov't Sanction 0.53401 -0.)1355 0.15847 0.14981 -0.86'799
. No. of Coups 0.59225 -0.23891 0.36394 -0.10660 -0.26448Demo/capita. 0.23145 0.01612 0.87061 0.288)4 -0.29507Riot/C%ita 0.45764 -0.07)23 0.89748 -0.01)10 ·"0.14381Deaths capita . 0.92782 -0.;6143 0.;7038 0.05002 ":'0.2,5426Attack/capita 0.83446 -0.09424 0.61079 0.212)4- -0.19937Sanction/capita 0•.51326 -0.2873.5 0.84870 0.16685 -0.14655
. Gov't Expenditure -0.0.54.59 -0.0;02; 0.05178 0.866;6 -0.02174Defense Expenditure 0.19732 -0.32139 -0.0)157 0.7207.5 -0.48620Internal Security Forces 0.1040.5 -0.• 07608 0.39135 0.69223 0.02088Press Freedom -0.221)4 0.89333 -0.02288 -0.19484- 0.13017Electoral Competition -0.270.59 0.83726 -0.04189 -0.02007 0.03736Power Distribution -0.)2830 0.88888 -0.07292 0.03303 • 0.068.50Freedom of Opposition -0.10891 0.87071 -0.07260 -0.16)4-7 -0.02465
NN\0
APPENDIX II. FACTOR ANALYSIS OF INDICATORS OF GOVERNHENTAL PERFORNA."'l"CE: OBLIQUE ROTATION
ke;'1 _ +1 chO:;ie!1 2S t..~e f1:12J. 1ndicator*$ used e.s CO::lilQocts of the 11:ldez
Pr1-nclpal Factor, No IteratIons Cblioce Rotation ~~+_~ KaIser ~o~lzatlon
concelt'..s 1:ldlcators Factor Patte:=n Factor S~r~ct~
cor.:::unality Factor I Factor II Fc.ctor I Factor II Factor I Factor II
Capacity to ~eet Co';ern:nental Expenditure 0.80 0.42 0.8) -0.07 0.9.5 O.2L• 0.9)iieEare De::ar.ds as %of GSPt-.... ......... .. ..... ....... .....•.......•....... ............ ..................... .......... . ., ... I .................
, I
..0.86 0.8) -0.42 0.98 .
P.esponslve~es~ ~ Social Insurance Index ..().25 0.90 0.07....elfare De:lall<1s
~oclal Sec~ty Benefit 0.93 0.96 -0.04 0.89 0.18 0.95 0.• 46S;:;pendi.tlL.""e $ per cap1ta*
,
Sc-::i2J. Securlty Benefit 0.81 0.93 -O.U 0.90 0.09 0.93 0.)8Ex:?e~diture as %Consunptlon ,
£~ndltare*
Ed~ca~lon2J. Expenditure $ 0.71 0.87 -0.14 0.86 0.06 0.88 0.))per capita*
Educat.ional Expenditure 0.61 0.68 0.)8 0.41 0.54 0.59 0.68%Q~P
-,..•••••.•.....•...•. ..........................•..•..••..•••...•••..••••.••.••.•.••. .. .......... ......... ... .. .......... ......
!::1senvalue . :;.87 1.04 factor correlation=.)2
re:rce:1~e of Va:d.azlce 64.6 11.'. .
Cr;::ulatlve Percentage 64.6 Bi.8.
APPENDIX III
PERSONAL INCOME DISTRIBUTION: DATA AND SOURCES
1. Data (0 = missing data)
Poorest Hidd1e Top 5%Country 40% share 40% share share Gini index
DEN 16.7 41.5 15.7 .3648FIN 11.1 39.6 21.0 .4674FRN 9.5 36.8 25.0 .5097GEW 15.4 31.2 33.7 .4604NTH 13.6 37.9 22.0 .4375NOR 16.6 42.9 15.4 .3588SWD 14.0 42.0 17.6 .4010UNK 18.8 42.0 15.0 .3305GRC 17.0 39.0 18.0 .3714SPN 17.0 37.8 20.0 .3856CAN 20.0 39.8 14.0 .3278USA 15.0 41.0 19.0 .3989AUL 20.1 41.2 14.3 .3154NEW 21.6 38.8 15.0 .3096AGR 17,,3 30.7 29.4 .4310BOL --12.9 28.0 35.7 0BRA 9.5 28.4 32.6 .5668CHL 13.0 30.2 30.4 .4961COL 7.3 25.8 40.4 .5458ECU 11.0 32.0 28.0 .5194PER 6.5 33.5 33.7 .5838URA 14.3 38.3 20.7 .4266VEN 9.7 32.3 26.5 .5385COS 14.7 34.7 22.8 .4398DOM 13.0 33.0 26.0 .4845ESL 12.3 26.3 33.0 .4632HON 7.3 25.2 36.0 .6211JAM 8.2 30.3 30.2 .5700MEX 10.5 25.5 36.0 .5707PAN 14.3 29.0 34.5 .5490TRI 9.4 33.6 26.6 0BDS 18.6 37.7 20.3 .3617PCO 13.7 35.7 22.0 .4486BUR 23.0 28.5 28.2 0CEY 18.0 37.1 19.0 .3671IND 13.1 33.7 25.0 .4720JAP 20.7 39.3 15.0 .3145KOS 18.0 37.0 17.0 .3686MAL 11.4 32.7 28.4 .5099PAK 18.8 37.4 18.5 .3539PHI 11.9 34.2 25.0 .4881TWN 14.0 33.8 25.7 .4614TAl 17.0 37.5 16.5 .3835IRN 12.5 33.0 26.0 .4822IRQ 6.8 25.2 34.0 .6220
