DETERMINANTS OF ECONOMIC CORRUPTION:A CROSS-COUNTRY COMPARISONAbdiweli M. Ali and Hodan Said Isse

In recent years, the detrimental effects of bureaucratic corruptiongained attention from development economists as well as interna-tional financial institutions and policymakers. Corruption, which waspreviously ignored and mentioned only with caution, has taken acenter stage. Nonetheless, corruption is not a new phenomenon. It isas old as government itself. The current literature on corruption high-lights its harmful effects on growth (see Klitgaard 1988, Shleifer andVishny 1993, Mauro 1995, Cheung 1996, and Bardhan 1997). How-ever, until recently the growth literature did not adequately explainwhy corruption is low in some countries and endemic in others.1 Therelevant analytical problem is not to assess the harmfulness of cor-ruption but why different political systems foster different levels ofcorruption. We cannot discern any useful prognosis from the litera-ture on corruption so long as the causes of corruption are not clearlyidentified. Moreover, the empirical studies on the effects of corrup-tion on economic growth are besieged by endogeneity problems. Fewof these empirical studies take into account the possibility that eco-nomic growth or the lack of it can increase or decrease the level ofcorruption.

This article seeks to fill that gap by identifying the determinants ofcorruption and by examining the extent to which those factorssuchas education, political regimes, the type of the state, ethnicity, judicial

Cato Journal, Vol. 22, No. 3 (Winter 2003). Copyright Cato Institute. All rightsreserved.

Abdiweli M. Ali and Hodan Said Isse are economists with the Commonwealth of Virginia andthe Beydan Institute for Research and Development. They thank W. Mark Crain, GarethDavis, Bill Peach, and G. Chris Rodrigo for helpful comments.

1The new empirical research on the determinants of corruption attempts to determine thecauses of corruption and concentrates mostly on cross-country analyses. See, for example,the studies by Ades and DiTella (1997); LaPorta et al. (1997); Treisman (1999a, 1999b);Fisman and Gatti (1999); and Swamy et al. (2001).

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efficiency, political freedom, and the size of governmentexplaindifferences in corruption across countries. When the determinants ofcorruption are clearly identified, appropriate policy conclusions canthen be drawn from the analysis, and policymakers can then designand implement measures to curb and control its harmful effects.

Alternative Views of CorruptionThe prevailing view is that corruption is harmful to economic

growth. Mauro (1995) finds that corruption lowers investment and,consequently, economic growth. Using data from a large sample ofcountries, he finds that corruption, red tape, and bureaucratic inef-ficiency are negatively correlated with economic growth. Klitgaard(1988) suggests that when political power translates corruptly intoeconomic gains, corruption redistributes resources from the poor tothe rich and encourages malfeasance and rent seeking. In corruptsocieties, government bureaucrats compete for positions of economicpower and spend their time and energy in the pursuit of rents. Thisrent-seeking activity, in turn, affects the capacity of public institutionsto provide services.2

Corruption adversely distorts incentives and creates uncertaintiesabout the expected benefits of productive activities, forcing entrepre-neurs to undertake costly and inefficient loss-avoiding behaviors.Shleifer and Vishny (1993) suggest that corruption is a tax on eco-nomic activity that is more costly than legal taxes. Unlike taxation,corruption is illegal and real resources are wasted to avoid detection.The need to keep the transactions secret directs resources to hard-to-detect activities with no regard for economic consequences.

Contrary to this prevailing view that corruption is harmful to eco-nomic development, some studies suggest that it might be beneficialand enhance efficiency.3 Leff (1964) long ago proffered that corrup-tion circumvents inefficient and cumbersome government regula-tions. He argues that corruption mitigates the distortionary effects ofgovernment policies and allows entrepreneurs to avoid bureaucraticdelays. A direct payment to corrupt officials reduces the transactions

2For a detailed description of the harmful effects of rent seeking, see Krueger (1974),Buchanan, Tullock, and Tollison (1980), and Bhagwati (1982).3Countries like Thailand and South Korea may have been riddled with graft; their econo-mies powered ahead regardless. Italys corruption did not stop it from drawing level withrelatively virtuous Britain in GDP per head. And, in states which suppressed the normalworkings of the market, bribery could sometimes seem to be a blessing; it could releasegoods trapped at the border by a corrupt customs officer, or set a price for a service thegovernment had foolishly offered for free (The Economist, 1999: 50).

