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TOO SICK TO PROGRESS?
ECONOMIC IMPACTS OF NON-COMMUNICABLE DISEASES IN
LATIN AMERICA AND THE CARIBBEAN
by
Latecia Frank
A thesis submitted in fulfillment of the
partial requirements for the completion of
Master of Commerce in Economics
Copyright © 2014 by Latecia Frank
School of Economics
Faculty of Business and Economics
The University of the South Pacific
July, 2014
DECLARATION OF ORIGINALITY
Statement by Author
I, Latecia Frank, hereby declare that this thesis is my own work and that, to the best of my
knowledge, it contains no materials previously published, or substantially overlapping with
material submitted for the award of any degree at any institution, except where due
acknowledgement is made in the text.
……………………………………… Date: 22nd of February, 2015
Latecia Akela Frank
Student ID No: S11093960
Statement by Supervisor
The research in this thesis was performed under my supervision and to my knowledge is the
sole work of Ms. Latecia Akela Frank.
Date: 22 day of February, 2015
Dr. Hong Chen
Principle Supervisor
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DEDICATION
“Beloved, I pray that you may prosper in all things and be in health, just as your soul prospers.”
(3 John 1:2 New King James Version)
With these words, I dedicate this thesis to my parents, Audrey and Floyd Frank. It is my heart’s
desire that the words of this scripture manifest in your lives. Cheers to health and long lives!
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ACKNOWLEDGEMENT
Research can be a lonely and daunting task, especially when in a foreign land. For the strength to
persevere and complete this journey I first thank my Lord and Saviour, Jesus Christ, without
Him this would not have been achievable.
To my supervisor, Dr. Hong Chen, I am grateful for the chance you took on me as your first
research student. Your guidance and patience were very instrumental in the completion of this
thesis. I hope this work is a reflection of your diligence and support.
For the opportunity to complete this Masters of Commerce in Economics I thank my sponsor, the
Caribbean Pacific Island Mobility Scheme (CARPIMS) and the University of the South Pacific
(USP).
To my parents, I say a resounding thank you for your support through every stage of my
academic journey. I will forever be grateful to you for giving me the opportunities you were not
privileged to receive. Thank you mom, for believing in me and cheering me on in the difficult
times. Special thanks to my dad for encouraging me to take a step of faith out into a place I had
never heard of to pursue my dream of obtaining a Master’s Degree.
To my two very special friends, Tracy Dolcy and Rolando Cocom, a big vinaka vakalevu for
reading my drafts, giving suggestions and encouraging me from the start. Also to my friends,
aunts, uncles and my 101 cousins home in Guyana, a huge thank you.
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ABSTRACT
This thesis examines the link between economic growth and mortality due to non-communicable
diseases (NCDs). It quantifies the annual macroeconomic loss of output per worker in ten Latin
American and Caribbean (LAC) countries during 1997-2009 resulting from increasing mortality
caused by cancers, diabetes mellitus, cardiovascular diseases (CVD) and chronic respiratory
diseases. The sample countries are Antigua and Barbuda, Argentina, Barbados, Belize, Brazil,
Chile, Ecuador, Guyana, Saint Vincent and the Grenadines, and Trinidad and Tobago. Both
country and period selections were solely based on consistent availability of data. Estimates are
done in a panel growth regression framework which also controls for endogeneity.
Use of the two-stage least squares (2SLS), instrumental variables generalized method of
moments (IV-GMM), dynamic panel data (DPD), and the fixed effects (FE) estimators shows
that higher rates of deaths caused by the four NCDs lowered the level of per capita income of the
sample economies during the period under investigation. During this time, approximately 8.5
million lives were lost due to these NCDs. This resulted in an estimated annual loss of US$2.3
billion. The results of this thesis show that an annual reduction of the NCD mortality ratio by one
percentage point is likely to result in an increase of per capita income ranging from 0.03 percent
to 0.05 percent.
Conversely, use of the same estimators suggests that there were negative though statistically
insignificant effects of NCD related deaths on the growth of per capita income. However, there
has been an upward trend in these deaths in the sample countries. Based on the findings of this
thesis, this increase is in part attributed to the growing prevalence of NCD risk factors and the
high out-of-pocket costs of health care. If the current trends continue to lower incomes there will
likely be an adverse effect on economic growth as the loss of labour and human capital continue
to accumulate.
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Table of Contents
ABSTRACT ................................................................................................................................................. iii
LIST OF ACRONYMS .............................................................................................................................. vii
CHAPTER ONE: INTRODUCTION ........................................................................................................... 1
1.1 Background ................................................................................................................................... 1
1.2 Statement of the problem .............................................................................................................. 2
1.3 Research rationale ......................................................................................................................... 3
1.4 Research question ......................................................................................................................... 4
1.5 Aim and objectives ....................................................................................................................... 4
1.6 Research hypothesis ...................................................................................................................... 5
1.7 Brief overview of research methodology ...................................................................................... 5
1.8 Research contribution ................................................................................................................... 5
1.9 Organization of the thesis ............................................................................................................. 6
1.10 Summary and conclusion .............................................................................................................. 7
CHAPTER TWO: ECONOMIC GROWTH, HUMAN CAPITAL AND HEALTH ................................... 8
2.1 Introduction ................................................................................................................................... 8
2.2 The Latin America and the Caribbean economies ........................................................................ 8
2.2.1 Structure of the sample economies (2000-2012) .................................................................. 8
2.2.2 Growth trends in Latin America and the Caribbean ........................................................... 11
2.3 Economic Growth ....................................................................................................................... 13
2.3.1 What is economic growth? .................................................................................................. 13
2.3.2 What do high growth economies have in common? ........................................................... 14
2.3.3 Why is economic growth important? .................................................................................. 15
2.4 How to achieve growth: Theories of economic growth .............................................................. 16
2.4.1 Neoclassical growth theory ................................................................................................. 16
2.4.2 Endogenous growth theory ................................................................................................. 18
2.4.3 Health and Economic Growth ............................................................................................. 20
2.5 Health care in Latin America and the Caribbean ........................................................................ 31
2.6 Summary and conclusion ............................................................................................................ 37
CHAPTER THREE: SILENT KILLER-THE THREAT OF NON-COMMUNICABLE DISEASES ...... 39
3.1 Introduction ................................................................................................................................. 39
3.2 Overview of general health trends .............................................................................................. 39
3.2.1 The epidemiological transition ............................................................................................ 41
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3.3 The challenge of development and non-communicable diseases ................................................ 43
3.3.1 Non-communicable diseases in Latin America and the Caribbean ..................................... 44
3.3.2 Risk factors for developing non-communicable diseases ................................................... 47
3.3.3 Addressing non-communicable diseases through research transferability.......................... 53
3.4 Conceptual framework and empirical evidence: Non-communicable diseases-growth nexus ... 54
3.5 The empirical evidence of the economic impact of non-communicable diseases ...................... 57
3.6 Summary and conclusion ............................................................................................................ 60
CHAPTER FOUR: EMPIRICAL ANALYSIS .......................................................................................... 62
4.1 Introduction ................................................................................................................................. 62
4.2 Data ............................................................................................................................................. 62
4.3 The Model ................................................................................................................................... 67
4.4 Methodology ............................................................................................................................... 69
4.4.1 Panel Unit Root Test ........................................................................................................... 69
4.4.2 Panel Long-run co-integration ............................................................................................ 70
4.4.3 Endogeneity ........................................................................................................................ 71
4.5 Empirical findings and interpretation ......................................................................................... 72
4.6 Summary and conclusion ............................................................................................................ 82
CHAPTER FIVE: CONCLUSION AND POLICY IMPLICATION ......................................................... 84
5.1 Introduction ................................................................................................................................. 84
5.2 Key findings and discussion ....................................................................................................... 84
5.3 Policy implication ....................................................................................................................... 86
5.4 Summary and conclusion ............................................................................................................ 87
5.5 Limitations .................................................................................................................................. 89
5.6 Future avenues for research ........................................................................................................ 89
References ................................................................................................................................................... 90
Appendix A ............................................................................................................................................... 101
Appendix B ............................................................................................................................................... 102
LIST OF TABLES
Table 2.1: Economic indicators (2000-2012)……………………………………………………………..9
Table 2.2: Economic indicators (2000-2012)……………………………………………………………..10
Table 3.1: World estimates of death by cause ..………………………………………………………….43
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Table 3.2: Composition of energy sources (per kilocalorie) in daily diet per capita…………………....50
Table 4.1: Summary statistics of core variables (1997-2009)…………………………………………...63
Table 4.2: Average growth rates of variables……………………………………………………………64
Table 4.3: Average growth rates of variables……………………………………………………………65
Table 4.4: Results of Breitung Panel Unit Root Tests…………………………………………………...72
Table 4.5: Durbin-Wu-Hausman Test for the Null Hypothesis of Exogeneity………………………….74
Table 4.6: Sargan Test for the Null Hypothesis of Over-identification of External Instruments………..75
Table 4.7: First stage IV estimates for NCD mortality ratio……………………………………………..76
Table 4.8: Estimates of the relationship between per capita income and deaths due to NCDs…………..79
Table 4.9: Estimates of the relationship between per capita income and deaths due to NCDs – Robustness test………………………………………………………………………………………………………...80
LIST OF FIGURES
Figure 2.1: Growth of Gross Domestic Product in Latin America and the Caribbean (1961-2012)……..11
Figure 2.2: Health and improved productivity…………………………………………………………....25
Figure 2.3: Health Expenditure and GDP growth in sample countries (3-year intervals)………………...32
Figure 2.4: Sources of health care services financing……………………………………………………..33
Figure 3.1: Trends in health and demographic indicators of Latin America and the Caribbean………….40
Figure 3.2: Major causes of death in Latin America and the Caribbean in 1995 and 2012……………….41
Figure 3.3: Cause of death by region……………………………………………………………………...45
Figure 3.4: Linking Non-communicable to economic growth…………………………………………….55
Figure 3.5: Non-communicable diseases and GDP growth in Latin American and Caribbean economies
(1997-2009)……………………………………………………………………………………………….57
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LIST OF ACRONYMS 2SLS Two-Stage Least Square
AR Autoregressive
BMI Body Mass Indexes
CARICOM Caribbean Community
CID Council for International Development
COI Cost of Illness
CVD Cardiovascular diseases
DALYs Disability Adjusted Life Years
DPD Dynamic Panel Data
EU European Union
FAO Food and Agriculture Organization
FE Fixed Effects
GDP Gross Domestic Product
GFCF Gross Fixed Capital Formation
GLS Generalized Least Square
GMM Generalization Method Moment
HDI Human Development Index
IMF International Monetary Fund
IV Instrumental Variables
IV-GMM Instrumental Variables Generalized Method of Moments
LAC Latin America and the Caribbean
MDGs Millennium Development Goals
NCDs Non-communicable diseases
OECD Organization for Economic Co-operation and Development
OECS Organization of Eastern Caribbean States
OLS Ordinary Least Squares
PAHO Pan American Health Organization
PAHO/HEF Pan American Health Organization Health Economics and Financing
PICs Pacific Island Countries
PIM Perpetual Inventory Method
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LIST OF ACRONYMS
SACECH South American Center for Cardiovascular Health
SHI Social Health Insurance
SPC Secretariat for the Pacific Community
TFP Total Factor Productivity
UN United Nations
UNDP United Nations Development Programme
USA/US United States of America
VLO Value of Lost Output
WHO World Health Organization
WEO World Economic Outlook
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CHAPTER ONE: INTRODUCTION
1.1 Background
The means through which economic growth and development are attained remain highly
debatable as history shows that ‘no one size fits all’. Theorists continue to incorporate aspects of
the neoclassical and endogenous growth theories to explain how countries achieve long-term
economic growth. Such enquiries have often advocated human capital development especially
through education and skills training as a fundamental factor of growth (Lopez-Casasnovas et al.,
2005) . As such, anything that negatively affects the quality of human capital presents a potential
challenge to economic development. More recently, the significance of health as an aspect of
human capital that is also integral to development has gained equal repute (Akram et al., 2009;
Ben-David, 2009; Kulik, 2013; Lopez-Casasnovas et al., 2005; Smith, 1999). In the past,
development initiatives addressing health have primarily focused on preventive health care and
the eradication of infectious diseases such as malaria (Gallup and Sach, 2001) and HIV/AIDs.
However, over the past two decades non-communicable diseases (NCDs) have emerged as the
new threat to health.
The World Health Organization (WHO) defines NCDs as long-term, non-contagious and non-
infectious diseases which develop over time and remain in the body, slowly progressing to cause
severe complications and deterioration in the victim’s health (WHO, 2013b). They are also
referred to as ‘lifestyle’ diseases. Cancers, diabetes mellitus, cardiovascular diseases (CVD) and
chronic respiratory diseases are the four most widespread NCDs. Globally, an estimated 63
percent of deaths (36 million) each year are caused by NCDs (WHO, 2013b).
NCDs are increasingly becoming a challenge to development in low and middle income
countries. Of the estimated deaths globally, 80 percent occur in these economies. Mortality and
morbidity due to these diseases reduce worker productivity and the stock of human capital
available in the form of skills and knowledge. Reduced productivity due to morbidity results in
worker absenteeism (Chadha et al., 2007). It lowers income and by extension consumer utility of
non-health related goods and services (WHO, 2009). As associated medical costs accrue to
employers output is reduced and firms’ profits decline (Chadha et al., 2007). There are also
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added costs to governments as an increase in morbidity raises public health care costs while
premature mortality reduces the available labour supply, skilled labour and shrinks the tax base
(Bell et al., 2004, p. 98; Englegau et al., 2011). These all accumulate to current and future
macroeconomic losses.
Latin America and the Caribbean (LAC) has experienced the double coincidence of low
economic growth and increasing rates of NCD related deaths. Currently, the region records an
annual NCD mortality rate of more than 70 percent of total deaths (World Bank, 2014a, p. 27).
Given the potential economic impacts of higher rates of NCD related deaths and morbidity, this
thesis attempts to investigate if there is a causal link between this phenomenon and economic
performance in ten LAC economies.
1.2 Statement of the problem
Some theorists (e.g., Erdil and Yetkiner, 2004; Mirvis and Clay, 2008; Morand, 2002) suggest
that the health-income relationship is bi-directional. It is argued that over time and across
countries increased income is correlated with improvements in health outcomes. In this accord,
Jack (1999, p. 27) advocates that any strategy to improve health must be hinged on economic
development. At higher income levels one’s propensity to consume both health and non-health
related goods and services increase (Preston, 1975, p. 232). On the other hand, improved health
can be an important precursor to economic growth and development (e.g., Arora, 2001;
Bhargava et al., 2001; Fogel, 1994) . According to this tenet, healthier people tend to have
greater productive potential and are more active in the labour force (Bloom et al., 2001; Lopez-
Casasnovas et al., 2005; Matthews, 2013; Weil, 2007).
However, the benefits of health can be reversed as premature mortality and frequent morbidity
due to diseases such as NCDs become more dominant. These occurrences have social and
economic ramifications. Matthews (2013) and Barcelo et al. (2003) in assessing the economic
costs NCDs impose on the LAC region posit that the public health care system bears the brunt of
these costs. They argue that economies are negatively affected by NCDs because public health
care services are more frequently accessed by people with NCDs. This has led to the progressive
increase in their associated costs. Conrad and Webb (2012) also show that the costs of treating
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these diseases significantly reduced output in three Caribbean states.1 It is recognized that NCDs
reduce social welfare, the growth of per capita income (Suhrcke and Urban, 2006, p. 2), and
lower consumer utility. Other economic costs include lower labour supply, productivity and
human capital accumulation.
Additionally, NCDs have direct socioeconomic impacts on families, especially children. The
emotional trauma of losing a parent(s) could “…plausible weaken the transmission of knowledge
and capacity from generation to generation” (Bell et al., 2004, p. 98). Correspondingly,
premature mortality due to these diseases result in reduced household incomes which affect
savings and financing of children’s education (Bell et al., 2004, p. 96).
1.3 Research rationale
In 2011, it was noted at the United Nations (UN) General Assembly’s first ever High Level
Meeting on Non-communicable diseases that,“…the spread of non-communicable diseases [is] a
socioeconomic and development challenge of epidemic proportions” (UN, 2011a). Past studies
(e.g., Abegunde and Stanciole, 2006; Bhargava et al., 2001; Gallup and Sachs, 2001) have shown
that disease prevalence affects the aggregate labour supply, capital accumulation and labour
productivity in economies. Recent estimates show that a country’s growth may be curtailed by
0.5 percent for every 10 percent increase in the costs of treating NCDs (WHO, 2012).Thus,
addressing NCDs is necessary when dealing with macroeconomic and development issues.