Personal Income Distribution: Data and Sources (continued)
Poorest Middle Top 5%Country 40% share 40% share share Gini index
ISR 20.4 41.3 13.0 .3060LEB 13.0 26.0 34.0 .5259LBY .5 10.0 46.2 0SUD 15.0 36.9 17.1 .4410TUR 9.5 29.9 32.3 .5583UAR 14.0 39.0 19.6 .4241MaR 14.5 20.1 20.6 0TUN 11.4 33.6 24.5 .4999CHA 18.0 39.0 23.0 .3607DAB. 15.5 34.5 32.0 .4437GAB 9.8 23.7 45.0 .6205IVO 10.1 32.7 29.7 .5268KNY 12.0 35.5 21.2 .4769MDR 14.0 27.0 37.0 .5333NIR 23.0 35.0 23.0 0NIG 14.0 25.1 38.4 0SEN 10.0 26.0 36.0 .5760SIE 10.1 25.8 33.8 0SAF 6.2 35.8 27.6 .5733TAZ 14.0 29.0 31.0 .4902UGA 17.1 35.8 17.0 .3953ZBA 14.6 28.4 37.7 .4956
232
2. Year, Type of Population, Sample Coverage
country year type of population sample compiler
Denmark 1966 income recipient national 1
Finland 1962 " " 1
France 1962 household " 1
Germany(West)1964 income recipient " 1
Netherland 1967 " " 1
Norway 1963 " " 1
Sweden 1963 " " 1
U.K. 1968 household " 1
Greece 57/58 " urban 1
Spain 64/65 " national 1
Canada 1965 " " 1
U.S.A. 1966 " " 1Australia 67/68 " " 1New Zealand 1966 " " 1Argentina 1961 " " 1Bolivia 1968 " " 2
Bmzil 1970 " " 1Chile 1968 " " 1Columbia 1964 " " "2
Ecquador 1968 " urban 1Peru 70/71 economically active national 1
populationUruguay 1967 household " 1Venezuela 1962 " " 1Costa Rica 1971 " " 1Donimican Rep. 1967 " urban 1
(Santo Domingo)E1sa1vador 1965 " national 2
233
234
Honduras 67/68 household national 1
Jamaica 1958 " " 1Mexico 1969 " " 1
Panama 1969 " " 2
Trinidad & 1965 population " 2Tobago
Barbados 69/70 income recipient " 1Puerto Rico 1963 household " 1
Burma 1958 " estimated 2from urbandistribution
Ceylon 69/70 " nationaJ. 1(Sri Lanka)
India 67/68 " " 1
Japan 1963 " " 1
Korea 1970 " " 1f1alaysia 1970 " " 1
Pakistan 66/67 " " 1
Philippines 1971 " " 1
Taiwan 1961 " " 1
Thailand ~970 " urban 1
Iran 1968 " " 1Iraq 1956 population national 1Israel 1970 household urban 1Lebanon 55/60 " nation~,l 1Libya 1962 " urba..'P}. 2
Sudan 1969 " " 2(Omdurman)
Turkey 1968 " nationaJ. 1Egy.pt 64/65 " " 1
Morocco 1965 population " 2Tunisia 1970 income recipient " 1
Chad 1958 population " 1Dahomey 1959 " " 1
•
235
Gabon 1968 income recipient national 1
Ivory Coast 1970 II II 1
Kenya .68/69 household urban 1
Hadagascar 1960 II national 2
Niger 1960 population II 2
Nigeria 1959 II II 2
Senegal 1960 II " 1
Sierra Leone 1968 household " 2
South Africa 1965 population II 1
Tanzania 1967 household II 1
Uganda 1970 AIrican male employees II 1
Zambia 1959 household II 1
key: compiler 1: Shail Jain, "Size Distribution of Income:Compilation of Data," S..taff Working Paper, No.190(Nov., 1974), International Bank for Reconstruc-tion and Development. .
compiler 2: Irma Adelman and Cynthia T. Horris, EconomicGrowth and Social E uit in Deve10 in CountriesStanford: Stanford University Press, 1973 , p. 52.
..
236
3. Original Sources
Denmark: Statistike Efterretninger, 1967 (No. 16) and 1968 (no. 28).
Finland: Economic Commission for Europe, Economic Survey of Europe1965: Part 2: Incomes in Postwar Europe: A Study ofPolicies, Growth and Distribution (U.N. Publication SalesNo. 66, II.E.44), p. 15.
France: Ibid.
Germany(West): Ibid.