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cost of business and energizes corrupt civil servants who would haveotherwise engaged in delaying tactics.4 Leff also claims that corrup-tion generates a social benefit and serves as a mechanism for politicalparticipation and influence for minorities and foreign corporations.Leff (1979: 328) remarks: In most underdeveloped countries, inter-est groups are weak, and political parties rarely permit the participa-tion of elements outside the contending cliques. Consequently, graftmay be the only institution allowing other interests to achieve articu-lation and representation in the political process.

Scott (1972) also argued that what is considered corruption in theWest is in fact a continuation of traditional gift giving in less devel-oped countries (LDCs). The imposition of Western values and atti-tudes has transformed this traditional gift exchange in LDCs intocorruption. Tullock (1996) also claims that illicit payments are a sub-stitute for higher wages. Corruption therefore saves money for thegovernment that it would have otherwise paid in higher salaries. Lui(1996) makes the case that what some people call corruption is noth-ing but a fee for underpriced services. He suggests that corruptionrestores the price mechanism and improves the allocation of re-sources in distorted and heavily regulated markets.

Reassessing the Relationship between Corruptionand Economic Growth

Table 1 is a correlation matrix of the regression variables presumedto affect economic growth. A detailed description of the data is in theAppendix. The correlation coefficient for the relation between cor-ruption in the 1980s and the 1990s is 0.73, showing that corruptionwas persistent over the years. Those countries with high levels ofcorruption in the 1980s continued to have high levels of corruption inthe 1990s. Corruption breeds corruption, and the longer it persiststhe more endemic it becomes. Table 2 provides descriptive statisticsfor the regression variables. The mean and the median of corruptionin the 1990s are higher than those of the 1980s. However, there is noconclusive evidence that corruption has increased worldwide in1990s. The corruption indexes for the 1980s and 1990s were providedby different organizations. They cover different samples, and thenature and content of the survey questions might have been quitedifferent.

4The fact that corruption is pervasive in low-growth countries of Africa and Latin Americacontradicts these arguments. Actually, bribery gives corrupt bureaucrats an incentive tocreate more red tape to extract bigger bribes and to extort more payments for the provisionof their services.

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Table 3 summarizes the empirical results employing the followingcore equation:

(1) Growth = 0 + 1(initial GDP) + 2(population growth)+ 3(education) + 5(other variables of interest) + .

The control variables are standard in the literature.5 They are theinitial GDP level, the secondary school enrollment rate, and thepopulation growth rate. Table 3 also includes dummy variables forAfrica and Latin America to account for continent-specific character-istics.

In Model 1 of Table 3, the corruption index for the 1980s is addedto the above specification as an additional variable of interest. Thecoefficient of corruption is negative and highly significant when othercorrelates of growth are included in the regression equation. How-ever, the prevalence of corruption can be a by-product of economicgrowth as well as its cause. The possibility of corruption being afunction of economic growth creates an endogeneity problem. Thereis a plausible argument that lower economic growth could lead tohigher corruption or higher corruption could lead to lower growthrate. Model 2 examines this potential bias using a two-stage least-squares approach. To correct for endogeneity, we used ethnolinguis-tic fractionalization as an instrumental variable; a measure of ethno-linguistic fragmentation.6 The fractionalization index is frequentlyused in the growth literature and measures the probability that tworandomly selected persons from a given country will not belong to thesame ethnolinguistic group (Easterly and Levine 1997, Mauro 1995).The higher the index the more heterogeneous and fragmented thesociety and the lower the probability that economic agents are treatedequally and fairly.

Ethnolinguistic fractionalization is not correlated to economicgrowth but is significantly and negatively correlated with corruption.As shown in Table 1, the simple correlation coefficient between cor-ruption in the 1980s and ethnolinguistic fractionalization is 0.61,while the correlation between corruption in the 1990s and ethnolin-guistic fractionalization is 0.63. The estimated results in Model 2

5For a detailed discussion of the control variables, see Levine and Renelt (1992) and Barro(1996).6In addition to ethnolinguistic fractionalization, we used other measures of ethnic frag-mentation. These include the percent of population not speaking the official language, thepercent of population not speaking the most widely used language, and the probability thattwo randomly selected individuals speak different languages. For a further description ofthose variables, see Easterly and Levine (1997).