Based on these, the rationale for this thesis is outlined below.
LAC, like other developing regions, has experienced a slow in economic performance. High
macroeconomic volatility on account of changing global economic conditions and vulnerability
to natural disasters amongst other factors have resulted in these countries having low growth
rates (World Bank, 2005; Zettelmeyer, 2006, p. 16). Hence, they are doubly challenged as the
number of deaths due to NCDs has grown, accounting for three out of every four deaths in the
region (World Bank, 2014a, p. 27). There is an increasing economic and human resource loss
resulting from NCD mortality in these economies. This and the low growth rates of the region’s
income cause one to question if this situation could have long-term growth effects. However,
1 More on this study can be found in Chapter Three.
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empirical research to quantify this relationship in low and middle income economies of LAC is
limited.
An urgency exists for research on NCDs in LAC. Such research can offer an avenue for research
tranferribility within the region that can be used to enhance policy decisions. According to Perel
et al. (2006), these countries have the adequate supply of technology-communications
infrastructure and human resources to execute high quality research. The fact that it is a fairly
homogenous group of similar language, culture and socioeconomic attributes makes pooling of
resources for such research comparatively cheaper than in developed countries. Yet research is
not centred on diseases that have a great burden in the region (Perel et al., 2006). As such, a
niche exists for research in this area.
1.4 Research question
This exploratory study attempts to answer the following question:
� How has higher ratios of deaths caused by NCDs in LAC during 1997 to 2009 affected
the level and growth of per capita income?
1.5 Aim and objectives
This study aims to investigate the relationship between NCD related deaths and economic
growth in ten LAC countries during 1997 to 2009. Based on this, the specific objectives of this
thesis are:
� To identify the trends in NCD related deaths and per capita income growth in the
sample countries during the period under investigation.
� To estimate the macroeconomic costs of deaths due to NCDs in the sample countries
during this time by quantifying the annual loss of income per worker.
� To discuss the risk factors influencing the growth of the NCD mortality in LAC.
� To recommend channels through which deaths caused by NCDs can be reduced.
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1.6 Research hypothesis
Given the means by which NCDs affect economies, this thesis undertakes to test the hypothesis
that higher rates of these diseases lowered current per capita income growth and income levels in
ten LAC countries during 1997 to 2009.
1.7 Brief overview of research methodology
The focus of this thesis is on ten LAC countries, namely Antigua and Barbuda, Argentina,
Barbados, Belize, Brazil, Chile, Ecuador, Guyana, Saint Vincent and the Grenadines, and
Trinidad and Tobago. The specific NCDs examined are cancers, diabetes mellitus, CVD and
chronic respiratory diseases. The sample period under study is 1997 to 2009, though periods
outside this window are used for general reviews and emphasis. The selection of these countries
and years is largely based availability of data. Information used were obtained from a wide array
of literature including journal articles, government and non-government reports and technical
papers, books, international organizations’ online databases and academic theses examining
related areas.2
Qualitative and quantitative analyses are used to base all conclusions and recommendations of
this study. The value of lost output (VLO) method is employed through the utilization of various
econometrics techniques such as two-stage least squares (2SLS), instrumental variables
generalized method of moments (IV-GMM), dynamic panel data (DPD), and the fixed effects
(FE) estimators.3 The STATA 13 software package is used for computation.
1.8 Research contribution
This thesis responds to a growing interest by stakeholders and policymakers seeking information
on the extent of potential macroeconomic losses due to the continued prevalence of NCDs. As
emphasized by the WHO (2009), studies in tandem with this thesis serve as tools to identify
ways to prevent and/or treat these illnesses through cost effective strategies. Though not aimed at
country specific policy recommendations, it provides a key avenue from which researchers and
policymakers can analyze the economic burden resulting from NCDs in the LAC region. It is 2 A more detailed account of the analysis of data is included in Chapter Four. 3 Refer to Chapter Three for further details on VLO.
6
therefore an intermediary tool that can be used for evidence-based policy planning (Mayer-
Foulkes and Villouta, 2012, p. 10).
Few researches have attempted to show the causal relationship between mortality due to NCDs
and economic growth in LAC. The adoption of this thesis’ methodology can provide useful
insights to other researchers conducting similar investigations. It is therefore hoped that
awareness of the issue will be gained to encourage other academics to do further research on the
economic burdens imposed by NCDs in the region. This in turn can contribute to the sharing of
best practices within the region to curtail the effects of these diseases.
1.9 Organization of the thesis
Four additional chapters are included in this thesis. Chapter Two focuses on the two broad
themes of economic growth and health. It discusses specifically the interconnectedness of
economic growth, human capital and health in the process of development. The chapter begins
with a review of economic structures of the sample countries and growth trends in LAC.
Following this is a discussion of some aspects and critiques of the neoclassical and endogenous
theories of economic growth. It then highlights the importance of human capital development
through education and health. Finally, some past empirical evidence are presented outlining the
arguments for health as pertinent to growth.
Chapter Three examines the impact of ill-health in the form of NCDs. This chapter highlights the
trends and current status of NCDs in the LAC region with references to other low and middle
income countries. A brief discussion of some aggregate health indicators and risk factors of
NCDs then follows. Finally, some empirical works estimating the economic costs of these
diseases are summarized.
Chapter Four details the research methodology, empirical findings and interpretation of results.
The econometric model is outlined along with identification of data sources and descriptive
statistics of the core variables used for analysis. This chapter includes an outline of a modified
Solow (1956) growth framework which is used to show the economic impact of NCD mortality
and full explanations of the procedures followed for estimation.
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Chapter Five concludes with a summary of this research and provides some insights for policy
direction and potential areas for future exploration. Also, it highlights some channels through
which NCD mortality deaths can be reduced and discusses general policy implications of the
research findings.
1.10 Summary and conclusion
This chapter has introduced the general aim and purpose of this thesis by outlining its rationale,
the research questions, contribution and the organization of this thesis. The first section defined
NCDs and introduced the concept of human capital in the form of health. It gave an overview of
the connection between health, NCDs and economic growth by highlighting the channels
through which NCDs affect economic growth. The following chapters expand on the theoretical
and conceptual frameworks, findings and recommendations of the thesis.
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CHAPTER TWO: ECONOMIC GROWTH, HUMAN CAPITAL AND
HEALTH
2.1 Introduction
There are two broad themes that govern this thesis: economic growth and health. The issues
surrounding these concepts are many. However, it is not plausible (nor is it the intention) to
cover all in this thesis. This chapter focuses on the conceptual framework of economic growth
and establishes the importance of health as an essential factor of permanent growth.
The first section begins with a brief overview of the economic structure of the sample economies
and growth trends in the LAC region. It then defines economic growth, shows its importance and
examines some critiques of the neoclassical and endogenous growth theories. The second section
presents theoretical and empirical evidence that support the interconnectedness of economic
growth and human capital development through education and health. This chapter paves the
way for Chapter Three which examines ill-health in the form of NCDs and its economic impacts.
2.2 The Latin America and the Caribbean economies
2.2.1 Structure of the sample economies (2000-2012)
The selected countries under investigation in this thesis have various geographic, historical,
cultural, and economic commonalities and peculiarities. One of the most prominent
commonalities in these countries is their economic structure (see Tables 2.1 to 2.2). Most of
them are service oriented, with this sector contributing an average of 50 to 80 percent of annual
Gross Domestic Product (GDP). The second largest sector is manufacturing which averages
around 2 percent to 20 percent, followed by the agricultural sector with a maximum of 15
percent except in the case of Guyana where it exceeds 20 percent.
Based on income categories, the majority of the ten was classified by the World Bank as low and
middle income at the end of 2013. These include Argentina, Belize, Brazil, Ecuador, Guyana,
and St. Vincent and the Grenadines. The others, such as Antigua and Barbuda, Barbados, Chile,
and Trinidad and Tobago were classified as high income. Eight of the ten have low per capita
income growth rates ranging below 1 percent to 2.5 percent with the exception of the high
9
income economies of Chile, and Trinidad and Tobago averaging 3.1 percent and 4.5 percent
respectively.
Important to note is that the economies with growth rates below 3 percent are those also with low
saving or investment ratios (less than 22 percent) or a combination of both. One exception is
Ecuador which has both investment and saving ratios in excess of 22 percent but growth is below
3 percent. This could be attributed to the fact that Ecuador over this period has had the second
fastest growing population in the group. Though Barbados has the highest per capita income it
also has the lowest growth rate coupled with the largest budget deficit in the group and
investment and saving ratios below 20 percent.
Table 2.1 Economic Indicators (2000-2012)
Antigua &
Barbuda
Argentina Barbados Belize Brazil
GDP per capita (Constant 2005 $US) 12,027 4,398a 14,230 4,022 4,982
GDP per capita growth (%) 0.7 1.8 a 0.5 2.1 2.3
Agriculture value added (% of GDP) 2 9 1.8 15 6
Services value added (% of GDP) 79 59 82 65 66
Manufacturing value added (% of GDP) 2 21 8 12 17
Trade (% of GDP) 115 39 92 120 25
Budget deficit (% of GDP) -4.2 3.0b -6.5c -4.0 -2.3
Foreign Direct Investment (% of GDP) 13.3 2.3 6.4 7.2 2.9
Human Development Index (HDI) 0.76 0.81 0.82 0.70 0.73
Total investment (% of GDP)* 40 20 17 22 18
Gross saving (% of GDP) 16g 21 12g 8h 16
Population growth rate 1.2 0.9 0.5 2.6 1.1
Public Health expenditure (% of GDP) 3.2 5.0 4.7 3.0 3.5
Source: World Development Indicators (2013) Note: a Data only available for 2000-06; b 2002-04; c2007-10; g2000-09; h2000-08; *Estimates of the World Economic Outlook database. ^Estimates for 2012 only, taken from United Nations Develpoment Programme (2013)
10
Additionally, the economies with at least 50 percent of their income coming from the services
sector are also those with per capita incomes in excess of US$3,000. The only exceptions are
those of Guyana and Trinidad. A closer comparison of these two economies as illustrated in
Table 2.2 shows some glaring similarities. Both have comparable service and manufacturing
sectors, investment and population growth rates. However, Guyana’s growth is one third and its
income per capita one tenth that of Trinidad’s. The apparent difference may be in the great
disparity in saving ratios.
Table 2.2 Economic Indicators (2000-2012)
Chile Ecuador Guyana St. Vincent &
Grenadines
Trinidad &
Tobago
GDP per capita (Constant 2005 $US) 7,816 3,045 1,126 5,098 12,536
GDP per capita growth (%) 3.1 2.4 1.3 2.3 4.5
Agriculture value added (% of GDP) 4 11 27 7 0.8
Services value added (% of GDP) 59 54 43 74 42
Manufacturing value added (% of GDP) 14 14 6 6 6
Trade (% of GDP) 68 57 201e 88 144
Budget deficit (% of GDP) 2.0d n.a n.a -2.1 1.0f
Foreign Direct Investment (% of GDP) 6.9 1.2 7.8 13.2 7.0
Human Development Index (HDI)^ 0.82 0.72 0.64 0.73 0.76
Total investment (% of GDP)* 22 23 17 26 18
Domestic saving (% of GDP) 22 24 10 5 36i
Population growth rate 1.0 1.8 0.5 0.1 0.4
Public Health expenditure (% of GDP) 3.1 2.0 4.5 3.5 2.5
Source: World Development Indicators (2013) Note: d Data for 2002-12; e 2000-05; f 2001-10; i2000-08; n.a-not available; *Estimates of the World Economic Outlook database. ^Estimates for 2012 only, taken from United Nations Develpoment Programme (2013)
Social indicators in the region have greatly improved over the years and are comparable across
country. For example the Human Development Index (HDI) in the sample has averaged above
11
0.70 which is equivalent to medium development status. The only exception is Guyana’s 0.64
which corresponds to its low income status.
Other social indicators such as public health expenditures as a percentage of GDP have shown
less improvement. For the most part this ratio has remained low in the region, averaging between
2 and 5 percent throughout 2000 to 2012 for the majority of countries.
2.2.2 Growth trends in Latin America and the Caribbean
Baumol (1986) reminds that the importance of economic history must not be obviated in efforts
to understand growth. In keeping with his admonition, a historical review of growth in LAC is
presented to show some of the dynamics that may have contributed to its present performance.
The LAC region’s growth history is one plagued by bouts of economic mismanagement, political
upheavals, crimes and external shocks that hampered progress in some of its economies (Loayza
et al., 2005) . In the periods prior to the early 1980s growth in Latin America averaged an
estimated 5.5 percent annually (Moreno-Brid et al., 2005) . The region posted some of its highest
growth rates during the 1960s and 1970s. Since then growth has not regained those levels. For
most of the post 1970s and 2000 period LAC has recorded the lowest growth amongst the
developing regions (Zettelmeyer, 2006, p. 4).
Figure 2.1 Growth of Gross Domestic Product in Latin America and the Caribbean (1961-
2012
Source: Constructed by author based on data from World Bank (2014b). Estimates are for the wider LAC region
inclusive of the ten sample countries.
-3-2-101234567
Perc
ent (
%)
Years Growth of GDP (%)
12
During the 1980s there was the major debt crisis. This marked the commencement of some of the
region’s worst economic performances. According to Godard and Williamson (2003), one of the
more significant events that occurred and affected the region was the 1982 depletion of Mexico’s
foreign reserve. This led to the region in a matter of weeks being declared in a state of crisis
(Godard and Williamson, 2003, p. 22). Average growth in LAC during 1981 to 1990 was 2.2
percent, down from its 3.2 percent in the previous decade (World Bank, 2014b). In this period
most of the economies in Latin America recorded negative growth except for Columbia and
Chile (Loayza et al., 2005). In association with this growth slowdown was an increase in
macroeconomic volatility in the region, averaging 0.0323 in the 1980s, up from its 1970s
estimate of 0.0246 (Loayza et al., 2005, p. 71). In an effort to revive the region economic
reforms were implemented in the latter part of the 1980s and early 1990s in most countries.
Following the implementation of these reforms performance improved in some economies.
During the latter half of the 1990s regional growth averaged 3.4 percent (World Bank, 2014b).
Though some fluctuations remained they were less pronounced as illustrated in Figure 2.1. In
fact, for the period 1990 to 1998 LAC was the second fastest growing developing region
(Zettelmeyer, 2006, p. 5). The economies of Suriname, the Dominican Republic, Guyana and,
Trinidad and Tobago were a few that had significant recoveries in the 1990s. Some like Haiti and
Jamaica posted further negative growth (Loayza et al., 2005). Still, only a few achieved growth
rates higher than their 1960s and1970s levels.
Between 2000 and 2009 growth declined again, coinciding with the 1999 Brazilian currency
devaluation, the 2002 crises in Brazil and Argentina and the global economic crisis of 2008.
Notwithstanding, LAC has made some improvements in social indicators such as life
expectancy, education and nutrition over the last two decades. This improvement has been
comparable to that achieved in some Asian economies (Zettelmeyer, 2006, p. 12).
Future challenges to economic growth in Latin America and the Caribbean
Godard and Williamson (2003) posit that the region continues to struggle with two things that
hinder its growth. Its high income inequality and low savings which perpetuate poverty and the
region’s rapidly ageing population. These will most likely result in larger public health care
13
burden which could lead to slower growth in the future, particularly in smaller LAC economies
as funds get diverted from other productive activities.
High rates of poverty can counter the effects of policies aimed at improving welfare. Most LAC
countries have in excess of 25 percent of the population living on less than $2 daily (Godard and
Williamson, 2003). According to Godard and Williamson (2003), in 2001 estimates of the
poverty ratio in Peru was as high as 54 percent. Consequently, very few of these economies have
saving ratios above 19 percent (Godard and Williamson, 2003, p. 29). Taking into account these
it is hard to imagine an already poor population increasing savings on meager incomes. This
poverty will likely reduce savings further, increase poverty and constrain growth.
Additionally, an increase in longevity means people live longer and their chances of developing
NCDs increase (Bloom et al., 2011). Thus, not only will the LAC economies have an ageing and
poor population that must be maintained on public resources but potentially one with more
illnesses. As evident in the analysis by Abegunde and Stanciole (2006) cost of treating these
diseases also affect investment and growth.