Netherlands: Statistical Yearbook of the Netherlands, 1971 (TheHague: Netherlands Central Bureau of Statistics, 1971),p. 285.
Norway: Economic Commission for Europe, .£p... cit.
Sweden: Ibid.
U.K.: Family Expenditure Surveys 60 and 68, U.K. Distributionof Households by Household Income.
Greece: National Statistical Service of Greece, Household SurveyCarried Out in the Urban Areas of Greece during 1957/58(Athens, 1961); quoted in ILO, Household Income andExpenditure Statistics, No.1, 1950-1964 (Geneva: 1967),p. 41.
Spain: Instituto Nacional de Estadistica, Encuesta de PresupuestosFamiliares, Marzo 1964 - Marzo 1965 (Madrid: 1969), p. 5.
Canada: Dominion Bureau of Statistics, "Historical Review onNon-Farm Income Distribution," Canadian StatisticalReview, vol. 44, No.8 (August, 1969), p. ii.
U.S.A. U.S. Bureau of the Census, Statistical Abstract of theUnited States: 1968, 89th edition (Washington, D.C.:1968), pp. 322-324.
Australia: N. Podder, "Distribution of Household Income in Australia,"Economic Record Vol. 48, No. 122 (June, 1972), pp. 187-188.
New Zealand: "A Note on the Relationship of Family Size and Income inNew Zealand," The Economic Record, Vol. 47, No. 119 (Sept.,1971), p. 404.
Argentina: U.N. Economic Commission for Latin America, EconomicDevelopment and Income Distribution in Argentina,Doc. No. E/CN. 12/802, UN Publications, Sales No. E.68.II.G.6 (New York: UN, 1969), pp. 53 and 83.
237
Bolivia: National Secretariat of Planning's Report for AID (1969).
Brazil: C. Langoni, Distribuicao de Rendae DesenvolvimentoEconomico do Brasil, Editora Expressao E Cultura(Rio De Janeiro, 1973), pp. 26, 64, 68, 70.
Chile: Economic Commission for Latin America, Metodos Analiticospara el Estudio de la Desigua1dad en la Distribuciondel Ingreso, ECLA/CPE/DRAFT 86 (1973), p. 34.
Columbia: William R. Cline, "Income Distribution Data forArgentina, Brazil, Chile, Columbia, Mexico, and Venezuela,"prepared for AID (1969); Gini index is taken from Departmento Nacional de Estadistica, Encuesta de Hogares dePropositos Multiples: Encuesta de Hogares 1970 (Bogota:Junio, 1971); National sample of 1970, Economicallyactive population.
Ecuador: Po1ivio Cordova, Analisis Econometrico de Distribucionde Ingreso, Departamento Administrativo Nacional deEstadistica (1972), p. 21.
Peru: Economic Commission in Latin America, Methodos Analiticospara e1 Estudio de la Desigua1aad en la Distribucion delIngreso, p. 34.
Uruguay: Instituto de Economia, Universidad de la Republica, "LaDistribucion del Ingreso en Uruguay," (Santiago, Chile:1971), pp. 99 and 155.
Venezuela: U.N. Economic and Social Council, Economic Commission forLatin America, Economic Survey of Latin America, 1968,Doc. E/cN. 12. 825, Rev. 1 (New York: U.N., 1969), p. 13.
Costa Rica: Victor H. Cespedes, Costa Rica: La Distribucion delIngreso Y el Consumo de Algunos Alimentos, Universidadde Costa Rica, Serie Economia y Estadistica, No. 45,pp. 53, 115, 116.
Dominican Rep.: Banco Central de la Rupulica Dominicana, Estudio SobrePresupuestos Familiares, I. Ingresos y Gastos de lasFamilias en la Cuidad de Santo Domingo, 1969, p. 128.
El Salvador: U.N., ECLA, Economic Survey of Latin America, 1969, p. 378;Gini index is drawn from Central American Common Market,"Informacion Basica de 1a Encuesta Socio-Cultural,"Socio Cultural Survey of INCAP (1965) as reported inShail Jain's paper (1969, population, National).
Honduras: Economic Commission for Latin America, MethodosAnaliticos para el Estudio de la Desigualdad en laDistribucion del Ingreso, p. 34.
Jamaica:
Mexico:
Panama:
Trinidad &Tobago:
Barbados:
238
A. Ahiram, "Income Distribution in Jamair.a, 1958,"in University of West Indies, Social and EconomicStudies, Vol. 13, No.3 (Sept., 1964), p. 337.
LB.R.D., "The Economy of Mexico: A Basic Report,"Report No. 192-ME, Vol. II (June, 1973), p. 91.
UN, ECLA, Economic Survey of Latin America, 1969,Fig. 37, p. 366;Gini index is drawn from Charles E. McLure, "TheDistribution of Income and Tax Incidence in Panama, 1969,"Working Paper No. 36 (Houston: Rice University), p. 25.(1969 Economically Active Population, National sample),which is reported by Shail Jain.
Nugent Miller, "Some Observations on the Income Distribution of Trinidad and Tobago," Income, Earnings ofIndividuals by Sex, In 1-1 (Trinidad and Tobago, continuous sample survey of population, No.6), pp. ix and 1.