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indicate that corruption has a substantial explanatory power for eco-nomic growth. The results in Model 2 suggest that the observednegative correlation between corruption and economic growth mightbe the consequence of higher corruption causing lower economicgrowth rather than lower growth rates leading to higher levels ofcorruption. This confirms Mauros results that corruption causeslower economic growth and not vice versa. However, when we rees-timated the regression equation using other measures of ethnic frag-mentation the results are not conclusive. The inconclusiveness is dueto the smallness of the sample size of these other measures of ethnicfragmentation. The data on other measures of ethnic fragmentationare available only for 38 countries. Angrist and Krueger (2001) sug-gest that researchers using instrumental variables should work withlarge samples since instrumental variables are consistent but not un-biased.

The idea that causation might go in both directions is still plausibleand more evidence might be required to come to a firm conclusion.If countries with lower corruption levels grew faster, this positiveexperience might lead them to fight corruption even more in thefuture. Therefore, economic growth in one period should be nega-tively correlated with corruption in the future. Following Gwartney,Lawson, and Holcombe (1999), Model 3 tests that proposition usingthe average annual growth rate from 1975 to 1985 as the dependentvariable. The model includes all the independent variables in Model1, with corruption in the 1990s replacing corruption in the 1980s as anadditional explanatory variable. If economic growth is correlated withfuture corruption, this variable is expected to be negative and statis-tically significant.7 The coefficient of corruption in the 1990s is notstatistically significant. The lack of correlation between economicgrowth from 1975 to 1985 and corruption in the 1990s suggests thathigher economic growth does not guarantee a lower corruption in thefuture. The possibility that high-growth countries will exhibit lowerlevels of corruption partly as a result of becoming richer is not sup-ported by the empirical results. However, if corruption is a by-product of economic growth as well as its cause, it would be quiteprudent not to attribute too much significance to economic growth inthe 1980s or the 1970s as a causal factor for corruption in the 1990s.

Models 4 and 5 provide further evidence about the cause and effectrelationship between corruption and economic growth. It runs a re-

7Gwartney, Lawson, and Holcombe (1999) used this method to evaluate the effect ofeconomic freedom on growth.

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gression with an annual growth rate from 1990 to 1995 as the depen-dent variable and corruption in the 1980s as the only independentvariable. The coefficient of corruption in the 1980s is 0.67 and ishighly significant, which indicates a strong negative correlation be-tween corruption in an earlier period and the GDP growth rate in alater period. When the regression is reversed, and corruption in the1990s becomes the dependent variable and GDP growth rate from1975 to 1985 as the sole independent variable, the coefficient of GDPgrowth rate is negative but statistically insignificant.

The empirical results in Models 4 and 5 indicate that higher cor-ruption leads to lower economic growth but economic growth has noeffect on future corruption. This finding suggests that economicgrowth by itself will not lead to lower corruption. It also indicates thatfighting corruption needs clear and explicit policy measures. For eco-nomic growth to take place, an environment less conducive to cor-ruption and malfeasance should be a priority.

Model 6 investigates the possibility that corruption affects eco-nomic growth indirectly through the investment channel. The cor-ruption coefficient is negative and statistically insignificant when theratio of investment to GDP is used as the dependent variable. Thisresult contradicts Mauros findings that corruption is a tax on capitalinvestment. Campos, Lien, and Pradhan (1999) and Wedeman (1996)found similar results and suggested some possible explanations.Wedeman (1996) argues that while correlation between corruptionand the ratio of investment to GDP might be strong for some coun-tries with little corruption, it loses its statistical significance for coun-tries with higher levels of corruption. Therefore, certain kinds ofcorruption might have more importance for investment decisionsthan the overall level of corruption.

Predictive Content of Corruption for GrowthIn this section, the predictive content of corruption for growth is

investigated using the Granger-Causality test, which helps determinewhether the corruption index contains additional information aboutsubsequently realized growth rates beyond what is already containedin the past history of actual GDP growth rates. The Granger-causalityequations explain how much of the current GDP growth rate can beexplained by past GDP growth rates and whether adding lagged val-ues of corruption can improve the explanation. The GDP growth rateis Granger-caused by corruption if corruption helps in the predictionof the GDP growth rate or if the coefficients on lagged corruption arestatistically significant.