2.3 Economic Growth
2.3.1 What is economic growth?
In dealing with the issue of economic growth there are some fundamental questions that must be
addressed by economists and policymakers. These include:
1. What is economic growth?
2. What contributes to economic growth?
3. How is economic growth sustained?
The answers to these questions are still being debated today. Nonetheless, an apt definition of
economic growth may essentially summarize it as being the positive and consistent increase in
aggregate output measured by GDP. It is caused by the improvement in a country’s productive
capacity over a long period (preferably decades). This can be either through an increase in
quantity and quality of available inputs or advancement in technology that results in better use of
productive factors. Put differently “a growing economy is one in which energies are better
14
directed; resources better deployed; techniques mastered, then advanced. It is not just about
making money” (The Commission on Growth and Development, 2008, p. 17).
Crucial to the growth process is the improvement in technical efficiency/total factor productivity
(TFP). How to improve this has been highly contested by both neoclassical and endogenous
growth theories. Each has presented its case on choice of variables to achieve and sustain
growth.4 Some of these claims have failed to produce robust results when applied across different
sample countries and time periods. This has left the questions of growth without any definitive
answers that are uniformly applicable to all economies.
Being mindful of the numerous issues of contention in the growth debate the review of the
literature from henceforth highlights only a few prominent areas, focusing on contributions by
some of the more well-known theorists.5 What follows is an attempt to succinctly raise the
importance of growth and a few arguments for and critiques of the endogenous and neoclassical
theories.
2.3.2 What do high growth economies have in common?
According to the Commission on Growth and Development (2008), there were thirteen countries
that experienced growth rates of 7 percent and higher annually over a 25-year post World War II
period.6 It notes that these countries had the following mutual characteristics:
� Capable, committed leadership, good governance and quality institutions
� High trade openness, knowledge importation and access to global demand
� High saving and investment ratios (20 to 25 percent)
� Credible macroeconomic policies (e.g., modest inflation, and sustainable public finances)
and overall macroeconomic stability
� Market oriented systems where prices determine resource allocation
4 Proposed factors of growth by neoclassical and endogenous theories are examined later in this chapter. 5 The mathematical derivation of growth channels is saved for the purpose of analysis in Chapter Four. 6 Seven percent is the prescribed benchmark as sufficient to double GDP in ten years (The Commission on Growth and Development, 2008, p. 1).
15
These are desirable attributes of high-growth economies which most countries may strive to
imitate. After pursuing these ‘ideal’ prerequisites for growth an economy must be able to
organize and execute necessary actions to set it on its growth path, assuming the path can be
chartered by policy and the provision of conductive environment to foster growth.
2.3.3 Why is economic growth important?
“The consequences of human welfare involved in questions like these are simply staggering:
once one starts to think about, it is hard to think about anything else.” (Lucas, 1988, p. 5)
Governments and international organizations have often emphasized the need for growth. Many
factors are touted as ‘growth-enhancing’ but what constitutes the necessary or sufficient
conditions for growth are highly contestable. The World Bank has continuously advocated the
pertinence of growth to foster development. It recognized as early as 1980 in its edition of the
World Development Report that ‘growth is vital for poverty reduction’. In the same light it states
clearly that growth by itself is not a sufficient condition to accomplish the eradication of poverty
(The World Bank, 1980, p. iii).
There has been expressed concern as to whether growth leads to poverty reduction or vice versa.
This thesis does not seek to argue this point or promote one as more important than the other.
Both sides of this debate have been extensively explored by previous theorists (e.g. Agrawal,
2007; Gafar, 1998; Ijaiya et al., 2011; and Warr, 2004) . The Commission on Growth and
Development (2008) offers that sustained growth is a means to several ends including poverty
reduction, human development, and improved health outcomes. Whether growth is a ‘means’ or
an ‘end’ in itself, may depend on the context in which it is being examined. In the context of
developing countries it can be contended that growth and poverty reduction should be
simultaneously tackled.
Growth is important for both its direct and indirect effects. More importantly, continuous growth
is important and particularly desirable to address a multiplicity of issues including health. Some
may agree that “countries that grow strongly and for sustained periods of time are able to reduce
significantly their poverty levels, strengthen their democratic and political stability, improve the
quality of their natural environment, and even diminish the incidence of crime and violence”
(Loayza et al., 2005, p. 4).
16
2.4 How to achieve growth: Theories of economic growth
The means through which growth is accomplished varies based on the theoretical framework
being applied. The neoclassical theory takes productivity/exogenous technical change as the sole
factor to sustain permanent growth. The endogenous growth theory advocates growth enhancing
factors such as health, education, and research and development (R&D) as sources of permanent
growth. The following section briefly surveys some of the key aspects and critiques of both
theories.
2.4.1 Neoclassical growth theory
One of the earliest attempts to address the issue of growth is that of Solow (1956) neoclassical
growth theory. This approach has for the most part withstood the test of time, still much is left
unexplained. In its effort to explain growth, the theory uses a simplified process of interaction
between technological and conventional inputs: labour and capital (Romer,1996). Solow (1956)
is one of the simplest yet most useful models for understanding growth. Below is an examination
of some of the basic assumptions and three critiques of the model.
The Solow (1956) model is premised on the concept of diminishing marginal returns to capital
and factor substitution that takes place in perfectly competitive markets. It is assumed that there
are constant returns to scale. The saving rate (s) and population growth rate (n) determine per
capita income levels in the steady state. Due to diminishing marginal returns, capital
accumulation fails to sustain long-term growth. It therefore takes exogenous technical
progress/TFP to sustain growth. These assumptions allow for stable growth equilibrium to be
accomplished in the long-run.7
The first critique of the model is related to measuring TFP. What constitutes TFP is an assumed
measure of systematic and idiosyncratic factors along with an error term that captures the effects
of all other things including technology (Bloom et al., p. 7). It is argued that there is no definite
method to quantify TFP because it is not something observed and the various methods used to
estimate it are flawed (World Bank, 2005). The debate on how to measure TFP and the factors
that influence it is ongoing and has resulted in a growing body of literature analyzing its
contribution to growth (e.g. Senhadji, 2000; Young, 1992, 1994). 7 For a mathematical derivation and application of the assumptions refer to Chapter Four.
17
The second critique is that the source of growth is exogenous thus policy-neutral. The exogeneity
of TFP means that the model “predicts stable growth independent of policy decisions” (Renelt,
1991, p. 1).This has raised skepticism amongst policymakers about its adoption because it
renders policies ineffective in the long-run.
The third critique is based on convergence. The model assumes countries with similarities such
as technology will eventually converge to the same level of steady state output to close the cross
country income gap. This is based on a proposed initial differential in returns to capital between
developed and developing countries that makes returns to capital higher in developing countries.
Thus, the economies with higher returns should attract more investment and grow at a faster
pace. This allows economies at lower levels of steady state output to catch up to those with
higher incomes, thus leading to convergence.
The two types of convergences popularly proposed by neoclassical theorists are: 1) β-
convergence which states that poorer countries grow faster and eventually attain the same level
of per capita income as their richer counterparts; and 2) σ-convergence which proposes the
reduction in the variance in per capita income distribution across countries (Barro and Sala-i-
Martin, 2004) . The empirical evidence of convergence has been mixed since wage and returns to
physical capital have not equalized across countries and regions. The variance in results claiming
convergence (or lack of it) suggests that it is based on more than similar technological and factor
endowments.
Baumol (1986) is one of the earliest attempts to test the hypothesis of convergence. He contends
that convergence in both growth rates and level of per capita income is evident in the developed
world. Following him there has been a list of works arguing for and against convergence
including Collins et al. (1996); Hahn and Kim (1999); Islam (1995); Mankiw et al. (1992); and
Quah (1993). These have created a rift amongst theorists as a consensus on convergence is still
pending.
Based on some of these short comings it became very apparent in the mid-1980s that the
neoclassical model was a misfit when it came to reconciling theory and empirics to determine the
true ingredients of long-run growth (Barro and Sala-i-Martin, 2004; McCallum, 1996). In an
18
attempt to correct what the neoclassical theorists started there was the emergence of the
endogenous growth theory.
2.4.2 Endogenous growth theory
The distinguishing mark of endogenous growth theory is that it assumes that growth is
determined within the system, influenced by human capital and knowledge. Romer (1986) is one
of the first to formalize endogenous growth theory. Following Romer (1986) are the works of
Lucas (1988) and Barro (1990) amongst others that have generated a vast body of endogenous
literature.
The literature does not produce a universal growth model (Singh, 2012) though many factors
including health as human capital are proposed to be growth enhancing if they can be shown to
increase TFP. Endogenizing growth removes the constraint of diminishing marginal returns to
factors and allows countries with higher investment and technology to grow faster and remain
ahead of their poorer comparators. This is proposed as an explanation to why convergence does
not occur.
To explain TFP as a variable that can be determined within the model and influenced by policy,
endogenous theorists redefine the conventional view of ‘inputs’ and ‘technology’ rebranding
them ‘ideas’ (which are non-rivalry) and ‘things’ (which are rivalry). Ideas are generated and
marketed as products created in the production process (micro level) for the production process
(macro level). As such ideas, a component of human capital, and things are used as two
components in the production process which are able to influence TFP to sustain long-term
growth.
Romer’s (1986) model shows ideas/knowledge gained from R&D as an intermediate good
produced by “…a research technology that exhibits diminishing returns” (p.1003). It is important
to note that knowledge itself has an increasing marginal product with spillover effects. The
importance of knowledge in the thrust towards development has long been recognized by
economists, including Adam Smith. Smith (1904, p. 8) asserts that an economy’s ability to
generate wealth lies in “…the skills, dexterity and judgment with which its labour is generally
applied.” Investing in knowledge increases the productivity of physical capital. Knowledge
19
accumulation through education and R&D can therefore advance an economy to new growth
trajectories.
The World Bank’s World Development Report (1980, p.1) notes the importance of knowledge
by stating “most of the fastest growing developing countries without oil have had well educated
populations.” A comparison of Brazil and South Korea supports the arguments advancing
investment in education. These countries once of comparable income levels and growth rates in
the 1960s have greatly diverged over the last three decades. Brazil’s sluggish growth of per
capita income (thrice its 1960 level) has led to it now being classified as middle income. South
Korea has managed to multiply its per capita income (almost ten times that of its 1960 level) and
is now a high income economy. All this has occurred jointly with the increase in the poverty and
education gaps. Brazil has 12.7 percent of its population living on less than $2 daily (Weisbrot,
2011). In South Korea, aggregate poverty level is ‘arguably’ 2 percent (UNDP, 2009 as cited in
Weisbrot, 2011). Similarly, estimates show that investment in education has contributed 3.3
percent and 15.9 percent of economic growth in Brazil and South Korea respectively
(Psacharopolous, 1984 as cited in Downes, 2001, p. 9). At its present growth rate Brazil will
need 25 years to catch up to the per capita income level of South Korea (Levy and Schady, 2013,
p. 195) .With situations like these endogenous growth theorists advocate for policies that
increase knowledge capital.
Lucas (1988) posits that an individual’s human capital is in the form of his skills and ability to
learn by doing. The model implies that individual human capital accumulation continues
throughout lifetimes. Human capital has the added ability to boost productivity of all other
factors through its ‘internal’ and ‘external’ effects. Thus, the cycle of knowledge accumulation
perpetuates continuous growth.
A critique of endogenous theory is the fact that continuous growth is based on continuous
accumulation of human capital (McCallum, 1996). Lucas (1988) recognizes that lifetimes are
finite “people accumulate it [human capital] early in life, then less rapidly, then not at all-as
though each additional percentage increment were harder to gain than the preceding one” (Lucas,
1988, p. 19). This implies an inverse relationship between human capital and lifespan. As people
20
age human capital contributes less to growth. Thus, infinite growth cannot be sustained by finite
human capital.
A second critique is that skills possessed by individuals and knowledge (which is assumed to be
publicly available at no cost) are vital to the growth process. However, unlike knowledge skills
cannot be completely transferred to future generations (McCallum, 1996, p. 58) and its quality
reduces with time. Furthermore, knowledge though freely available must incur expenditure to
generate new stocks. Its non-excludable nature therefore relinquishes rights to profit which
would make it less attractive to private investors.
In sum, proponents of the neoclassical theory offer that economic growth in the long-run is only
possible through exogenous technical progress. However, it fails to detail the source of the
technical progress. Similarly, the proposed ineffectiveness of policy in the long-run and
unobserved cross country convergence have casted doubts on the model. Endogenous theorists
have proposed such factors as human capital development and knowledge accumulation through
education and R&D as growth enhancing. Its literature has proposed ways to solve the problems
of policy and convergence in the neoclassical models. Yet, endogenous models still have their
shortcomings as it relates to skills transfer and funding knowledge generation.
The main thread through the arguments presented above is the crucial need for investing in
human capital via education and skills training. Nevertheless, intellectual ability is only one
component of human capital. As such “to attribute all improvements [in economic output] to
education would be a little more than naive” (Lewis, 1961, p. 114). Besides, education and health
are interdependent because unhealthy persons invest less in education. Educated persons take
better care of their health. The next section introduces health as another important aspect of
human capital that affects output.
2.4.3 Health and Economic Growth
Why health?
“The linkages of health to poverty reduction and to long-term economic growth are powerful,
much stronger than is generally understood” (The Commission on Macroeconomics and Health,
2001, p. 1).
21
According to the WHO (2003), “health is a state of complete physical, mental and social well-
being and not merely the absence of disease or infirmity”. The conventional way of estimating
aggregate health status in a society has been to use measurements including life expectancy,
child or adult mortality, adult survival rates, overall mortality rates, disease specific mortality,
and disease prevalence. (Acemoglu and Johnson, 2006; and Aghion et al., 2010) . Even this
does not suffice as health is a multifaceted concept that does not abide by one definition or
measurement (Arora, 2001).
Health is important for economic development (Lopez-Casasnovas et al., 2005).“Different
theories of economic growth produce different answers to the question of how health conditions
affect a country’s per capita GDP over time” (Howitt, 2005, p. 19). In the neoclassical context
the only factor that will affect the growth rate is thought to be exogenous technical progress,
anything else, including health, will only affect level of per capita income. In endogenous growth
models health can impact positively during the transition to the steady state within the context of
intertemporal optimization (Lopez-Casasnovas et al., 2005, p. 4). These effects can be observed
either directly or indirectly through their impact on labour productivity and physical capital.
Though nascent, enquiries into the economic benefits of health have gained prominence and have
generated a growing body of literature (e.g. Aghion et al., 2010; Arora, 2001; Bhargava et al.,
2001; Bloom et al., 2001; Gallup and Sach, 2001; Howitt, 2005; Weil, 2007) . These have all
recognized the dynamic relationship between health and economic outcomes. The importance of
health is made more resounding because three of the world’s Millennium Development Goals
(MDGs) are health related.
Benefits of health
Educational opportunities
The health status of a person can directly impact on the level of educational attainment. Better
health raises the incentives for education. Lopez-Casasnovas et al. (2005) note that in order to
maintain sustained growth an economy must have a labour force equipped with at least some
minimum level of education and health. Mirvis and Clay (2008, p. 138) suggest that workers’
productivity is affected by childhood health status and educational achievement since they are
22
positively related. For example, a decline in child mortality increases the likelihood of investing
in children’s education since parents expect children to live longer. Healthier students have less
absent days from school and higher cognitive abilities (Howitt, 2005; Lopez-Casasnovas et al.,
2005). Hanushek and Woessman (2012) using regional tests scores, offer that 50 percent of Latin
America’s low growth can be attributed to the low levels of students’ cognitive ability (cited in
Levy and Schady, 2013, p. 198) . Additionally, ill health during childhood and parental death due
to diseases reduce “…school attendance and enrolment” (Lopez-Casasnovas et al., 2005, p. 14).
By the same token, adult health contributes directly to productivity. When people expect to live
longer self-improvement through education is more likely. Higher life expectancy increases
average years spent in the workforce. This therefore extends the time in which educational
investment returns are amortized (Mirvis et al., 2008; Weil, 2007) . Kalemi-Ozcan, et al. (2000)
and Sala-i-Martin (2005), find that a one percent increase in longevity is likely to produce an
equal increase in years spent in school. This can potentially be rewarded with a starting wage 15
percent higher than average (as cited by Mirvis and Clay, 2008. P. 139) .