Moon Hiwhoa, "Income Distribution in Barbados," unpublishedmimeo of Economic and Social Data Division of I.B.R.D.(1974), p. 3.
Puerto Rico: Richard Weisskoff, "Income Distribution and EconomicGrowth in Puerto Rico, Argentina and Mexico," The Reviewof Income and Wealth, Series 16, No.4 (Dec., 1970),pp. 312, 320.
Burma: Central Statistical and Economics Department, Governmentof the Union of Burma, "Report on the 1958 Survey ofHousehold Expenditure in Rangoon," as reported in Adelmanand Morris, .2E.. cit., p. 152.
Ceylon (Sri Lanka): Department and Census and Statistics, PreliminaryReport on the Socio-Economic Survey of Ceylon 1969-70(1971), p. 50.
India: National Council of Applied Economic Research, All IndiaHousehold Survey of Income, Savings and Consumer Expenditure (with Special Reference to Middle Class Households)(New Delhi: 1971), p. 26.
Japan: Harry T. Oshima, "Income Inequality and Economic Growth:The Postwar Experience of Asian Countries," MalayanEconomic Review, Vol. 15, No.2 (Oct., 1970), p. 13.
Korea: Bureau of Statistics, Economic Planning Board, AnnualReport on the Family Income and Expenditure Survey 1970:Report on the Results of Farm Household Economic Surveyof Agricultural Products, 1971, pp. 56-65.
Malaysia:
Pakistan:
Philippines:
Taiwan:
Thailand:
Iran:
Iraq:
Israel:
Lebanon:
Libya:
Sudan:
Turkey:
Egypt:
239
computed from the Data of Post Enumeration Survey of 1970.
Central Statistical Office, Economic Coordination andExternal Assistance Division, Government of Pakistan,Report on the Quarterly Survey of Current EconomicConditions in Pakistan (Household Income and Expenditure)July 1966 to 1967, pp. 97-105; 223-231.
Republic of the Philippines, Department of Commerce andIndustry, Bureau of Census and Statistics, Family Incomeand Expenditure, 1971, BCS Survey of Households Bulletin,p. 151.
Working Group of National Income Statistics DirectorateGeneral of Budget, Account and Statistics, The ExecutiveYuan, Report on Pilot Study of Personal Income andConsumption in Taiwan, pp. 12-13.
Economic Survey of Asia and the Far East, 1971, UNPublication Sales No. E. 72.II.Fl, Table 1-3-8, p. 59.
A. S. Jaffe, "Notes of Family.lncome Distribution inDeveloping Countries in Relation to Population andEconomic Changes, 1969," (mimeo report).
Christian Morrisson, La Repartition des Revenus Dansles pays du Tiers Monde (Paris: Editions Cujas, 1969),p. 205.
Report on the Committee on Income Distribution and SocialInequality, (Tel Aviv: 1971), p. 48.
Christian Morrisson, ~. cit., p. 205.
Sami W. Dajani, "Family Budget Survey in Tripoli Town,1962," National Economy Central Statistics Office,Tripoli, Libya.
"Omdurman Household Budget Survey," Republic of Sudan,Department of Statistics, p. 24. Gini index represents1963 data, and drawn from the same survey conducted in1965.
Tuncer Bulutay, Serim, Timur and Hasam, Ersel, Turkiye'deGelir Oagilimi (Ankara: 1971), p. 23, Table 1.lA.
Mostafa H. Nagi, Labor Force and Employment in Egypt:A Demographic and Socioeconomic Analysis (Praeger: 1971),p. 134.
Morroco:
Tunisia:
Chad:
Dahomey:
Gabon:
Ivory Coast:
Kenya:
Madagascar:
Niger:
Nigerria:
Senegal:
Sierra Leone:
South Africa:
Tanzania:
Uganda:
Zambia:
240
Abderrazaq,"Les Sa1aires dans 1e Revenu National de1955 a 1966," Bulletin economique et social du Maroc,19, Nos. 106-7 (1967).
Christian Morrisson, "Tunisia" unpublished mimeo ofIncome Distribution Division, IBRD, p. 25.
Christian Morrisson, La Repartition des Revenus dansLes Pays du Tiers Monde (£E.. cit.), pp. 194-205.
Loc. cit.-- --Christian Morrisson, "Gabon," unpublished memo of IncomeDistribution Division, IBRD, p. 15.
Christian Morrisson, "Ivory Coast," (memo), pp. 17-18.
International Labor Office, Employment, Income andEquality: A Strategy for Increasing ProductiveEmplOyment in Kenya (Geneva: 1972), p. 72.
Morrisson, La Repartition des Revenus dans Les Pays duTiers Monde, pp. 159, 204. Gini index is taken fromShai1 Jain's report (population is the base).
Morrisson, £E.. cit., pp. 194, 204.
J. Marchal and B. Ducros, The Distribution of NationalIncome (New York: St. Martin, 1968).
Morrisson, £E.. cit., p. 205.
"Sierra Leone Household Survey," African Research Bulletin:(Feb., 1968), p. 917.
estimated by IBRD from various sources.