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Consider the following regressions:

(2) Gt = 0+a(Gt1 +k=1

n

a1k Gts +k=1

n

a2k Cts + 1t

(3) Ct = 0 + bGt1 Ct1 +k=1

n

a3k Gts

+k=1

n

a4k Cts + 2t ,

where G is the growth rate of GDP, C is corruption, and is adisturbance term. Corruption Granger-causes growth if a a2k 0.In that case, corruption provides information about the subsequentlyrealized GDP growth rates beyond what is already contained in thepast history of actual GDP growth rates. Similarly, GDP Granger-causes corruption if b a3k 0. In that case, GDP growth rateshave information about corruption beyond what is already containedin the past history of corruption.

The results of the Granger-causality test are reported in Table 4. Asthe table shows, corruption Granger-causes the GDP growth rate,implying that corruption has information about the subsequently re-alized GDP growth rate beyond what is already contained in the pasthistory of the GDP growth rate. In contrast, GDP fails to Granger-cause corruption and has no predictive content beyond what is al-ready contained in the past history of corruption.

Determinants of Corruption:The Empirical Evidence

Model 7 of Table 3 regresses the corruption level of the 1990s onsome independent variables that we consider relevant in explainingthe difference in corruption levels across countries. Corruption in the

TABLE 4GRANGER-CAUSALITY TEST RESULTS

a A10.034 (2.62) 0.18 (5.43) F-Statistic

3.14783Prob.

0.04988b A20.105 (0.89) 0.06 (1.07) F-Statistic

0.29241Prob.

0.74748NOTE: A1 = k=l a2k, and A2 = k=l a3k; t-values are in parentheses.

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1980s is added as an additional explanatory variable because the otherdeterminants of corruption can easily be affected by that variable.Clearly there is some persistence in corruption. The coefficient ofcorruption in the 1980s is positive and highly significant. Most of thecoefficients of the other explanatory variables are also significant atthe 5 percent level.

The coefficient of education is negative and significant at the 1percent level. Evaluating the effect at the sample mean, the estimatedcoefficient indicates that a one-unit increase in secondary school en-rollment reduces corruption by 0.508 percent. The rule of law alsohas a noticeable impact on corruption. For example, a one-unit in-crease of the rule of law is associated with a decline of corruption by0.18 percentage points.

The size of government is positively and significantly correlatedwith the level of corruption. The coefficient of GOV in Model 7shows that a 10 percent increase of the size of government is associ-ated with about a 2 percent increase in the level of corruption. Thecoefficient of foreign aid is also positive and highly significant. For-eign aid strengthens the predatory power of the government and thusundermines the emergence of the private sector. Since foreign aid isfungible, it tends to increase government consumption. It createsopportunities for the government to proliferate, which in turn in-creases the level of corruption. The interaction term between foreignaid and government expenditure shows that the marginal effect ofgovernment expenditure on corruption increases with the level offoreign aid.

Political freedom is negatively correlated with corruption; however,the correlation coefficient of political freedom is not significant at theconventional level. The effect of freedom on corruption appears inthe economic freedom coefficient. The coefficient of economic free-dom is negative and significant at the 5 percent level. The empiricalresults also indicate that federalism reduces corruption. The coeffi-cient of the type of the state in Model 7 is significant at the 10 percentlevel. Two dummy variables are also included in Model 7 to accountfor continent specific characteristics. The dummy variable for Africais positive and insignificant, while the dummy variable for LatinAmerica is negative and significant.

Most of the indicators we used to explain variations in corruptionacross countries reflect an overall impression of how well countriesare governed in a very general sense. If so, they will be correlatedwith corruption, itself subjectively measured. A more interesting andinformative test would include more objectively measured determi-nants of corruption. Therefore, in Model 7, the per capita GDP

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growth rate is also included as an additional explanatory variable. Thecoefficient of the per capita GDP growth rate is negative but statis-tically insignificant.

The empirical results are consistent with the theory that higherjudicial efficiency, higher level of schooling, greater economic free-dom, smaller government, less foreign aid, and decentralized govern-ment will lower corruption. Ethnicity has no significant impact oncorruption. The implications of these results are obvious. Those poorcountries with large and cumbersome bureaucracies, weak and inef-ficient judicial systems, and poor educational systems can reducecorruption and increase their growth potential by improving theirlegal systems, investing in education, reducing the size of the govern-ment, reducing dependence on foreign aid, and decentralizing thepower of the state.