Increased investment in physical and technological capital
An increase in the stock of health capital can lead to an increase in physical and technological
capital. The double benefits of a highly educated and healthy labour force suggest that it is
“…easier to create, use and adapt new technology” (Lopez-Casasnovas et al., 2005, p. 3). This
can result in an increase in the rates of investment as improvements in health and education have
a bi-directional relationship with physical capital accumulation. According to Lopez-Casasnovas
et al. (2005, p. 13), the demographic transition that is as a result of longer lifespans and less
disease works to promote higher household savings because funds that would have otherwise
been used for caring the sick can now be saved for investment. Therefore, health tends to
increase domestic and foreign investments vice versa. Zhang et al. (2003) reiterates this point.
They argue that longer life expectancy increases GDP growth through higher rates of capital
accumulation funded by increased savings (cited in Aghion et al., 2010, p. 1).
23
Poverty reduction
Through better health there is an avenue for poverty reduction. Lopez-Casasnovas et al. (2005)
posit that the disparity between the rich and the poor would have been much more pronounced if
not for the improvements in health. On the macroeconomic level health investment, especially in
developing countries “…provides a means of escaping from the poverty trap” (Lopez-
Casasnovas et al., 2005, p. 7). Increased labour participation due to improved health enables
workers to earn more income and accumulate assets (Smith, 1999). Additionally, family
planning services that help to promote stable fertility rates aid in this effort of reducing poverty
through improved health and offering education as an alternative to child bearing.
Increased labour productivity
“Health is an important form of human capital which can enhance worker productivity by raising
physical capacities such as strength and endurance, as well as mental capacities like cognitive
functioning and reasoning ability” (Bloom et al., 2002, cited in Nisha, 2006, p.72). Health
increases resilience against diseases, worker productivity and income (Lopez-Casasnovas et al.,
2005, p. 4). Therefore “any activity depending on the input of labour hours will be negatively
affected by a decrease in the health state of the population” (Zon and Muysken, 2003, p. 3). The
reduction of output and hourly wages due to ill-health and disability can be substantial,
especially in developing countries where a greater percentage of the production process is labour
intensive compared to industrialized countries (Bloom et al., 2001).
Potential consequences to improved health?
It could be argued that improved health does not always have a positive effect on income growth.
For instance, reduced child mortality can increase the dependency ratio. Accordingly, Bloom et
al. (2004) find that an increase of one percent in the population below the age of 15 is likely to
lower per capita income by 0.4 percent (as cited in Mirvis et al., 2008, p. 40).
Bloom et al. (2011) posit that the downside to improved life years and rapid ageing is that there
is a relatively large portion of elderly in the population. This reduces the relative size of the
working age population and affects saving since there are less income earners in the economy.
As suggested by Boersch-Supan and Ludwig (2009), “the combination of possible labor market
24
tightening and dissaving raises concerns that the steeply ageing countries will experience slower
economic growth. Some countries may even face the shrinkage of their economies” (cited in
Bloom et al., 2011, p. 4).
2.4.3.1 The bi-directional income-health relationship
“The analysis of the impact of economic growth on health and the impact of health on economic
growth is still today very challenging in the health economics literature” (Lopez-Casasnovas and
Sloey-bori, 2013, p. 2).
The direction of health’s impact on per capita income growth could conceptually be ambiguous,
due to the endogenous nature of these variables (Weil, 2007). This also makes it difficult (and
according to some impossible) to accurately measure this relationship.
Erdil and Yetkiner (2004) through the use of micro panel data verify that the income-health
relationship is bi-direction. They claim this would indeed render any estimation of the
relationship using the ordinary least squares estimator (OLS) inadequate. Through the use of
Granger causality they show that the dominant relationship in their panel was bi-directional.
Moreover, they contend that the relationship is unidirectional from income to health only in low
and middle income economies. In the case of LAC countries they find that both directions hold.
In Argentina and Chile the relationship was found to be bi-directional, for Ecuador it goes from
GDP to health and in Brazil it goes from health to GDP.
Bhargava et al. (2001) reaffirm this two way relationship. They state that in aggregate terms a
country’s income level, either above or below a given threshold, is what determines the direction
of the relationship. They argue that the effects of better health leading to higher income are more
pronounced for low income groups while the opposite is true in higher income groups.
Hamoudi and Sachs (1999) likewise show that a significant and robust cyclical relationship
exists between health and income. According to them the simultaneity of the relationship may
indicate a situation where multiple equilibria exist. As such, there is possible scope for policy to
influence these outcomes. In the undesireable equilibrium ill-health (e.g. NCDs) begets ill-health
which perpetuates poverty (Hamoudi and Sachs, 2009). Alternatively, they posit that in the ‘good
health’ equilibrium improved health ignites growth which further promotes health.
25
Figure 2.2: Health and improved productivity
Source: Created by the author.
2.4.3.2 From health to income
Gains in health outcomes have been associated with income growth. Schultz (1961) was one of
the earliest to argue that investment in human capital in the form of health has extensive impacts
on productivity. He posits that a large portion of low income is as a result of low investments in
health (Schultz, 1961, p. 14). As one becomes healthier both physical and mental endurance
improve to permit increased time in the labour force and more accumulation of knowledge which
amounts to higher incomes.
Conversely, a deterioration in health leads to sickness. Sick individuals either withdraw from the
labour force or continue to work at lower productivity. Some may regain health and return to
contribute productively to society while others may die. Correspondingly, mortality and
morbidity reduce investment in education which results in lower output and growth (see Figure
2.2).
Education: Knowledge,
Accumulation, Technological
innovations
Cure
Health: Life Expectancy,
Disease, Mortality, Morbidity
Productivity/Growth
Death
Sickness
26
2.4.3.3 From income to health
It is recognized and supported empirically that higher incomes are associated with better health
outcomes (Mirvis et al., 2008). Preston (1975) in his early attempt to examine the income-health
relationship models the effects of growth on mortality and life expectancy using cross-sectional
data for three decades. His conclusion is that economic factors including income lead to changes
in life expectancy.
People in richer countries with higher wages are healthier since they have more access to health
care and better knowledge of nutrition. This helps to impact current and future labour
productivity as richer families raise healthier children who participate more in school (Weil,
2007, p. 18). These children likewise have a better chance at getting higher paying jobs and
continuing the cycle of income growth.
Conversely, lower income can preclude the poor from accessing preventive health care services
making them more prone to sickness. To a large extent low incomes also help to exaggerate
health and social constraints that interact to promote the prevalence of certain diseases as
demonstrated in the ‘fundamental cause theory’ (Chang and Lauderdale, 2009). Goldstein et al.,
(2005) report that individuals in Peru on the higher socioeconomic spectrum are four times less
likely to suffer from cardiovascular diseases compared to the poor (cited in Perel et al., 2006).
Similarly, in Colombia the underprivileged, especially the uneducated young, are highly
vulnerable to mental health diseases (Perel et al., 2006).
Some disadvantages to health due to income growth and distribution
Income growth can cause deterioration in health status. Lopez-Casasnovas and Soley-bori
(2013) suggest that higher growth comes at the cost of lower health status indicators. For
example, the increase in industrialization and globalization that leads to economic growth has
been linked to the rise in chronic diseases. Elkins (2008) argues that with industrialization comes
rapid urbanization and congestion which are associated with many illnesses. Based on Kuznet’s
premise of the pollution-growth relationship she finds that there is an indirect relationship of
income growth on health through pollution. This relationship is modelled using the incidence of
respiratory diseases associated with pollution due to industrialization. The findings of her thesis
27
show that there exists a significantly positive relationship between air pollution and respiratory
complications in a sample of Indonesian communities where the level of industrialization is high.
In a similar manner, the distribution of income has been argued to affect the level of health. The
International Monetary Fund (IMF, 2014) notes that income inequality across and even within
countries has grown over the decades. This has been observed in the LAC region which has one
of the most skewed income distribution in the world (Godard and Williamson; and Levy and
Schady, 2013) .
Lopez-Casasnovas and Soley-bori (2013) contend that health inequality within an economy is
the result of income inequality. They investigate a panel of 32 Organization for Economic
Cooperation (OECD) countries for the period 1980 to 2000. The random effects estimator was
employed to ascertain the underlying causes of observed inequality in cross country health status.
The findings indicate that for every 1 percent increase in income inequality (measured by the
gini coefficient) the health index will likely reduce by approximately 0.20. 8
Drabo (2010) takes an indirect approach to modeling the effects of income inequality on health
status. He uses a sample of 90 developed and developing countries for the period 1970 to 2000.
The under-five mortality rate is used as the health indicator and the gini coefficient as a measure
of income inequality. Through the use of two stage least square (2SLS) he shows that increased
income inequality is associated with lower health outcomes. He contends that as inequality
increases it leads to environmental degradation in the form of pollution which is associated with
a decline in health indicators. A finding that concurs with Elkins (2008).
2.4.3.4 Empirical studies linking health and economic growth
The health and economic growth literature is fairly new and has for the most part focused on
income leading to improvements in health (Mirvis and Clay, 2008) . Nevertheless, the focus of
this thesis is on the role of (ill)-health affecting economic outcomes.
According to Mirvis and Clay (2008), health is seen as serving a dual function as both an input
into and output of the production process. There are quite a few studies that investigate this
8Lopez-Casasnovas and Soley-bori (2013) use the UN’s Health Human Development index (HHDI) as their health variable.
28
relationship using different estimation techniques, time spans, and sample countries in either
cross country or time series datasets. Likewise, all have defined health differently and used
various types of indicators as measures of individual or aggregate health.
Like many other areas of contention in growth theory, there are still some skepticism as to the
accrued benefits of health as a catalyst in the growth process as well as its impact on income
levels (Acemoglu and Johnson, 2006; Nisha, 2006).What follows is an attempt to summarize a
number of studies on the health-income relationship.
What have we learnt from the health-to-income relationship?
It is important to reiterate that knowing the relationship between health and economic growth is
relevant in assessing the impacts of ill-health (NCDs) as the consequences of this would be the
reversal of the health benefits that accrue.
Fogel (1994) was instrumental in igniting the health-to-income debate with his seminal paper
that investigated the link between malnutrition and economic growth in Britain over a 200-year
period. He states that due to the low energy intake from food calories by the poor it was virtually
impossible for them to contribute productively. Fogel argues that with the increased food supply
and better nutrition a significant portion of the poor was able to join the labour force. This in turn
accounted for an estimated 20 percent of Britain’s long term growth.
Bloom et al. (2001) use data from 1960 to 1990 to estimate the impact of health in a panel of
developed and developing countries using 2SLS. The findings indicate that for every additional
year of life expectancy gained GDP is likely to grow by 4 percent. They accordingly promote
health as a more crucial factor of growth.
Lorentzen et al. (2008) regress the adult mortality rates on the growth rate of GDP per capita for
a panel of 98 developed and developing countries for the period 1960 to 2000.They find that a
one percent increase in the mortality rate will likely lead to a 4.25 percent reduction in per capita
GDP. They posit that the increase in mortality rates shortens lives, leading to lack of incentive to
save and invest in capital (both physical and human) for future benefits. They show that the
relationship holds when including other control variables and suggest mortality rates account for
at least ten percent of the differential in incomes across countries.
29
Chadha et al. (2007) find that there are significant levels of correlation between preventive health
care and corporate profitability. They use a sample group of high earnings, Indian companies and
their employees to conclude that preventive health care is associated with a 17.2 percent increase
in profitability. Conversely, absenteeism and lost man-days due to illness are associated with a
4.7 percent and 21.8 percent reduction in profits respectively. They also find that early
intervention reduce cost of curative care by four percent.
Gallup and Sach (2001) regress malaria rates on the growth rate of per capita income using cross
country data for a group of countries from 1965 to 1990. They find that a ten percent increase in
malaria prevalence will likely reduce per worker income by 0.3 percent. They contend that there
is a significant and robust impact of disease on income growth as countries with high malaria
infections have incomes 30 percent less than those without.
Weil (2007) reaffirms that health affects economic output. By use of the fixed effects estimator
with 82 developed and developing countries he finds that a 0.1 increase in adult survival rate
leads to a 4.4 percent rise in per capita income.
Arora (2001) uses the life expectancy at different age and average height of adults to estimate
health impact on growth. He employs dynamic OLS method for ten industrialized countries
spanning different time intervals from 1870 to 1990. The findings show that the improvements in
life expectancy permanently raised the level and growth rate of per capita income.
Cole and Neumeyer (2007) use a panel of 52 developed and developing countries for five year
intervals from 1965 to 1995 to measure the impact of malaria, malnutrition and sanitation on the
level of TFP. They find that a one percent increase in the malaria rate lowered TFP by an
average ranging from 0.41 to 0.70 percent in the sample countries.
Bhargava et al. (2001) use five year intervals from 1965 to 1990 to estimate the impact of adult
survival rates on the GDP growth rate in a group of developed and developing countries. They
conclude that health has positive growth effects only in poor countries where the per capita GDP
is below $3,554 (measured in 1985 international dollars).
Aghion et al. (2010) investigate the relationship between the growth rate of per capita GDP and
life expectancy in 96 high, middle and low income countries during 1960 to 2000. They find
30
that both the level and rate of accumulation of health have significantly positive effects on
growth of per capita GDP.
Akram et al. (2009) use time series data for Pakistan from 1972 to 2006 to estimate the impact of
health on income. They use health expenditure and life expectancy as two measures of health.
The findings show that health expenditure has a negative impact on per capita income while life
expectancy had a positive and significant effect only in the long-run.
Acemoglu and Johnson (2006) using data for 59 countries from 1940 to 1980 and the 2SLS
estimator estimate health’s contribution to economic growth. They instrument life expectancy
using the effects of specific diseases. Contrarily, they find that improved life expectancy lowers
per capita GDP.
Qureshi and Mohyuddin (2006) investigate the impact of health proxied by under-five mortality
rate, life expectancy, tuberculosis, diarrhea, hepatitis and malaria rates on income levels and
growth for 18 developing countries. They dispute that the mortality rates and life expectancy
play significant roles in growth. They find only the rate of hepatitis to have negative effects on
both level and growth of income while malaria has a significantly negative impact on income
level only. One inconsistency of this estimation that may have led to life expectancy being
insignificant is the authors’ use of OLS which neglected to control for possible endogeneity.
Malik (2006) use time series data for India from 1975 to 2003 to regress the infant mortality rate,
life expectancy and fertility rate on gross national income. He finds no significant evidence to
suggest that any of these health indicators have growth enhancing effects on income.
Nisha (2006) uses time series data for Fiji from 1970 to 2002 to estimate the growth impact of
life expectancy. Through the use 2SLS approach she concludes that life expectancy has short run
level effects on income but no permanent impacts on the growth rate of income.
The findings presented by the various empirical studies vary according to methodology and
health proxy used. One common observation made by most of the studies is the fact that
endogeneity may exist in the health-income relationship. This is an important consideration in
estimating this interaction of the two variables.
31
Notwithstanding, the potential growth effects of health on income can only be experienced
through access to improved healthcare. For this to materialize there must therefore be
mechanisms in place to finance and deliver quality health care services.
2.4.3.5 Financing health care services
According to Sloan and Hsieh (2012) “…how the health care system is structured in financing
personal health care services has important implications for other macroeconomic outcomes such
as precautionary saving, labour market outcomes and deadweight loss…”(p. 693). For this
reason increased investment in health is advocated as an avenue to economic development.
Caution should be administered when it comes to recommending increased public spending on
health as there is a tendency for some theorists to equate higher expenditure on health as
‘investment in health’ (Lopez-Casasnovas et al., 2005). Any such attempt to improve health
through spending should be guided by a well-designed system of checks and balances to ensure
efficient allocation and use of funds. This ensures the goal of improved health outcomes is
achieved.
2.5 Health care in Latin America and the Caribbean
The structure of the health care finance bill varies largely in LAC. Estimates from the Pan
American Health Organization Health Economics and Financing (PAHO/HEF, 2012) for LAC
show that total public and private health expenditure amounted to 6.7 percent of the region’s
GDP in 2011. This was the equivalent of US$661 per capita. In countries such as Antigua and
Barbuda, Argentina, and St. Vincent and the Grenadines, governments subsidize in excess of 66
percent of total health care costs. There are others where governments fund less than 50 percent
of these costs. In per capita measure, the sum of annual public and private expenditure on health
in some countries is very high; at US$1000 in Brazil and US$900 in Trinidad and Tobago. Yet
there is the exceptional case of Bermuda with US$10,830 per capita, almost twice that of Canada
and 1.5 times the United States of America amount (PAHO/HEF, 2012).