Morrisson, "Tanzania," paper prepared for IBRD, 1972,p. A-7.
completed from Enumeration of Employees, 1961-70,Uganda Government Printer, Entebbe, as quoted in,"Employment and Income Distribution in Uganda,"University of East Ang1ia, Table d and t (iii), pp. 6, 53.
R. E. Baldwin, Economic Development and Export Growth:A Study of Northern Rhodesia, 1920-60 (Berkeley:University of California Press, 1966), p. 46.
REFERENCES CITED
Books
Adelman, Irma and Cynthia T. Morris. Economic Growth and Social Equityin Developing Countries. Stanford: Stanford University Press, 1973.
Almond, Gabriel A. and James S. Coleman, eds., The Politics 0 f theDeveloping Areas. Princeton: Princeton University Press, 1960.
Asher, Herbert B. Causal Mode1~ng. Beverly Hills: Sage UniversityPaper, Series No. 07-003, 1976.
Bachrach, Peter and Morton S. Baratz. Power and Poverty: Theory andPractice. New York: Oxford University Press, 1970.
Bay, Christian. The Structure of Freedom. Stanford: StanfordUniversity Press, 1965.
Blalock, Hubert H.Chapel Hill:
Causal Inferences in Non-Experimental Research.University of North Carolina Press, 1964.
Brinton, Crane. The Anatomy of Revolution. New York: Vintage, 1965.
Camus, Albert. The Rebel. New York: Vintage Books, 1956.
Chadwick, Richard W. Developments in a Partial Theory of InternationalBehavior: A Test and Extension of Inter-Nation Simulation Theory.Ph.D. Thesis, Northwestern University, 1966.
Chenery, Hollis, et a1., Redistribution with Growth. London: OxfordUniversity Press, 1974.
Cockcroft, James D., Andre Gunder Frank, and Dale L. Johnson.and Underdevelopment: Latin America's Political Economy.Anchor Books, 1972.
DependenceNew York:
Coser, Lewis A. The Function of Social Conflict. New York: Free Press,1956.
Dahl, Robert A. Preface to Democratic Theory. Chicago: Universityof Chicago Press, 1956.
~ahl, Robert A. Who Governs? New Haven: Yale University Press, 1961.
Dahrendorf, Ra1f. Class and Class Conflict in Industrial Society.Stanford: Stanford University Press, 1959.
242
Dahrendorf, Ralf. Essays in the Theory of Society. Stanford: StanfordUniversity Press, 1968.
Dunlop, John J., Frederick H. Harbison, and Charles A. Myers. Industrialism and Industrial Man: The Problems of Labor and Management in Economic Growth. Cambridge: Harvard University Press,1960.
Easton, David. The Political System. New York: Alfred A. Knopf, 1953.
Ellul, J. The Technological Society. New York: Vintage, 1967.
Fanon, Franz. The Wretched of the Earth. New York: Glove Press, 1966.
Fogelson, Robert M. Violence as Protest: A Study of Riots and Ghettos.New York: Doubleday, 1971.
Gans, Herbert J. More Equality. New York: Pantheon Books, 1973.
Goulet, Denis. The Cruel Choice: A New Concept in the Theory ofDevelopment. New York: Atheneum, 1973.
Goulet, Denis. World Interdependence: Verbal Smokescreen or New Ethic?Washington: Overseas Development Council, 1976.
Gurr, Ted Robert. Po1imetrics: An Introduction to QuantitativeMacropo1ities. Englewood Cliffs: Prentice-Hall, 1972.
Gurr, Ted Robert. Why Men Rebel? Princeton: Princeton UniversityPress, 1970.
Haas, Michael. International Conflict. Indianapolis: Bobbs-Merri11,1974.
Hei1broner, Robert L. The Great Ascent: The Struggle for EconomicDevelopment in Our Time. New York: Harper & Row, 1963.
Heinz, Peter. The Future of Development. Switzerland: Hans HuberPublishers, 1973.
Hibbs, Douglas A., Jr. Mass Political Violence: A Cross-National CausalAnalysis. New York: John Wiley & Sons, 1973.
Hirschman, Albert. The Strategy of Economic Development. New Haven:Yale University Press, 1958.
Horowitz, Irving Louis. Three Worlds of Development: The Theory andPractice of International Stratification. New York: OxfordUniversity Press, 1966.
Hudson, Michael C. Conditions of Political Violence and Instability:A Preliminary Test of Three Hypotheses. Beverly Hills: SageProfessional Papers in Comparative Politics, Series No. 01-005,1970.
243
Huntington, Samuel P. 'Po1itica1 Order in Changing Society. New Haven:Yale University Pr~~3, 1968.
Jackman, Rovert W. Politics and Social Equality: A Comparative Analysis.New York: John Wiley, 1975.
Jacob, Philip E. et al. Values and the Active Connnunity: A CrossNational Study of the Inf luence of Local Leadership. New York:Free Press, 1971.
Kerlinger, Fred N. and E. J. Pedhazur. Multiple Regression inBehavioral Research. New York: Holt, Rinehart & Winston, 1973.