ConclusionThe social and economic costs of corruption recently gained atten-

tion from the development literature. The literature on corruptionemphasized the deleterious effects of corruption on investment andeconomic growth. However, until recently no attempt has been madeto elaborate the determinants of economic corruption. In this article,education, judicial efficiency, the size of government, political andeconomic freedom, foreign aid, ethnicity, and the type of the politicalregime are used to explain cross-country differences in corruption.Corruption is found to be negatively and significantly correlated withthe level of education, judicial efficiency, and economic freedom. It ispositively and significantly correlated with foreign aid and the size ofgovernment. An interesting result of this study, which might needfurther analysis, is the effect of foreign aid on corruption. The coef-ficient of foreign aid is positive and highly significant. The fungibilityof foreign aid exacerbates the negative effect of big government ongrowth. The interaction term between foreign aid and governmentexpenditure in Model 7 of Table 3 suggests that the marginal effectof government expenditure on corruption increases with the level offoreign aid.

The findings of this study also indicate that those countries thatenjoyed a substantial growth rate for the past two decades are thosethat developed legal, institutional, and educational measures that en-couraged bureaucratic honesty and discouraged corruption and mal-feasance. The political implications of the study are clear. Effortsshould be directed to the establishment of good education, efficientlegal systems, smaller and decentralized government, and less depen-

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dence on foreign aid. Corruption is encouraged not only by the im-portance of government as the provider of goods and services but alsoas the producer of a plethora of confusing and contradictory regula-tions. Resources should thus be marshaled to expand opportunitiesfor employment in the private sector.

Corruption flourishes in an environment of unrestrained bureau-cracy. It can be contained when the laws of the land are vigorouslyenforced. Moreover, when the administration or the political order isconsidered as illegitimate, the social pressures against acts of corrup-tion become less important. Corruption can therefore be effectivelycurtailed by an administration that enjoys an enduring legitimacy.

Appendix: Description, Source, and Relevance ofthe Variables

AID: Effective development assistance (EDA) measures officialaid flows as the sum of grants and the grant equivalent of officialloans. The grant equivalent of a financial inflow is the amount that, atthe time of its commitment, is not expected to be repaidthat is, theamount subsidized through below-market terms at the time of com-mitment.

Corruption 1980s: The corruption level in the 1980s. It measuresthe extent to which high government officials are likely to demandspecial payments. It is from the Political Risk Services of Syracuse,New York, a private firm that publishes country risk factors and sellsthem to interested parties. The data on corrup80 is available onlyfrom 1982 to1990. The index ranks countries in the scale of 0 to 6,where 0 means the highest level of corruption and 6 the lowest. Wereversed the scale and converted the original ranking of 0 to 6 into ascale of 0 to 1.

Corruption 1990s: The corruption level in the 1990s. It is fromTransparency International (a coalition against corruption in interna-tional business transactions). This index is based on international sur-veys of business people and reflects their impressions and perceptionsof the countries surveyed. The index is available from 1995 to 1999,and ranks countries on a scale of 0 to 10. For conformity, we reversedthe scale and converted the original rankings into a scale of 0 to 1.

Economic Freedom: Measures the extent to which economicagents are free to use the market mechanism for the allocation ofresources and the extent to which property rights are protected. Theindex ranks countries on a scale of 0 to 10, where 10 indicates thehighest level of economic freedom and 0 the lowest. For conformity,

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we converted the original ranking of 0 to 10 into a scale of 0 to 1. Thisindex is from Gwartney and Lawson (1997) and covers more than 100countries.

Ethnicity: The domination of one ethnic group in the polity of acountry creates differential access to power. Less powerful politicalethnic groups or minorities resort to corruption for leveling the po-litical and economic landscape. In ethnically diverse societies, theobligation of a bureaucrat is sequential: first to his close kin, then tohis ethnic group, and then maybe to his country. Thus, highly frag-mented societies are likely to be more corrupt than homogenoussocieties. We converted the original ranking of 0 to 100 into a scale of0 to 1. The index is from Mauro (1995) and Easterly and Levine(1997).