The LAC region seems to spend less on health care during economic booms and more in times of
crises. PAHO/HEF (2012) notes that expenditures grew less rapidly in the region during the
2004 to 2008 spell of growth compared to the increase in 2008 to 2010 which coincided with the
global economic crisis and the H1N1 epidemic.
32
An interesting observation is made for the sample of LAC economies where the trends in public
expenditure on health appear to be inversely related to the growth of output (see Figure 2.3). The
same is true for education expenditure. This trend is in conflict with the economic a priori which
suggests a direct relationship (Ozturk and Topcu, 2014) .
There are two possible explanations to this contradictory scenario. The first is that of the type of
activities funded by public finance in these two areas. Public funding in the health and education
sectors is usually tailored to capital and current expenditures including administrative costs. It is
plausible to offer that the current costs, for example, health care professionals’ and teachers’
salaries, are likely to be immediately re-injected in the economy in the form of increased
consumer demand. On the other hand, expenditures on capital goods, for example new hospitals,
will normally take years before their impacts are transmitted to productivity.
Figure 2.3 Health Expenditure and GDP growth in sample countries (3-year intervals)
Source: Based on World Bank Development Indicators (2014b) for the ten sample LAC countries
The second explanation to this scenario is the likely impact of migration, especially of the skilled
and healthy labour force. Migration can act as an outflow from the stock of educated human
capital which in turn lowers productivity growth. According to estimates from the World
Development Indicators (2014b) the LAC region as a whole recorded a 27 percent increase in net
migration from 1997 to 2007. This figure was representative of 0.9 percent of its total population
00.5
11.5
22.5
33.5
44.5
1999 2002 2005 2008
Perc
ent (
%)
Years
Public health expenditure (% of GDP) GDP growth (%)
33
and 1.4 percent of its working age population. If skilled labour continues to migrate before the
gains from health and education financing are recovered then growth could be retarded in the
region. Hence, the apparent negative correlation between these expenditures and income growth.
Figure 2.4: Sources of health care services financing
Source: Created by author using Sloan and Hsieh (2012, p. 694)
The funding of health services can either be private (out-of-pocket and private insurance) or
public (through general or special medical tax revenues).9 Unlike the national policymakers who
decide in advance how much to allocate towards health and what methods to use, the individual
worker cannot set a limit on how much to spend on health because illness is unplanned. What he
can do is have precautionary savings or private insurance to assist in the event of sickness. The
source and mechanism of financing health care at the individual level also has an enormous
impact on the macroeconomic functioning of the economy. There are two ways through which
individual financing affects the economy.
Firstly, if individuals are given minimum health coverage by the government and no private
insurance this could mean that the greater portion of health expenditures must be covered by out-
of-pocket funds. This increases financial vulnerability especially of low income earners.
9In some developed countries e.g. UK and Demark up to 80% of all medical expenses are covered by public resources (Sloan & Hsieh, 2012). The estimate for some developing countries are far less e.g. 97% of all medical costs are funded out-pocket in India (see Chadha et al., 2007) .
Health Financing
Out-of-pocket spending by individuals
Private health insurance
General and/or
earmarked tax revenues
34
Depending on the extent of illness and costs, households may face financial catastrophe and even
slip into poverty.
Xu et al. (2007) using data from 89 countries estimate that 150 million people globally suffer
financial catastrophe annually because they pay for relatively exorbitant health services. They
note this is not just applicable to the poor but also to the rich. It is estimated that one could be on
the brink of bankruptcy or even poverty if more than 15-20 percent of health expenditure is
funded out-of-pocket (Xu et al., 2010, p. 14). 10 They further show that around 100 million
people slip below the poverty line yearly because they are faced with greater out-of-pocket costs
for health care. Of this 100 million 90 percent live in low and middle income countries (Xu et al.,
2007, p. 976).
Hwang et al. (2001) find that individuals with chronic diseases are especially burdened with
higher out-of-pocket costs. They argue that uninsured persons affected by such diseases are less
likely to seek medical attention due to these costs. This situation increases the likelihood of
further complications due to disease and higher rates of mortality. Arredondo and Reyes (2013,
p. 1) note “in middle income countries, health disparities generated by the economic burden of
diabetes is one of the main reasons for catastrophic health expenditure”.
In LAC, the average out-of-pocket cost for 2009 was approximately 33 percent with Cuba
having the lowest of 7 percent and Ecuador and Paraguay with the highest at 55 percent (WHO,
2012). In 2011 LAC’s regional average of out-of-pocket expenditure was 48 percent
(PAHO/HEF, 2012, p. 3). For the ten LAC economies under study, out-of-pocket medical
expenditure averaged 32 percent over the period. Guyana and St. Vincent and the Grenadines
were the only countries with this cost below 20 percent of total medical expense. All other
countries had ratios above 30 percent.
Secondly, individuals’ saving decisions are affected by source of health funding. Assuming that
income is only allocated between consumption and saving (either for investment purposes or
precautionary), the threat of catastrophic health expenditure leads one to increase precautionary
saving. This shift acts as a personal safety net since there may be need for greater out-of-pocket
10 The economic consequences of illness are among the leading causes of personal debts in the United States (Himmelstein et al., 2005 as cited in Mirvis et al., 2008, p. 35)
35
spending in case of illness. This correspondingly reduces consumption and is especially true for
people suffering from chronic diseases. The long lasting nature of these diseases means that
financing their treatment and care can result in permanent adjustments in saving.
Based on these two rationales a country can experience less consumption spending, increased
poverty or a change in the saving rate when out-of-pocket expenditures are high. This in turn can
affect national income. As a counteractive measure to these having macroeconomic
consequences Sloan and Hsieh (2012) suggest governments should facilitate either public or
private insurance. They contend this reduces the risk of facing heavy out-of-pocket payments
that could lead to financial difficulty.
Chou et al. (2003) suggest that insurance provision has a dual macroeconomic function (cited in
Sloan and Hsieh, 2012). First, it reduces the demand for precautionary saving and increases
current consumption. Second, if governments incentivize employers to provide worker insurance
it can influence labour supply. Governments’ provision of concessionary tax privileges could
reduce wage costs for the employers and promote job creation.
Employer provided insurance has the added benefits of:
1. Influencing job choice since workers would gravitate to insured sectors.
2. Reducing turnover rates and promoting job security. For example, some jobs have a
probationary period until insurance coverage is granted. A worker may not want to leave
his job in search of another and risk losing his insurance benefits.
3. Potentially reducing the number of absent days. Being insured reduces the cost of doctor
visits and can help employees keep regular check on their health. This helps to promote
early diagnosis and treatment before extreme sickness manifests. Prevention or early
diagnosis can be less expensive than late detection and prolonged treatment. By
extension this boosts company productivity and profits (see e.g., Chadha et al., 2007).
Thus, both employers and employees benefit from improved health.
36
2.5.1 Social health care insurance in LAC
PAHO/HEF (2012) reports that eight countries of the LAC economies had universal social health
insurance (SHI) systems in 2011. Under these systems no less than 50 percent of the population
is covered by mandatory health care or extensive social security provisions. Examples of such
countries include Argentina, Chile and Costa Rica (PAHO/HEF, 2012).
The social insurance system in LAC is closely linked to the labour market and by extension
affects functioning of insurance programmes, productivity and domestic saving (Ferreira and
Robalino, 2011 cited in Levy and Schady, 2013, p. 200) . These programmes provide many
benefits including health, pension and employment insurance. In most of Latin America social
insurance schemes are designed to cover formal and informal workers through contributory and
non-contributory insurance.
In the case of formal workers, coverage is provided under the contributory insurance schemes
which are financed through wage taxes. These schemes, apart from providing a pension, ensure
job security as they are governed by legal employment protection regulations. Unfortunately, less
than half the formal employees in Latin America are granted the benefits of the insurance
scheme as many employers do not adhere to requirements (Levy and Schady, 2013).
Over the past two decades, the region has slowly extended what is now called the non-
contributory social insurance schemes to include informal workers. These are largely funded by
government revenues and account for approximately 0.56 percent of the region’s GDP (Levy and
Schady, 2013, p. 202). Benefits include health insurance and pension entitlements. Prominent
examples of these programmes include Mexico’s Seguro Popular and Colombia’s Regimen
Contributivo. These programmes, especially the non-contributory ones that capture the poor and
unemployed, reduce the risk of financial vulnerability caused by ill-health [including NCDs].
King et al. (2009) report that beneficiaries of the Seguro Popular had a reduction of 23 percent in
catastrophic health expenditure (Levy and Schady, 2013, p. 203).
Levy and Schady (2013) raise two concerns about social insurance, particularly the non-
contributory schemes. In the first instance, they suggest them as costly to the public treasury. As
non-contributory schemes are not funded by wage taxes the public bears the burden of financing
them. They contend this can lower the incentive of informal employment. The compensation for
37
pension is high in some Latin American countries. In Brazil it is 33 percent of per capita income.
On the other hand, the eligibility age for compensation is low (55 for females and 60 for males).
This poses a potential threat to public finances, especially domestic savings as the Latin
American population age 65 and older is estimated to increase from 7.6 percent in 2010 to 21
percent in 2050.
The second concern is that the division of the social insurance schemes into contributory and
non-contributory can result in inefficiency through resource allocation distortion that reduce
productivity and growth. They contend that movements between formal and informal
employment are very volatile. This results in most individuals having less contributions in the
formal scheme throughout their time in the labour force. As coverage is extended to all
regardless of employment status it is associated with “…erratic coverage against risks that are
only covered by contributory insurance” (Levy and Schady, 2013, p. 205). This lowers the
relative contributions of the contributory schemes share in national saving. And it dampens
individual incentive to continue funding these schemes since the same benefits accrue to those in
the informal sectors who are not subjected to the wage tax. Levy and Schady (2013) propose that
this could lead to the reallocation of resources to a growing informal sector which has lower
productivity. Thus, having a likewise reduction in macro level productivity and growth.
2.6 Summary and conclusion
The arguments presented in this chapter have examined the concept of economic growth and its
importance. It was established that growth is necessary but not sufficient for economic
development. Moreover, there was an exploration of the arguments and critiques of the
neoclassical and endogenous growth theories. The connection between growth and health was
examined in some detail from a theoretical and empirical prospective. Though the arguments
show that indeed there is a connection between these two concepts there are still some
uncertainties as to the extent of the benefits that accrue from health on an aggregate level.
Most of the empirical works cited in this chapter have highlighted the endogenous nature of the
health-income relationship. For the most part, the literature has tended to support a direct
association of health on growth. Health may be seen as an input also an outcome as the
mechanisms by which it is financed determine the final results. This chapter presented these
38
major concerns with the intention of setting the framework for the subsequent chapter which
deals with the reversal of economic gains from health caused by NCDs.
39
CHAPTER THREE: SILENT KILLER-THE THREAT OF NON-
COMMUNICABLE DISEASES
3.1 Introduction
The previous chapter provided an in-depth examination of the relationship between health and
economic growth. It highlighted the various channels through which health can affect growth and
vice versa. It was equally emphasized that ill-health can reverse all the gains from health and
adversely affect economic growth.
The aim of this chapter is to substantiate the research hypothesis by showing how ill-health in the
form of NCDs can affect economic performance by focusing on the Latin American and the
Caribbean region. It commences with an overview of some aggregate health indicators for LAC
and makes general reference to the developed and developing world to give a glimpse of health
progression in the region.
To raise the issue of the growing trend in mortality due to NCDs, the epidemiological transition
theory is briefly introduced. Following this, the link between economic development and NCDs
in LAC is made. This chapter also includes an outline of some main risk factors for NCDs.
Additionally, it contains an examination of some empirical evidence of economic costs
associated with the disease burden of NCDs. The chapter then concludes with a brief summary of
the main points presented.
3.2 Overview of general health trends
During 1950 to 1955, the health divide between developed and developing countries was quite
substantial. Average life expectancy during this time was about 35 to 45 years in developing
countries and 60 to 70 years in developed countries (Caselli et al., 2002). This disparity began to
dissipate from the 1970s and more rapidly in the 21st century when most of the developing
economies attained an average of 60 to 70 years.
The improvement in lifespan also coincided with significant reductions in infant and child
mortality. Jack (1999) estimates that child mortality in the developing world fell almost 60
percent from 1950 to 1990. Soubbotina (2004) reports under-five mortality rates reduced in the
40
20th century from an average of 280 to 79 per 1,000 in low and middle income countries. Though
these rates are in excess of those for high income economies (6 per 1,000), it is evidence of a
major improvement in the developing world.
The LAC region showed tremendous convergence to the more developed economies with life
expectancy being second only to former socialist economies of Europe (World Bank, 1993 as
cited in Jack, 1999, p. 19). It can be contended that the reduction in mortality caused by
infectious diseases (especially in children) and reduction in fertility rates played an integral role
in the improvement in longevity.
Figure 3.1: Trends in health and demographic indicators of Latin America and the
Caribbean
Source: Based on estimates from United Nations (2011) , World Bank Development Indicators (2014b) and WHO (2013). (See
Table 1 in Appendix A)
Under-five mortality in LAC was amongst the lowest in the developing world declining from 78
per 1,000 in 1980 to 38 per 1,000 in 1998. Fertility rates also declined during 2005 to 2010
reaching 2.30 down from its 1970 to 1975 rate of 5.02 (see Figure 3.1). In the same vein,
estimates for Chile, Costa Rica, and Cuba indicate that adult mortality rates also shrank by an
estimated 50 percent (Jack, 1999). In fact, the probability of dying in both developed and
developing nations showed consistent declines during the decades of 1950, 1980 and 1990. What
0
2
4
6
8
10
12
0102030405060708090
1970-75 1980-85 1985-90 1990-95 1995-2000 2000-05 2005-10
Per 1000
Years
Years
Life expectancy Infant Mortality (per 1000) Fertility Crude death rate (per 1000)
41
is interesting to note is that the greatest decline (20 percentage points from 1950 to 1980)
occurred in the most productive age cohort (15 to 59) in developing economies (World Bank
1993 as cited in Jack, 1999, p. 20). Likewise, in LAC the crude death rate plummeted during the
1970s and continued on a downward trend as life expectancy rose in association with a reduction
in fertility rates and disease-mortality shift.
3.2.1 The epidemiological transition
Generally cause of death is categorized as due to injuries, communicable or non-communicable
diseases. The shift from communicable (infectious) diseases to a high incidence of death due to
NCDs is referred to as the ‘epidemiological transition’. Evidence of this transition in the LAC
region can be seen in Figure 3.2. Within 17 years the region moved from an average NCD
mortality rate of 25 percent to 75 percent.
Figure 3.2: Major causes of death in Latin America and the Caribbean in 1995 and 2012
Source: Adapted from the Pan American Health Organization (PAHO,2012)
The theory of ‘epidemiological transition’ was first introduced by Abdel Omran (1971). He
defines epidemiology as “the distribution of disease and death, and their determinants and
0
20
40
60
80
100
120
1995 2012
Perc
ent (
%)
Years
Communicable NCDs Injuries Ill-defined causes
42
consequences in population groups” (Omran, 1971, p. 509). More specifically, Omran (1971)
infers that the transition and its consequences are deeply intertwined with a population’s
demographic and socioeconomic characteristics. As these characteristics change so does the
health and disease pattern within an economy. In this light, he proposes that as countries become
economically advanced “de-generative and man-made [chronic] diseases displace pandemics of
infection as the primary causes of morbidity and mortality” (Omran, 1971, p. 510).
This long term shift occurs in three stages: the “age of pestilence and famines” (Malthusian
regime), the “age of receding pandemics” (the transition) and the “age of degenerative and man-
made diseases” (post-transition) ” (Omran, 1971, pp. 516-517). This transition is also argued to
be a result of great improvements in health that increase life expectancy thus liberating an
economy from the Malthusian era of low survival rates (Arora, 2005).
Omran (1971) categorizes the determinants of diseases to be of three broad types. These are as
follow:
1. Ecobiological: this is a combination of disease strains, a conducive environment for its
mutation and the victim’s resilience.
2. Socioeconomic, political and cultural determinants: this includes standards of living,
health habits [lifestyle], hygiene and nutrition.
3. Medical and public health determinants: this refers to specific preventive and curative
measures used to combat disease.
The epidemiological transition in the industrialized world has been well documented. Graunt
(1939) shows that in London during the 17th century 75 percent of deaths were due to under
nourishment, prenatal complications and contagious diseases while chronic noninfectious
diseases were less than 16 percent (as cited in Omran 1971, p. 517). Like most developing
countries, those in LAC began showing signs of this transition later than the industrialized
countries. Chile was one exception where evidence of this transition was displayed as early as
1920 (Omran, 1971).