Kornhauser, William. The Politics of Mass Society. New York: TheFree Press, 1959.
Lasswell, Harold. Politics: Who Gets What, When, and How'? Cleveland:World Publishing Co., 1958.
Lenski, Gerhard. Power and Privilege: A Theory of Social Stratification.New York: McGraw-Hill, 1966.
Lipset, Seymour M. Political Man: The Social Bases of Politics. NewYork: Anchor Books, 1963.
Mills, C. Wright. The Power Elite. New York: Oxford UniversityPress, 1956.
Moore, Barrington, Jr. Social Origins of Dictatorship and Democracy:Lord and Peasant in the Making of the Modern World. Boston:Beacon Press, 1966.
Myrda1, Gunnar. Asian Drama: An Inquiry into the Poverty of Nations.New York: Pantheon Books, 1968.
Myrda1, Gunnar. Economic Theory and Under-Developed Regions. London:Gerald Duckworth & Co., 1957.
Myrda1, Gunnar. The Challenge of World Poverty: A World Anti-PovertyProgram in Outline. New York: Pantheon Books, 1970.
Nie, Norman H. et a1.Second Edition.
SPSS: Statistical Package for the Social Science.New York: McGraw-Hill, 1970.
Okun, Arthur M. Equality and Efficiency. Washington, D.C.: TheBrookings Institution, 1975.
Olson, Mancur. The Logic of Collective Action: Public Goods and theTheory of Groups. Cambridge: Harvard University Press, 1965.
Parsons, Talcott. The Social System. New York: Free Press, 1951.
244
Popper, Karl R. Conjectures and Refutations. New York: Harper Torchbooks, 1968.
Popper, Karl R. The Logic of Scientific Discovery. New York: BasicBoos, 1959.
Prebisch, Raul. The Economic Development of Latin America and ItsPrincipal Problems. New York: United Nations, 1950.
Prezeworski, Adam and Henry Teune. The Logic of Comparative SocialInquiry. New York: John Wiley, 1970.
Roszak, T. The Making of a Counter Culture. New York: Anchor, 1969.
Rummel, R. J. Applied Factor Analysis. Evanston: NorthwesternUniversity Press, 1970.
Rummel, R. J. The Dimensions of Nations. Beverly Hills: SagePublications, 1972.
Sharp, Gene. The Politics of Nonviolent Action. Boston: Porter SargentPublishers, 1973.
Simmel, Georg. Conflict and the Web of Group Affiliations. Translatedby K. Wolff and R. Bendix. New York: Free Press, 1955.
Stauffer, Robert B. National-Building in a Global_~_conomy: The Roleof the Multi-National Corporations. Beverly Hills: Sage ProfessionalPaper on Comparative Politics, Series No. 01-039, 1973.
Stauffer, Robert B. The Philippine Congress: Causes of StructuralChange. Beverly Hills: Sage Research Papers in the SocialSciences, Series No. 90-024, 1975.
Stinchcombe, Arthur L. Constructing Social Theories. New York: Harcourt,Brace &World, 1968.
Tochqueville, Alexis de. The Old Regime and the French Revolution.New York: Doubleday, 1955.
Touraine, Alain. The Post-Industrial Society. Translated by LeonardF. X. Mayhew. New York: Random House, 1971.
Weber, Max. The Theory of Social and Economic Organizations. Translatedby Talcott Parsons. New York: Free Press, 1947.
Articles
Ahluwalia, Montek S. "Income Inequality: Some Dimensions of the Problem,"in Hollis Chener¥., eS al., Redistribution with Growth. London:University of Oxford Press, 1974, pp. 3-37.
245
Alker ~ Hayward R., Jr. and Bruce M. Russett. "Indices for ComparingInequa1ity~" in Richard L. Merritt and Stein Rokkan~ eds.COmparing Nations: The Use of Quantitative Data in Cross-NationalResearch. New Haven: Yale University Press~ 1966~ pp. 349-372.
Bachrach~ Peter. "A Power Analysis: The Shaping of Antipoverty Policyin Baltimore," in Public Po1icy~ Vol. 8, No. 2 (Winter~ 1970) ~
pp. 155-186.
B1alock~ Hubert M., Jr. "A Causal Approach to Non-Random MeasurementError," American Political Sc ience Review ~ Vol. 64 ~ No. 4 (Dec. ~
1970)~ pp. 1099-1111.
B1a1ock~ Hubert M., Jr. "Causal Inference~ Closed Popu1ation~ andMeasures of Association~" American Political Science Review~
Vol. LXI~ No. 1 (March~ 1967)~ pp. 130-136.
B1a1ock~ Hubert M. ~ Jr. "Correlated Independent Variables: The Problemof Multicollinearity ~" Social Forces ~ 62 (Dec. ~ 1963) ~ pp. 233-237.
B1a1ock~ Hubert M., Jr. "Theory Building and Causal Inferences ~" inH. M. Blalock and A. B. Blalock~ eds., Methodology in SocialResearch. New York: McGraw-Hi11~ 1968, pp. 155-198.