Government Expenditure Share of GDP: Economic corruptionis defined as the sale of public office for a private gain. Big govern-ments create opportunities for corruption. The larger the size of thebureaucracy, the more likely that more bureaucrats will put theiroffices up for sale. In LDCs, the modern private sector is embryonicand the state assumes the primary role of allocating and distributingresources. The larger the relative size and scope of the public sector,the greater the likelihood of corrupt behavior.

Growth of Real GDP per Capita (9095, 7595, 7585):World Development Indicators, the 1998 edition (hereafter WDI98).

Political Freedom: An index that measures the level of politicalfreedom. The index ranks countries on a scale of 0 to 7. The higherthe score the lower the level of political freedom. We reversed thescale and converted the original ranking of 0 to 7 into a scale of 0 to1. When the media is independent and free from government control,and citizens are allowed to freely express their opinion about theaffairs of the state, governments become more transparent and cor-ruption easily exposed. Thus, politically open societies tend to be lesscorrupt. Furthermore, when the political order is undemocratic andis perceived by the public as an illegitimate entity, social pressuresagainst the acts of corruption are of little significance. Stealing fromthe oppressor is not as tainted as stealing from the public treasury.The political freedom index is from the Freedom House and is com-piled annually since 1972.

Rule of Law: Reflects the degree to which the citizens of a countryare willing to accept the established institutions to make and imple-ment laws and adjudicate disputes. It also measures the extent thatcountries have sound political institutions, strong courts, and orderlysuccession of powers. Cheung (1996) attributes the pervasiveness ofcorruption in LDCs to the weakness and the absence of institutional

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safeguardsthat is, to a lack of well-defined and firmly enforcedprivate property rights. It is from the Political Risk Services of Syra-cuse, New York, and ranks countries on a scale of 0 to 6. This indexis available only for the 198290 period. Again, the original ranking isconverted into a scale of 0 to 1.

The level of corruption depends on the extent to which the laws ofthe land are binding and enforced. Corrupt officials are rational wel-fare maximizers. They weigh the pecuniary benefits from corruptionagainst its cost. The personal cost of corruption is the loss of a job andthe jail-time if caught and persecuted. Individuals will act corruptly solong as the perceived gains from corruption outweigh the costs. Theprobability of detection is lower the more lackadaisical the judicialsystem is. Judicial laxity reduces the opportunity cost of being corrupt.Hence, countries with strict laws and efficient judicial systems tend tobe less corrupt and vice versa.

Secondary School Enrollment Rate in 1975: Measures the per-centage of school-age population that was enrolled in secondaryschools in 1975. A higher level of education fosters a sense of nation-alism and instills pride and civic duty in the citizenry. It also raises thepublics awareness of their rights for the services of the bureaucrats.Generally, most of the citizens in LDCs are not aware that they areentitled to the services of the bureaucrats. Scott (1972: 15) succinctlydescribed this lack of awareness in developing countries:

The bureaucrat is a high school or university graduate . . . who dealsoften with illiterate peasants for whom government, let alone itsregulations, is a mystifying and dangerous thing. In approaching acivil servant, the peasant is not generally an informed citizen seek-ing a service to which he is entitled, but a subject seeking to appeasea powerful man whose ways he cannot fathom; where the moderncitizen might demand, he begs or flatters.

In developing countries there is a confusion of the bureaucratsprivate rights and his public responsibility. The bureaucrat hardlydistinguishes when he is acting in a public capacity providing servicesas a matter of duty, from when he is acting in a private capacityproviding personal services. That attitude is attenuated by the igno-rance of the general public. Thus, the higher the level of education,the lower the level of corruption.

Type of State (Federal or Unitary System): Decentralizationand vertical separation of powers reduces corruption and creates mul-tiple veto powers along vertically competing jurisdictions. It makescollusion among corrupt officials difficult to enforce. However, Shle-ifer and Vishny (1993) claimed that centralized corruption is prefer-

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able to decentralized corruption for efficiency purposes. They claimthat the devolution of power from central to regional governmentsmultiplies opportunities of corruption. They suggest that decentral-ized governments with decentralized bribe-taking mechanisms in-crease the cost of bureaucratic corruption. The cost of corruptionbecomes excessive when different levels of the government set theirbribes independently. Federalism as a hierarchical separation of pow-ers can therefore either increase corruption or keep it in check. Weuse a binary variable that takes 0 if a country is a centralized unitarystate and 1 if it is a decentralized federal system.

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