The theory of epidemiology suggests that economic advancement acts as the precursor to the
shift from communicable diseases to NCDs. This has led to the conventional belief that as
43
countries become richer the likelihood of deaths and morbidity due to NCDs become more
prominent, deeming them the diseases of the affluent (Abdulkadri et al., 2009; Suhrcke and
Urban, 2006). Increasingly this belief is changing as more evidence show even in countries
where incomes are low a growing portion of the population is being affected by NCDs. The
increase in NCDs coupled with low growth rates present a challenge to these economies
especially those of the developing world.
3.3 The challenge of development and non-communicable diseases
“The global pattern of death will increasingly be dominated by NCDs; by 2020 coronary heart
disease and stroke are expected to be the leading causes of death and loss of disability adjusted
life years.” (Beaglehole and Yach, 2003,p.903)
Over the last decade deaths due to NCDs have increased in both developed and developing
countries. Worldwide CVD, cancers, chronic respiratory diseases and diabetes mellitus account
for more than 50 percent of all deaths annually (WHO, 2013a). Each year an estimated 36
million people die around the world as a result of NCDs. Approximately 30 million of these
deaths occur in low and middle income countries (WHO, 2013a). They are rapidly replacing
infectious diseases as the leading cause of death in developing countries.
Table 3.1: World estimates of death by cause
NCDs 2000 2011 Change
Share of total deaths (%) 59.6 66.4 +6.8
1. Cardiovascular diseases (CVD) 27.9 30.4 +2.5
2. Cancers 12.4 14.4 +2.0
3. Respiratory diseases 7.5 7.1 -0.4
4. Diabetes 1.9 2.6 +0.7
44
Source: Adapted from WHO (2013a) Global Summary estimates
CVD has the fastest growing rates of mortality worldwide (see Table 3.1). In developed
countries, mortality due to CVD is thrice as high as that due to malaria, tuberculosis and
HIV/AIDS combined in developing countries (Suhrcke and Urban 2006, p. 2). They, and NCDs
in general, reduce both the quality and years of life. The great difference in life expectancy in
Central and Eastern Europe during the 1900s has been attributed to the high rates of CVD which
are associated with the “distortion of the structure of age specific mortality” (Caselli et al., 2002,
p. 19). In Eastern Europe this trend reversed male life expectancy during the early 1990s to that
of its 1950s level.
While the data and literature for the assessment of the economic burdens of NCDs in the
developed world is widely available. The same cannot be said about the low and middle income
economies even though they account for the greatest proportion of mortality.
3.3.1 Non-communicable diseases in Latin America and the Caribbean
NCDs are responsible for three quarters of all deaths and two thirds of all disability adjusted life
years (DALYs) lost in LAC (World Bank, 2014a).11 The main causes of death in LAC are due to
CVD and cancers (World Bank, 2014a). In the year 2000, 51 percent of all deaths in the
Caribbean were due to heart diseases, diabetes, stroke, cancer and hypertension (Abdulkadri et
al., 2009, p. 176). By 2007, the region recorded its highest rate of mortality due to NCDs.
According to the Pan American Health Organization (Pan American Health Organization, 2013),
this included 22,000 premature deaths which occurred in persons below age 50 as a result of
diabetes mellitus alone. This has resulted in LAC having one of the highest percentages of deaths
due to NCDs among the developing regions (see Figure 3.3). The increase is projected to
continue as the region’s ratio of mortality due to injuries and NCDs compared to infectious
diseases will rise by 2020 from 2.2 to 8.1 (Perel et al., 2006).12
11 A Disability Adjusted Life Year (DALY) is a healthy life year lost (quoted in Bloom et al., 2011, p. 7). The WHO (2011) defines DALYs as “The sum of years of potential life lost due to premature mortality and the years of productive life lost due to disability.” 11 LAC’s epidemiological transition is fuelled by the challenges of globalization and its ageing population which is expected to double to approximately 10 percent by 2025.
45
Figure 3.3: Cause of death by region
Source: Adapted from WHO, 2008 cited in UN (2011:p xii)
The high rates of NCD related mortality have also caused an increase in the region’s disease
burden making it comparable to that of the OECD countries (World Bank, 2014a, p. 27). For
instance Guyana, and Trinidad and Tobago are two of the few countries in the world that have in
excess of 300 deaths per 100,000 due to diabetes; in Brazil across every income group more than
20 percent of the population suffers from an NCD; Chile and Argentina have the highest NCD
mortality throughout the region; and in Belize the prevalence of newly diagnosed cases of
diabetes mellitus and stage 1 hypertension is as high as 5 and 10 percent respectively (World
Bank, 2014a). Further, the NCD related mortality rate rise disproportionally across countries in
the region. This is also evident in the ten sample countries examined. In Antigua and Barbuda the
rate rose from 63 percent in 1997 to 72 percent in 2003 while St. Vincent and the Grenadines
recorded a steep increase from 49 percent to 65 percent during this same period.
In the Caribbean hypertension, which is the number one cause of heart diseases, is the third
leading cause of death in females and the fourth in males (Abdulkadri et al., 2009, p. 176). The
incidence of hypertension in the region is 40 percent in males and 33 percent in females (World
Bank, 2014a, p. 56). Estimates from the Caribbean Community (CARICOM, 2011) show that in
0%
20%
40%
60%
80%
100%
World AfricaDeveloping
OceaniaAsia
LatinAmericaand the
Caribbean
Perc
ent
Regions
Injuries
NCDs
Communicable
46
2000 hypertension contributed to approxiametly 425,000 deaths in the Cariabbean. According to
the Ministry of Health, 72 percent of all deaths recorded in Guyana are as a result of the four top
NCDs. Hypertension, the most prevalent, accounts for 16.7 percent of death amongst Guyanese
females and 13.3 percent amongst males (Ministry of Health Guyana, 2009, p. 27).
Obesity and overweight in the Caribbean is especially prevalent amongst women at almost 60
percent and 50 percent in men and accounted for 297,000 deaths in 2001 (CARICOM, 2011).
WHO (2008) estimates that most of the LAC countries have average Body Mass Indexes (BMI)
for males and females ranging from 28 to 30 (World Bank, 2014a).13 Farrante et al. (2011) report
that obesity rates in Argentina have grown from 14.6 percent in 2005 to 18 percent in 2009 with
53.4 percent of the population said to be obese (World Bank, 2014a, p. 60). Estimates show that
there seems to be a direct relationship between socioeconomic status in some LAC countries and
the chances of men being obese.
Diabetes is equally a growing problem in the LAC region. There is a growing public health care
bill attributed to the rise in diabetes. In the region, the cost of treatment and care for persons
living with this disease is 2-3 times higher compared to a non-diabetic person (Barcelo et al.,
2003, p. 19). Estimates for the Caribbean show that mortality due to this condition has trended
upward from 1985 to 2004. During this period, the death toll has been consistently higher in
females compared to males. In 1985, deaths due to diabetes in females were 40 per 100,000
(CARICOM, 2011). This figure increased to 79 per 100,000 in 2004. There has been a similar
increase in male death rates from 28 per 100,000 in 1985 to 65 per 100,000 in 2004 (CARICOM,
2011, p. 16).
Cancer is on the rise in the region. In 2000, the incidence of cervical cancer in the Caribbean was
ranked amongst the top four in the world at 35.8 per 100,000. In the case of Guyana the rate was
52 per 100,000, Belize 40 per 100,000, Trinidad and Tobago 34 per 100,000, and Barbados 31
per 100,000. Similarly, the incidence of breast cancer has become more pronounced, where
Barbados had the highest rate (25.5 per 100,000) in 2002 (CARICOM, 2011).
In 2006, the Council for International Development (CID) estimated that four of the leading
NCDs in the Caribbean cost approximately 2.8 percent of the region’s GDP (CID, 2012, p. vi) . 13 The World Health Organization suggests a BMI ranging from 25 to 30 as overweight and more than 30 as obese.
47
Recognizing that much is at stake the CARICOM Heads of State convened the world’s first ever
NCDs summit in September 2007 (2011). They called on the UN to support the cause as one of
global urgency (Chand, 2012). The main output of this summit was the Declaration of Port-of-
Spain. Following this move the UN in 2011then hosted its High Level Meeting on NCDs. These
actions resulted in getting NCD alleviation the deserved position on the international
development agenda.
3.3.2 Risk factors for developing non-communicable diseases
There are several risk factors that make one predisposed to NCDs. Apart from a few exceptions
due to biological and environmental factors, poor lifestyle choices account for the greater
proportion of NCDs. These include use of tobacco, alcohol abuse, physical inactivity and poor
diets which are the four main risk factors (WHO, 2014). These factors are common to a group of
core NCDs. It is a lethal combination of these behavioural factors that is responsible for 80
percent of coronary heart disease and cerebrovascular diseases (WHO, 2012).
Hu (2011) and Shoja et al. (2012) argue that some chronic diseases are in fact transgenerational.
They postulate that the predisposition to genetic factors compounded by exposure to certain
lifestyle and environmental factors can activate an otherwise dormant trigger associated with
chronic illnesses. Their suggestion is that if the genetic exposure is relatively higher than that of
the environmental then the risk of developing certain chronic diseases increases.
Correspondingly, MacFarlene et al. (2009) argue that there are hereditary and environmental
factors promoting type 1 diabetes (cited in Shoja et al., 2012, p. 471).
One may develop an NCD due to occupational (formal and informal) hazards. Chronic
respiratory disease is one such NCD liked to occupational hazards. As recent as the 1980s many
respiratory diseases in the Pacific were attributed to exposure to smoke from open fires (Thaman,
1988). This was due to the fact that an estimated three out of every four households used this
means to cook. Smith (1985) shows that in India women who cook on open fire “…suffer
extreme exposure to smoke pollution equivalent to smoking 20 packs of 20 cigarettes per day”
(Thaman, 1988, p. 214).
Some scholars have justified that lifestyle changes along with ageing and globalization have
direct impacts on the rates of mortality and morbidity due to NCDs. Kapoor and Anand (2002, p.
48
804) write “the epidemiological transition leading to higher prevalence of non-communicable
diseases is associated with overweight and obesity”. According to them, the nexus between
obesity and NCDs is due to urbanization and lifestyle changes related to technology that limit
physical activity. Likewise, dietary choices largely contribute to NCDs. Notwithstanding, they
note that this transition brings with it a dual challenge to policymakers when dealing with
infectious diseases and the overweight and obese who are more prone to chronic and
degenerative diseases.
The World Bank (2014a) asserts that the growing rates of urbanization associated with
globalization has led to the increasing consumption of calories from animal products, sugars and
salt—all of which are associated with increasing levels of diabetes, weight gain, CVD and
cancers. Beaglehole and Yach (2003) asuggest that due to the increasing level of global
integration the risk factors of NCDs have become more prominent in developing countries over
the past two decades. They posit that globalization has a particularly growing impact on health
through the international promotion of the tobacco and alcohol industries.
Use of tobacco
Globally six million avoidable deaths occur each year due to first and second hand tobacco
smoke (WHO, 2013b).14 Not only is tobacco a known health hazard, it is a less well known
contributor to the poverty cycle in developing countries because it is consumed more often by
the poor (Ciapponi et al., 2011 cited in the NCD Alliance, 2014). Expenditure on tobacco
competes with essential goods and services. In 2005, smoking households of Indonesia spent
11.5 percent of income on protein food products and 11 percent on cigarettes. Likewise, in
Southwest China in 2002, rural and urban poor smoking households spent an average of 9
percent of income on cigarettes while expenditure on food and education was reduced (The NCD
Alliance, 2014, p. 1).
Tobacco use is high on the list of risk factors prevalent in LAC. The results of a recently
concluded health and demographic survey in Bolivia, the Dominican Republic, Guyana, and
Peru show that the prevalence of smoking is 35 percent amongst the poorest and 19.6 percent 14 Tobacco accounts for 30 percent of cancers globally, and the annual economic burden of tobacco-related illnesses exceeds total annual health expenditures in low- and middle-income countries (American Cancer Society and World Lung Foundation (2009) quoted in Bloom et al., 2011, p.9)
49
amongst the richest adults (World Bank, 2014a, p. 52). Correspondingly, it was reported in the
Jamaica Healthy Living Survey (JHLS, 2008) that 14.5 percent of the population use cigarettes,
of these most were of lower income brackets (CARICOM, 2011, p. 25).
Alcohol consumption
Alcohol consumption is another major contributor to the growing number of NCDs. Caselli et al.
(2002, pp. 20-21) write: “…since the 1960s, the increase in man-made diseases [alcoholism,
smoking, suicides, homicides, etc.] has played a large part in the deterioration of the health
situation.” Worldwide 2.3 million deaths occur annually due to fatal imbibition of alcohol.
Some of the highest rates of alcohol consumption per capita are recorded in the LAC region.
Belize, Grenada, Guyana and St. Lucia particularly account for the most alcohol consumption
and highest risks to health as a result (World Bank, 2014a). For the region as a whole,
CARICOM (2011, p. 22) estimates that in 2001, alcohol and smoking combined resulted in
505,000 deaths.
Consumption patterns, Culture and Diseases
Consumption patterns, culture, and diseases are interrelated components in the cause of and fight
against NCDs. With the economic transition that coincides with globalization every aspect of a
society changes including social and eating habits. The thrust towards modernization has
inadvertently shifted personal and family values and priorities, transformed cultures and changed
disease patterns (World Bank, 2014a).
The increasing interconnectedness of the global community brings with it economic success that
is associated with access to improved quantity and quality of food. This has resulted in the
‘nutrition transition’ which moves an economy from being nutrient deficient to having adequate
food supply for its populace.
Prior to this transition developing island countries like those in the Caribbean and Pacific with
tropical climates were known for the production of vegetables and citrus fruits. These foods are
associated with lower risks of cancers of the stomach, lung, colon and oesophagus (Sinha and
McIntosh, 1992). In this accord, Thaman ( 1988, p. 220) states “…most rural agriculturalists and
50
fisher folk seem to suffer from few of the nutritional disorder including “… obesity, and other
nutrition-related diseases, such as CVD, hypertension, diabetes[and] cancers…”
With the rise of international food trade, it is no longer customary for the average Caribbean and
Pacific Islander to practice subsistence farming. This has coincided with reduced consumption of
traditional diets of tubers, fruits and vegetable to a shift in the source of nutrients to diets high in
refined sugars, animal products, fats, salt and calories (Rakodi, 2008; World Bank, 2014a) (see
Table 3.2).
Table 3.2: Composition of energy sources (per kilocalorie) in daily diet per capita
1967--1969 1997--1999
Region Vegetables (%) Animal (%) Vegetables (%) Animal (%)
Developing countries 92 8 87 13
Newly industrialized countries 76 24 77 23
Industrialized countries 71 29 72 28
Source: Adapted from Table 2 WHO/FAO (2003, p. 15)
In LAC, the average consumption of required fats is in excess of 160 percent and consumed
sugar is more that 250 percent that of its required portion (World Bank, 2014a). In Barbados and
Jamaica it was reported by the World Bank (2014a) that less than ten percent of the population
gets its daily recommended fruit and vegetable intake. This deficiency of essential nutrients fuels
the region’s high rates of overweight and obesity, which is the third leading risk factor of NCDs.
Most of the unhealthy foods are supplied by fast food restaurants and supermarkets which
according to Hawke (2007) now account for almost 60 percent of food supply in Latin America
(World Bank, 2014a, p. 41). According to the Food and Agriculture Organization (FAO, 2003),
this new consumption pattern has been associated with increasing rates of NCDs (Beaglehole
and Yach, 2003; and WHO/FAO, 2003) including obesity, diabetes, hypertension, heart disease
and some forms of cancers (Sinha and McIntosh, 1992).
51
Socialization and Culture
“In the social sphere, NCD risks are also shared – eating, drinking and smoking habits are
powerfully influenced by social networks” (Bloom et al., 2011a, p.8). Culture and socialization
influence the extent of exposure to these risk factors and how people deal with illnesses. External
influences seem to overpower beliefs and usual ways of life. A survey conducted by Burns and
Pierce (1992) in California show that the smoking prevalence amongst females of Asia/Pacific
decent was 8.9 percent compared to a 19.1 percent in the overall female U.S population (cited in
True and Guillermo, 1996). Tamir and Cachola (1994) substantiate the claim of effects of
external influences by reporting “…that as Asian/Pacific Islander American women become
more acculturated in the U.S, their smoking may increase as they begin to lose the cultural
prohibition against smoking” (True and Guillermo, 1996, p. 104).