Caparoso~ James. "Methodological Issues in the Measurement of Inequality:Dependence and Exploitation~" in S. J. Rosen and J. R. Kurth~ eds. ~
Testing Theories of Economic Imperialism. Lexington: D. C. Heath~
1974~ pp. 87-114.
Carlin~ Jerome E. ~ Jan Howard and Sheldon L. Messinger. "Civil Justiceand Poor: Issues for Sociological Research~" in Law & SocietyReview~ Vol. 1~ No. 1 (Nov.~ 1966), pp. 9-89.
Chadwick, Richard W. "An Empirical Test of Five Assumptions in anInter-Nation Simulation about National Political System." GeneralSystems~ Vol. XII (1967)~ pp. 177-192.
Chalmers~ Douglas A. "Developing the Periphery: External Factors inLatin American Po1itics~" in James Rosenau~ ed.~ Linkage Politics:Essays on the Convergence of National and International Systems.New York: The Free Press~ 1969~ pp. 67-93.
Clark, Kenneth B. "The Invisible Wall," in Peter Co1lier~ cd., Crisis:A Contemporary Reader. New York: Harcourt~ Brace & Wor1d~ 1969~
pp. 48-57.
Cnudde~ Charles E. and D. E. Neubauer. "New Trends in Democratic Theory~"
in Cnudde and Neubauer~ eds.~ Empirical Democratic Theory. Chicago:Markham Publishing Co.~ 1969~ pp. 511-533.
Cohen~ Jacob. "Multiple Regression as a General Data-Analytic System~"
in Psychological Bu11etin~ Vol. 70, No. 6 (1968)~ pp. 426-443.
246
Cutright, Phillips. "National Political Development: Measurement andAnalysis," American Sociological Review, Vol. 28, No. 2 (April,1963), pp. 253-264.
Davies, James C. "Toward a Theory of Revolution," American SociologicalReview, Vol. 27, No.1 (February, 1962), pp. 5-19.
Davis, Kingsley and Wilbert E. Moore. "Some Principles of Stratification,"American Sociological Review, Vol. 10, No.2 (April, 1945), pp.242-249.
Deutsch, Karl W. "On Inequality and Limited Growth," InternationalStudies Quarterly, Vol. 19, No.4 (Dec., 1975), pp. 381-398.
Deutsch, Karl W. "Social Mobilization and Political Development,"American Political Science Review, Vol. LV, No.3 (Sept., 1961),pp. 493-514, reprinted in Jason L. Finkle and Richard W. Gable,eds., Political Development and Social Change, 2nd Edition. NewYork: John Wiley & Sons, 1971, pp. 385-386.
Duncan, Otis Dudley. "Path Analysis: Sociological Examples," AmericanJournal of Sociology, Vol. 72, no. 1 (July, 1966), pp. 1-16,reprinted in Blalock, ed., Causal Models in the Social Sciences.Chicago: Aldine-Atherton, 1971, pp. 115-138.
Farrar, Donald E. and R. R. Glauber. "Multicollinearity in RegressionAnalysis: The Problem Revised," in Review of Economics andStatistics, Vol. XLIV, No.1 (Feb., 1967), pp. 92-107.
Feierabend, Ivo K., Rosalind L. Feierabend, and Betty A. Nesvold."Social Change and Political Violence: Cross-National Patterns,"in Hugh Davis Graham and Ted Robert Gurr, eds., Violence in America:Historical and Comparative Perspective. New York: The New AmericanLibrary, 1969, pp. 606-668.
Flanigan, William H. and Edwin Fogelman. "Patterns of Political Violencein Comparative Historical Perspective," Comparative Politics, Vol. 3,No.1 (Nov., 1970), pp. 1-20.
Galtung, Johan. "A Structural Theory of Imperialism," Journal of PeaceResearch, Vol. 7, No.2 (1971), pp. 81-118.
Gamson, William A. "Violence and Political Power: the Meek Don't MakeIt," Psychology Today (July, 1974), pp. 35-41.
Gannage, Elias. "The Distribution of Income in Underdeveloped Countries,"in Jean Marchal and Bernard Ducros, eds., The Distribution ofNational Income: Proceedings of a Conference held by InternationalEconomic Association. New York: St. Martin's Press, 1968, pp. 326360.
247
~iaas, Michael. "Dimensional Analysis in Cross-National Research,"Comparative Political Studies, Vol. 3, No.1 (April, 1970),pp. 3-35.
Hempel, Carl G. "Explanatory Incompleteness," in May Brodbeck, ed.,Readings in the Philosophy of the Social Sciences. New York:McMillan, 1968, pp. 398-415.
Horwitz, Hortense and Elias Smith. "The Interchangeability of SocioEconomic Indices," in Paul F. Lazarsfeld and Morris Rosenberg, eds.,The Language of Social Research. New York: Free Press, 1955,pp. 73-77.
Huntington, Samuel P. "Political Development and Political Decay,"World Politics, 17 (April, 1965), pp. 386-430.
Lasch, Christopher. "Toward a Theory of Post-Industrial Society," inM. Donald Hancock and Gideon Sjoberg, eds., Politics in Post-WelfareState. New York: Columbia University Press, 1972, pp. 36-50.