In a similar manner, culture influences the response to health care. In the Hispanic subculture,
self-care is administered as remedy for most illnesses because medical professionals are not
trusted (True and Guillermo, 1996, pp. 134-135). A 2005 survey conducted in New Mexico by
the University of Montana showed that health care providers think Latinos are suspicious of
them because they fear stigma. The health care workers asserted that “…Hispanic cultural
heritage and values [are] obstacles to general wellbeing” (Mental Health Weekly Digest, 2007, p.
395). It is for this same reason that many NCDs in LAC go unnoticed or unreported (World
Bank, 2014a, p. 30). Caribbean islanders especially have a culture of traditional herbal medicines
to treat any signs of illness in the family.
The South American Center for Cardiovascular Health (SACECH, 2013) estimates that if the
region continues its current trend in risk factors mortality due to ischemic heart disease and
stroke will increase by an estimated 145 percent during 1990 to 2020. This is in comparison to
28 percent for women and 50 percent for men over the same period in developed countries. This
presents a social and economic challenge because the loss and permanent disabilities that result
from deaths due to these diseases reduce productivity (Hamoudi and Sach, 1999) and can retard
growth.
Given these risk factors and the threat of lower growth there should be more strategically
designed mechanisms for dealing with NCDs. The World Bank (2014a) reiterates the two main
52
known facts about NCDs. First, these diseases are almost always avoidable. Second, the role of
public policy is crucial in reducing their prevalence. In this vein, it notes “…a large share of non-
communicable diseases are preventable, because they result from known determinants that can
be modified through public policy” (World Bank, 2014a, p. 39). The merit of public policy to
curb the effects of risk factors was proven in Eastern Europe where the anti-alcoholic campaign
spearheaded by president Mikhail Gorbachev from 1985 to 1987 coincided with increased male
life expectancy (Caselli et al., 2002, p. 18). There is evidence that suggests interevening to
reduce NCDs presents a viable economic opportunity. Estimates from the WHO find that NCDs
can be alleviated by investing as little as US$0.40 per person annually in low and middle income
countries to combat and avoid them all together (Bloom et al., 2011, p. 5).
Chand (2012) posits that countries like China with large balance of payments surplus would be
greatly affected by NCDs. He contends that the growing health care costs in low and midddle
income countries would reduce consumption demand for China’s exports as persons would be
forced to divert income to meet unplanned medical expenses. Being cognizant of this, China has
offerred health insurance to those affected by NCDs. Chand’s claim is further substantiated by
Beaglehole et al. (2011) who find that for every $1 invested in the fight against NCDs, $3 to $10
are likely to be gained (cited in Chand, 2012, p. 4). In the case of China this could translate to
about $10.7 trillion (68 percent of its 2010 GDP) (Chand, 2012, p. 4).
Reversing the negative impact of NCDs will take time and commitment. These diseases take
many years to develop, thus curtailing their future threat implies adjusting current risk factors.
Adequate policies can result in many saved lives and financial resources which can contribute to
economic growth.
This re-emphasizes the need for more substantive research focused on developing countries to
generate knowledge-based policies that can mitigate the adverse effects of NCDs. As such, the
following section shows the niche that exists for research in regions like LAC and the Pacific
that share similarities. It then presents the conceptual framework through which NCDs affect
growth and a review of some empirical works that have estimated the economic burden of these
diseases.
53
3.3.3 Addressing non-communicable diseases through research transferability
Deaths due to NCDs in at least 12 Pacific Island Countries (PICs) are in excess of 70 percent
(Council for International Development, 2012, p. vi). Yet, only a few studies, e.g., Gani (2009)
and Maharaj (2011), have invesigated the economic impact of NCDs in this region. Stuckler
(2008, p. 276) projects that the Pacific (231 per 100,000) and Latin America (162 per 100,000)
will have the highest rates of mortality due to NCDs amongst all other regions during 2002-
2030.
Secretariat for the Pacific Community (SPC, 2010) reports that “…the majority of the adult
population in most PICs have a high risk of developing NCDs” (SPC, 2010, p. 27). The
prevalence rates of smoking, drinking, physical inactivity and diabetes mellitus are estimated at
an alarming 70 percent, 75 percent, 70 percent and 16 percent respectively in some PICs. In
these countries, an estimated 60 percent to 75 percent of the populace is overweight with at least
four countries having more than half the adult population being obese.
In Kiribati [formerly the Gilbert Islands and known for its tobacco trade in the 19th century] two
out of every three persons smoke daily (Council for International Development, 2012). As recent
as 1985 the Vanuatu NCDs survey conducted by its Ministry of Health in collaboration with the
WHO found that the island nation was relatively underexposed to the any significant levels of
NCDs. Almost three decades later, 70 percent of all deaths are now due to these diseases while
95 percent and 90 percent of adult females and males respectively display at least one of the
preventable risk factors for NCDs (Council for International Development, 2012). Fifty percent
of the population of Solomon Island is said to have at least three out of the five risk factors
associated with NCDs. In Tonga, the Ministry of Health (2010) reported that NCDs’ prevalence
was 18 percent in 2004, up from its 1973 value of seven percent and has coincided with a five
and three-year reduction in male and female life expectancy respectively (CID, 2012).
Fiji has one of the highest mortality rates due to diabetes in the Pacific, recording 4,537 deaths
due to NCD related illnesses in 2010 (SPC, 2010; Ministry of Health, Fiji, 2010). According to
technical officer for nutrition and physical activity, Dr Temo K Waqanivalu, of the Office of the
World Health Organization in Suva, in Fiji premature deaths due to NCDs have resulted in less
than 16 percent of Fijians living beyond 55 years (Parry, 2010). These recent evidence of the
54
state of health in the Pacific has led to renewed calls for regional action through the June 30,
2011 issuing of the ‘Honiara Communique on the Pacific NCD Crisis’.
Small island nations in the LAC and the Pacific regions stand to gain from each other through
collaborative research and sharing of best practices to inform public policy because risk factors
and mortality rates are very similar. This reiterates the need for research within and across these
regions.
3.4 Conceptual framework and empirical evidence: Non-communicable diseases-growth nexus
“NCDs reduce productivity, curtail economic growth, and pose a significant social challenge in
most countries.” (United Nations, 2011a)
It is argued that NCDs affect productivity and economic growth (Suhrcke and Urban, 2006). In
order to assess these effects there should be a conceptual framework through which the path is
mapped (see Figure 3.4). Ill-health caused by disease resulting in increased rates of morbidity
and premature mortality lowers labour supply, labour productivity and human capital
accumulation while raising health care expenditures (Suhrcke and Urban, 2006; and WHO,
2009). Barro (2013, p. 327) argues that increasing mortality and diseases have a direct impact on
productivity as they raise the effective rate of human capital depreciation and slow the process of
human capital accumulation.
Persons with NCDs have shorter durations in the work force due to increased likelihood of
mortality and morbidity. For example, in Brazil and Chile persons affected by NCDs reduce their
labour force participation rates by an estimated 5 percentage points (World Bank, 2014a). This
reduces personal earnings, consumption and welfare in general (Suhrcke and Urban, 2006; and
WHO, 2009).
The fact that NCDs are long term may cause increases in out-of-pocket health care costs which
inturn increases the likelihood of financial catastrophe (Xu et al., 2007, 2010) and poverty
(Nikolic et al., 2011). These costs equally affect savings and can lead to liquidation of fixed
assets (WHO, 2009, p. 5) to finance health care bills, especially in low income households.
Firms’ and public health care costs rise (Matthews, 2013) resulting in reduced profits (Chadha et
55
al., 2007), lower government revenues from taxes (Englegau et al., 2011), higher labour turnover
rates and training costs (Nikolic et al., 2011).
The impacts of mortality and morbidity due to NCDs are likely to be more pronounced in low
and middle income countries as they account for the highest proportion of deaths due to NCDs.
Added to this is the fact that more than 40 percent of these deaths occur in persons within the
working population (Suhrcke et al., 2006). This poses a challenge as the production processes in
these countries are highly labour intensive. This great loss of human captial and labour supply
may be curtailed if preventive health care policies are implemented and closely monitored.
However, there needs to sound research to quantify these impacts.
Figure 3.4: Linking Non-communicable to economic growth
Source: Created by author. (Arrows indicate direction of flow)
There are three common approaches to quantify the extent of losses due to diseases. These
include:
1. The full income approach which adds potential health benefits from preventive care to
national output.
2. Cost of illness (COI) which calculates direct and indirect medical and opportunity costs
associated with the diseases.
Lower human capital
accumulation NCDs
Low saving
Low capital/Investment
Low income
Low productivity
Poor diets
Reduced labour force participation
56
3. Value of lost output (VLO)/Growth accounting method that estimates portion of output
lost through human capital or labour supply due to the costs NCDs impose.15 Here NCDs
are assumed to have a negative impact on both labour and capital.
Each of these methods varies in their application and has inherent weaknesses but there is a
general consensus that NCDs have a substantial impact on output (Nikolic et al., 2011, p. 6).
Still, caution should be exercised when comparing estimates derived from these different
approaches.
The COI estimates the direct and indirect costs of disease and value of income foregone. These
estimates tend to overestimate foregone income and underestimate the value of lost human
capital (WHO, 2009, p. 4). Additionally, some theorists without showing causality calculate
these costs and estimate them as a portion of GDP to conclude that they reduce output.
Studies investigating the causal link between NCDs and economic growth in developing
countries are exceptionally few. The evidence is even scarcer for countries in Latin America and
the Caribbean even though there has been a growing prevalence of NCDs in this region.
For the selected sample group there has been a consistent increase in mortality due to cancers,
diabetes mellitus, CVD and chronic respiratory diseases from 2000 to 2007. However, a plot of
GDP growth rates against these rates seems to indicate no distinct correlation (see Figure 3.5).16
15 This thesis makes use of this approach by employing regression analysis. 16 This relationship is formally verified by the use of econometric analysis in Chapter Four.
57
Figure 3.5: Non-communicable diseases and GDP growth in Latin American and
Caribbean economies (1997-2009)
Source: Created by author based on data from World Bank online database (2014b) and PAHO Regional Health
Observatory for the ten sample countries only.
3.5 The empirical evidence of the economic impact of non-communicable diseases
This subsection reviews some of the works done in the past to estimate the economic impacts of
of NCDs. Included in the review are panel data, cross section and time series studies. The aim is
to highlight these various approaches and their findings in order to validate the approach of this
thesis and form a benchmark for its findings and conclusions.
Abdulkadri et al. (2009) use the COI approach to estimate the economic cost of diabetes and
hypertension in the Bahamas, Barbados, Jamaica, and Trinidad and Tobago during 2001. They
measure direct costs, indirect costs and the impact of premature death and morbidity on human
capital in terms of earnings foregone due. The estimates show that Jamaica and Barbados spent
US$487 million and US$111 million respectively with the highest portion allocated to cost of
medication. In the case of the Bahamas, total cost amounted to US$73 million with diagnosis as
the most expensive cost. Trinidad and Tobago had the the highest bill of US$717 million with
the greatest share attributed to the cost of morbidity. They find that the cost of the two diseases
ranged from 1 percent of GDP in the Bahamas to 8 percent in Trinidad and Tobago.
-3-2-101234567
0
10
20
30
40
50
60
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Perc
ent (
%)
Perc
ent (
%)
Years
NCD Mortality Rate Growth
58
Barcelo et al. (2003) employ the COI method to estimate the disease burden of diabetes in LAC
for the year 2000. They estimate that in 2000 the region lost 339,035 lives below the age of 65 to
the disease. This was equivalent to an excess of US$65 billion in direct and indirect costs. Loss
due to temporary and permanent disability amounted to US$51billion and 12,835,788 productive
life years.
Matthews (2013) reports that public expenditure per diabetic patient in the Organization of
Eastern Caribbean States (OECS) could range from US$326 to US$776 per year. The burden of
NCDs in St. Lucia is estimated per person at an annual cost of US$1,320 which is approximately
25 percent of per capita income (cited in Matthews, 2013, p. 6).
These studies are point in time snapshots and therefore lack sufficiency to induce policy response
due to short time and small sample size. Additionally, no inference can be made about the causal
links between the amounts spent on care and treatment of these diseases and worker productivity.
The use of regression analysis and VLO give a better understanding of the direction and
relationship of NCDs and growth.
Stuckler (2008) investigates the dual relationship between NCDs and growth. First, he
establishes the link from economic growth to NCDs. Data for male mortality rates due to heart
diseases are regressed on the growth rates of per capita income, population ageing, foreign direct
investment (FDI), market integration and urbanization for a group of 56 countries including the
OECD. His results indicate that there is a significant impact of all these variables on heart
diseases and NCDs in general. An interesting finding is that the impact of economic outcomes on
the rate of morality is thrice that of ageing. This gives credence to Omran (1971) theory by
showing that as poor countries become more integrated and experience higher growth,
urbanization and FDIs they become more susceptible to CVDs and other NCDs. Stuckler also
finds that economic growth reduces almost 0.05 percent for a 10 percent increase in the mortality
rate of those aged 15 to 64 afflicted by NCDs. His estimates for Latin America for 2002 to 2030
suggest at least a 2 percent reduction in growth rates annually due to NCDs.
Maharaj (2011) models this two way relationship by using data on stroke and socioeconomic
variables for Fiji. The estimation is based on data for the year 2001. He adopts a probit model
approach and finds that males have a 25 percent higher risk of suffering a stroke. This risk is
59
even higher if an individual smokes and consumes alcohol. Additionally, using the discounted
value of foregone income and healthy life years lost due to premature stroke mortality amongst
persons age 15 to 64, he finds a loss of US$5.31 million. This he apportions to an equivalent of 1
percent of Fiji’s central government’s revenue and 9.7 percent of the Ministry of Health’s 2001
budget.
Bloom et al. (2011) use both the COI and VLO approaches to estimate the losses due to diabetes,
cardivascular diseases, chronic respiratory diseases and cancer for a group of 169 countries.
They find that for those classified as low and middle income approximately 14 percent (0.7
percent per annum) of their GDP will be lost over the period 2011-2030. Results of the COI
approach indicate that the direct and indirect costs associated with diabetes in 2010 amounted to
US$500 billion worldwide with high income countries bearing 90 percent of this cost.17 These
costs are projected to further mushroom to US$745 billion by the year 2030 (Bloom et al., 2011).
However, middle income countries will bear a rapidly increasing share of the bill by 2030 as
diabetes related disability costs will quadruple. They estimate that Brazil will lose almost US$72
billion in medication costs and productivity decline due to diabetes, coronary heart diseases,
stroke and hypertension.
Abegunde and Stanciole (2006) use the VLO approach for nine countries during 2005-2015 to
show the negative impacts of heart diseases, stroke and diabetes on economic growth. 18 They
highlight that while there is need for the issue to be more aggressively attacked in middle and
low income countries, there is a double jeopardy faced by these countries when dealing with
chronic and infectious diseases with limited public resources. They estimate potential losses if
the epidemic goes unnoticed by policymakers and potential gains from controlling them through
intervention. The authors show at the household level how savings and investment are reduced
on account of treating these diseases. Their estimates suggest that in 2005 most countries lost
less than 0.5 percent of GDP with the exception of the Russian Federation which lost 1percent.
As more people die of these illnesses the losses are projected to rise in 2015 to as much as 1
percent of output for the rest of the group and 5 percent in the Russian Federation.
17 Based on Bloom et al (2011) COI estimates 18 The sample countries are Brazil, Canada, China, India, Nigeria, Pakistan, Russia, United Kingdom, and United Republic of Tanzania
60
Conrad and Webb (2012) attempt to compensate for the limitations in Abdulkadri et al. (2009)
by re-examining the group of Caribbean countries (replacing the Bahamas with Guyana) to
quantify the impact of expenditure on diabetes and heart diseases on economic output. They look
at time series data for the countries from 1990 to 2009 and find a negative and significant impact
on aggregate output in three of the four countries. The findings suggest that output is on average
0.001 percentage points lower due to increasing medical costs of NCDs. The exception where
output was not significantly affected, was Guyana. They rationalised the results for Guyana
based on the fact that females suffer the highest rates of death by NCDs and also have a lower
participation rate in the work force.
Suhrcke and Urban (2006) investigate the impact of CVD mortality on worker productivity.