McCrone, D. J. and C. F. Cnudde. "Toward a Connnunication Theory ofDemocratic Political Development: A Causal Model," AmericanPolitical Science Review, Vol. LXI, No.1 (March, 1967), pp. 72-79.
Merkx, Gilbert W. "Economics and History in the Study of Rebellions:The Aagentine Case," in Garry D. Brewer and Ronald D. Brunner, eds.,Political Development and Change: A Policy Approach. New York:The Free Press, 1975, pp. 103-127.
Morgan, James. "The Anatomy of Income Distribution." The Review ofEconomics and Statistics, Vol. XLIV, No.3 (Aug., 1962), pp. 270282.
Neubauer, Deane E. "Some Conditions of Democracy." American PoliticalScience Review, Vol. LXI, No.4 (Dec., 1967), pp. 1002-1009.
Nie, N. H., G. B. Powell, Jr., and K. Prewitt. "Social Structure andPolitical Participation: Developmental Relationship." AmericanPolitical Science Review, Vol. 63 (June, 1969), pp. 361-378 andVol. 63 (Sept., 1969), pp. 808-832.
Olson, Mancur, Jr. "Rapid Growth as a Destablizing Force," Journalof Economic History, Vol. XXIII, No.4 (Dec., 1963), pp. 529-552.
Rummel, R. J. "Dimensions of Conflict Behavior within and betweenNations," General Systems Yearbook, Vol. 8 (1963), pp. 1-50.
Rummel, R. J. "Some Empirical Findings on Nations and their Behavior,"World Politics, Vol. 21-, No.2 (Jan., 1969), pp. 226-241.
248
Stauffer, Robert B. "Great Power Constraints on Political Development,"Studies in Comparative International Development, Vol. VI, No. 11(1970-1971), pp. 231-251.
Stauffer, R. B. "Philippine Authoritarianism: Framework forPeripheral Development," unpublished mimeo., University of Hawaii,1977 •
Stauffer, R. B. "The Political Economy of a Coup: Transnational Linkageand Philippine Political Response," Journal of Peace Research,Vol. 11, No.3 (1974), pp. 161-177.
Thurow, Lester. "Toward a Definition of Economic Just ice. " The PublicInterest, No. 31 (Spring, 1973), pp. 56-80.
Zolberg, Aristide R. "The Structure of Political Conflict in the NewStates of Tropical Africa," American Political Science Review,Vol. LXII, No.1 (March, 1968), pp. 70-87.
Data Sources
Adelman and Morris, .2£.. cit.
Ahluwalia, .2£.. cit.
Benjamin, Roger W. and John H. Kautsky. "Communism and EconomicDevelopment," American Political Science Review, Vol. LXII, No. 1(March, 1968), pp. 110-123.
Cutwright, Philips. "Political Structure, Economic Development andNational Social Security Programs," American Journal of Sociology,Vol. LXX, No.5 (March, 1965), pp. 537-550.
F.A.O. and I.L.O. Progress in Land Reform. New York: United Nations,1970.
Jackman, .2.P.. cit.
Jain, Shail. "Size Distribution of Income: Compilation of Data,"Staff Working Paper No. 190 (Nov., 1974), International Bank forReconstruction and Development.
Kuznets, Simon•. "Quantitative Aspects of the Economic Growth of Nations(VIII): Distribution of Income by Size," Econ9mic Development andCultural Change (Jan., 1963).
Runnnel, R. J., et al. Attribute of Nations: Data and Codes 1950-1965,The Dimensionality of Nations Project, Research Report No. 65,Honolulu, 1973.
249
Banks, Arthur S. Cross-Polity Time Series Data. Cambridge: The MITPress, 1971.
Russet, Bruce M. "Inequality and Instability: The Relationship ofLand Tenure to Politics," in Robert A. Dahl and Deane E. Neubauer,eds., Readings in Modern Political Analysis. Englewood Cliffs:Prentice-Hall, 1968.
Russet, Bruce M. et al. World Handbook of Political and Social Indicators.New Haven: Yale University Press, 1964.
Taylor, Charles L. and Michael C. Hudson, second ed., World Handbook ofPolitical and Social Indicators. New Haven: Yale University Press,1972.
U.N., Department of Economic and Social Affairs. Social Policy and theDistribution of Income in the Nations. New York: United Nations,1969.
U.N. 1967 Report on the World Social Situation. New York: UnitedNations, 1968.
U.N., Department of Economic and Social Affairs. 1970 Report on theWorld Social Situation. New York: United Nations, 1971.
U.N., Economic Commission for Latin America. Economic Bulletin forLatin America. New York: United Nations, 1969.
U.N., I.L.O. The Cost of Social Security: 6th International Inquiry,1960-1963, Geneva, 1967.
United States, Department of Health, Education, and Welfare, SocialSecurity Administration. Social Security Programs Throughout theWorld 1973. Washington: United States Government Printing Office,1973.
Walleri, Robert D. The Political Economy of International Inequality:A Test of Dependency Theory, Ph.D. Dissertation in PoliticalScience, University of Hawaii, 1976.
A more comprehensive list of sources on income distribution data usedin this study is reported in Appendix III.