They use dynamic panel growth regression for a group of low, middle and high income
countries. In the high income economies, they find an inverse and highly significant relationship.
However, contrary to Stuckler (2008) the results indicate that in low and middle income
economies the impact of CVD in the working age population had an insignificant impact on
income growth.
These studies all use different methodologies, samples and proxy measures of NCDs as such the
results warrant caution in cross study comparisons. Given the research question of this thesis the
more appropriate approach to estimate the economic impact of NCDs is taken as the VLO
regression approach.
3.6 Summary and conclusion
This chapter analyzed the connection between economic growth and non-communicable
diseases. It commenced with a brief overview of aggregate health indicators for Latin America
and the Caribbean. Some emphasis was placed on the epidemiological transition and how it
relates to the recent trend in NCDs in LAC. Risk factors and development challenges of NCDs in
the region were also highlighted. The final section of the chapter examined some empirical work
that specifically investigated the costs of NCDs on the economic outcomes.
It was noted that NCDs is not only a challenge to individuals but to the wider society as it strains
private and public resources. Treatment of NCDs diverts income from consumption spending
and lowers savings. These coincide with lower aggregate demand and reduced investment. It can
61
also reduce funding of other productive activites including expenditure on education and
preventive health care. Likewise, with higher rates of premature death and lower labour force
participation caused by NCDs, productivity declines thus growth rates. The next chapter goes in
depth with the data analysis and interpretation of the findings of this thesis.
62
CHAPTER FOUR: EMPIRICAL ANALYSIS
4.1 Introduction
The three previous chapters have outlined the general scope, objectives, importance and
conceptual framework of this thesis. This chapter presents the empirical analysis based on the
data obtained for the ten sample countries. The central purpose is to test the hypothesis and
answer the research question posed in Chapter One. In the first section the data sources and
descriptive statistics, the model and methodology are described. In The second section, the
findings and interpretation of the results are provided.
4.2 Data
The panel dataset covers the period 1997 to 2009 and the sample countries are Antigua and
Barbuda, Argentina, Barbados, Belize, Brazil, Chile, Ecuador, Guyana, Saint Vincent and the
Grenadines, and Trinidad and Tobago. The main data sources are online databases of the World
Bank’s World Development Indicators (2014b), PAHO/WHO Regional Health Observatory, and
the International Monetary Fund/World Economic Outlook (IMF/WEO) (see Table 1 in
Appendix B). All variables in currency units are measured in constant 2005 US$ for uniformity
in cross-country comparisons.
More specifically, the countries’ GDP is used as national output (Y). The labour force is
estimated as the size of the population aged 15 to 64 since actual employment data were difficult
to obtain. This proxy variable is not adjusted for the unemployed or those institutionalized due to
data limitation. Per worker income (y) is therefore estimated as the GDP divided by the labour
force (L).
Similarly data for capital stock (K) are not available. To compensate for this, the World Bank’s
data on gross fixed capital formation (GFCF) are used as a proxy. The perpetual inventory
method (PIM) is used with a depreciation rate of 4 percent in accordance with Senhadji (2000) to
adjust GFCF. Like Senhadji (2000), it is acknowledged that this estimation technique of capital
is not a precise representation since it is difficult, if not impossible, to obtain actual data on
initial physical capital and depreciation rates. Per worker capital (k) is therefore used as
estimated K divided by the labour force.
63
The main variable of interest, NCDs death ratio, was obtained from the PAHO/WHO Regional
Health Observatory. It is measured as the sum of deaths by all ages caused by diabetes, cancer,
CVD and respiratory diseases, divided by total deaths annually. For two of the sample countries
data for years unavailable from PAHO Regional Health Observatory database were obtained
from annual reports from the respective Ministries of Health reports and data extrapolation. Of
the 130 data points used for NCDs mortality a total of 10 points were extrapolated.19 All other
data are figures reported by PAHO/WHO Regional Health Observatory and the respective
Ministries of Health reports. The group of control and instrumental variables was also obtained
from the World Bank database. Summary statistics of core variables and their rates of change are
presented in Tables 4.1 to 4.3.
19The value of y is predicted by using the formula , Where y is the value to be predicted
based on observed values of x. The estimated value of y is found using the closest points (x0, y0) and (x1, y1), such that x0 < x and x1 > x where y0 and y1 are observed.
64
Tab
le 4
.1: S
umm
ary
stat
istic
s of c
ore
vari
able
s (19
97-2
009)
Ant
igua
&
Bar
buda
Arg
entin
a B
arba
dos
Bel
ize
Bra
zil
Chi
le
Ecu
ador
G
uyan
a
St. V
ince
nt
Trin
idad
&To
bago
All
coun
tries
GD
P pe
r wor
ker
(US$
2005
)
Mea
n 18
,321
8,
202
15,9
70
6,62
8 7,
110
10,8
65
4,72
2 1,
829
7,49
1 15
,872
9,
701
Std.
Err
or
6,6
56
5,7
48
1,5
79
1,5
12
1,3
23
2,8
51
880
1
20
2,6
84
11,
376
5,37
1
Min
imum
16
,272
6,
000
15,1
53
5,70
3 6,
644
9,82
3 4,
329
1, 7
65
6,27
6 11
,204
1,
765
Max
imum
22
,540
12
,747
16
,899
7,
147
7,95
8 12
,295
5,
198
1,90
8 8,
666
20,5
37
22,5
40
Estim
ated
Cap
ital
per
wor
ker (
US$
2005
)
Mea
n 11
,732
3,
095
6,58
4 2,
602
2,30
8 4,
558
1,80
2 87
3 3,
870
6,10
4 4,
353
Std.
Err
or
11,5
45
3,38
9 1,
592
1,30
4 66
5 1,
424
696
285
2,28
4 3,
850
3,28
4
Min
imum
7,
036
1,63
4 5,
498
1,64
7 2,
086
3,97
2 1,
508
746
1,64
7 4,
307
746
Max
imum
16
,987
5,
342
7,33
9 3,
366
2,85
6 5,
496
2,26
2 97
2 4,
780
8,07
8 16
,987
NC
D (%
of a
ll de
aths
)
Mea
n 0.
65
0.62
0.
65
0.45
0.
51
0.61
0.
42
0.51
0.
59
0.65
0.
57
Std.
Err
or
0.0
90
0.0
35
0.1
20
0.0
76
0.0
75
0.0
66
0.0
72
0.0
65
0.0
85
0.0
35
0.08
7
Min
imum
0.
62
0.60
0.
61
0.41
0.
48
0.55
0.
38
0.50
0.
49
0.63
0.
38
Max
imum
0.
72
0.64
0.
70
0.56
0.
54
0.63
0.
45
0.56
0.
64
0.68
0.
72
65
Tab
le 4
.2: A
vera
ge g
row
th r
ates
of v
aria
bles
G
row
th ra
tes
Ant
igua
&
Bar
buda
Arg
entin
a B
arba
dos
Bel
ize
Bra
zil
Chi
le
Ecu
ador
G
uyan
a
St.
Vin
cent
Trin
idad
&To
bago
1997
-200
0
GD
P pe
r ca
pita
(%
chan
ge)
2.18
0.
79
3.53
4.
20
0.48
2.
04
-1.0
4 1.
06
5.63
5.
05
Estim
ated
cap
ital p
er
wor
ker (
% c
hang
e)
54.6
9 -2
.69
-0.3
3 4.
98
-2.4
5 -3
.60
-0.4
1 -2
6.03
-7
.77
-12.
11
NC
Dr (
% c
hang
e)
0.11
-0
.08
-0.0
6 4.
47
0.55
1.
54
0.54
0.
92
2.59
-0
.06
2001
-200
4 G
DP
per
capi
ta (
%
chan
ge)
1.52
-0
.29
-1.1
9 3.
25
1.35
2.
71
2.78
0.
98
4.75
8.
13
Estim
ated
cap
ital p
er
wor
ker (
% c
hang
e)
-8.4
1 -1
.94
1.77
-6
.34
-0.1
0 0.
91
3.62
-1
.26
1.65
8.
56
NC
Dr (
% c
hang
e)
1.38
-0
.21
-0.3
1 -3
.05
0.44
0.
47
0.69
-0
.48
0.87
0.
16
66
Tab
le 4
.3: A
vera
ge g
row
th r
ates
of v
aria
bles
G
row
th ra
tes
Ant
igua
&
Bar
buda
Arg
entin
a B
arba
dos
Bel
ize
Bra
zil
Chi
le
Ecu
ador
G
uyan
a
St. V
ince
nt
Trin
idad
&To
bago
2005
-200
9
GD
P pe
r ca
pita
(%
chan
ge)
2.19
0.
54
-0.1
0 -0
.07
2.57
2.
45
1.97
0.
33
2.41
4.
14
Estim
ated
cap
ital p
er
wor
ker (
% c
hang
e)
12.4
1 17
.11
0.45
-2
.74
6.05
5.
76
5.21
3.
03
1.94
-3
.69
NC
Dr (
% c
hang
e)
-0.7
7 -0
.47
0.20
-0
.04
0.59
0.
02
0.53
0.
25
0.02
-0
.34
67
4.3 The Model
The model takes the form of a Cobb-Douglas production function with the Harrod-neutral
technology as follows:
(1)
(2)
Where,
(3)
(4)
In the above model Y represents aggregate output measured as GDP; A represents productivity or
technology; L represents the labour force; K represents capital stock; (1-α) and α are the shares of
labour and capital respectively in output, and the sum of which is restricted to one; and it
represents the ith country at time t = 1,2,3,…,n.
Equation (2) illustrates the production function in intensive form of output per effective worker
derived by dividing both sides of Equation (1) by AL. Equation (3) shows the neoclassical Solow
(1956) assumption that technological change is exogenously determined and grows at rate gt.
Likewise, Equation (4) indicates that labour force is exogenously determined with growth rate nt.
The growth in capital per effective worker illustrated in Equation (5) is based on the saving rate
(s), the depreciation rate (δ), the growth of labour (n) and the growth of productivity/technology
(g).
(5)
Since the change in the capital stock depends on new investment which is a portion of income
(sy) and δ it implies that:
(6)
Equating Equation (6) to zero to show capital in steady state gives:
68
(7)
Substituting k* in the production function to get steady state level of output per worker:
(8)
By logging and first differencing Equation (8) the growth rate of output per worker in the steady
state can be obtained as:
(9)
The parameters δ, s, nt, gt are all constant in the steady state. Therefore per worker output growth
is equivalent to growth in productivity (∆ln A) which is gt.
With the Solow model the exogenous nature of technical progress implies that policies aimed at
increasing growth rates are neutral in the long-run. However, endogenizing the growth of
technical change as suggested by endogenous theorists may affect long-run growth. As such
technical change can be modeled as being a function of some advocated growth enhancing
factors such as health, trade, debt and foreign aid amongst others.
In this way where X is a vector of proposed growth enhancing factors. So that the
estimated model becomes:
(10)
Dividing both sides of Equation (10) by labour force to get per worker level of output:
(11)
Using X as an exponential power to model the effect on productivity is also employed by Bloom
et al. (2001) to demonstrate the impact of life expectancy on productivity, Rao and Singh (2007)
to model the impact of trade openness on growth, and more recently by Chen and Singh (2014)
to estimate the growth impact of foreign aid.
Linearizing Equation (11) using logs gives the level of per worker output as:
69
(12)
It is important to note that Ai,0 is not an actual observation but rather a term partially captured in
the error term of the model that gives an indication of country level productivity across time
(Bloom et al., 2001). The model to be estimated for the sample economies is:
(13)
Transforming Equation (13) by first differencing leads to the derivation of the growth of per
worker income as shown in Equation (14):
(14)
Where,
� y represents real GDP per worker (constant 2005 US$)
� k represents capital per worker (constant 2005 US$)
� NCDr is the NCD mortality ratio (%)
In keeping with the objective of this thesis to assess the impact of mortality due to NCDs on the
level and growth of per worker output the procedures that follow are done
concurrently for both Equations (13) and (14).
4.4 Methodology
4.4.1 Panel Unit Root Test
Testing for stationary of each variable (Zit) being considered must precede the econometric
estimation of the model to avoid spurious estimates. The test of choice is the Breitung (2000) test
where the null hypothesis of each panel series is non-stationarity. Breitung is chosen above
Levin-Lin-Chu (2002) due to its appropriateness for the given sample size and its better
estimation power (Moon et al., 2006). The second moments of the local-to-unity parameters
determine the strength of the Breitung test. One of the assumptions of the test is that an
autoregressive, AR(1) process without deterministic terms is used to generate the data (Kunst et
al., 2011). The detection of any mean autoregressive parameter is made easier for panels where
the alternatives are more heterogeneous (Moon et al., 2006).
70
In the first stage of the Breitung test the residuals êit are obtained from regressing
it
P
ppitipit eZZ
i
���� ��
�1� . P which is the lag order is permitted to vary across cross-section
(Jayaraman and Chen, 2013). Similarly the second stage estimates vit-1 by using
11
1 ��
�� ���� it
L
llitipit vZZ
i
. The third stage involves a forward orthogonalization transformation of
êit and vit which results in ê*it and v*
it respectively. The last stage is to estimate **1
*ititit ve � �� �
which is asymptotically distributed (Kunst et al., 2011). The assumption for the final stage is that
ρ ≤ 1. If the null hypothesis cannot be rejected it means there is a unit root in the panel, that is ρ
= 1. Rejection of the null implies ρ < 1 which suggests that the panel series is stationary
(Jayaraman and Chen, 2013). If Zit is non-stationary, the test for unit root of ∆Zit which is the
first difference of Zit is conducted. If ∆Zit becomes stationary Zit is said to be integrated of order
one, i.e. I(1) (Jayaraman and Chen, 2013).
4.4.2 Panel Long-run co-integration
A co-integrating relationship is said to exist if “…for a set of variables that are individually
integrated of order one, some linear combination of these variables can be described as
stationary” (Pedroni, 1999, p. 655). This step is only possible when the series are found to be
integrated of the same order. Estimating the long-run relationship in panels give the added
benefit of allowing cross country heterogeneity or fixed effects among the members while
accounting for the short run dynamics (Pedroni, 1999). It also allows the co-integrating vector of
each panel member to vary. It is important to correctly specify the equation as assuming a
common co-integrating vector that holds across members may lead to incorrect rejection of a co-
integrating relationship (Pedroni, 1999). Therefore the estimated equation should be:
(15)
The estimation of a co-integrating relationship should be conducted on the residual of Equation
(15) where a number of additional modifications including demeaning can be done to test
stationarity.20 In Equation (15) both the intercept and slope coefficients are allowed to vary to
capture country specific or fixed effects while there is an arbitrary inclusion of a panel specific
20 See Pedroni (1999) for more details on the different methodology to modify error term.
71
deterministic time trend (Pedroni, 1999). The null hypothesis of the residual to be tested is
that of no co-integration. Rejection of this hypothesis can confirm a long-run relationship
between the tested variables.
4.4.3 Endogeneity
After testing for stationarity and long-run co-integrating relationships the test for endogeneity
should follow. It is well known that macroeconomic dynamism can potentially result in inputs
affecting growth of output and likewise growth in output may affect input growth (Bloom et al.,
2001). This randomness of the Xs may also be the result of measurement errors in the proxied
variables or omitted variables that cause correlation with in Equation (13). With this in mind
any estimation of the aggregate production function must test for endogeneity. Distinguishing the
impact of growth on inputs and inputs on growth helps to avoid overestimating inputs’
contributions to the growth in output (Bloom et al., 2001).
If the test for endogeneity confirms its existence then it may be addressed by the use of the
instrumental variables (IVs) in the two stage least square (2SLS) or the generalized method of
moments (GMM) framework. This is necessary as the use of OLS in any estimation where
endogeneity is present will produce inconsistent parameters.
In the scenario where at least one of the regressors (XK) is recognized as endogenous the first
step would be to identify valid IVs to estimate XK. Selection of valid IVs should be guided by
theory and three additional assumptions: 1) IVs are strongly correlated with ; 2) IVs are not
correlated with ; and 3) IVs are not directly correlated with the dependent variable.
(16)
The endogenous variable is then estimated as in Equation (16) using all the exogenous variables
(Xi,i≠k) of Equation (13) as internal IVs along with at least one other external instrumental
variable (ℓ) not included in Equation (13). In the second step the predicted is substituted for
XK in Equation (13) to obtain . The estimated should be uncorrelated with so that the
new parameters used to predict are consistent.
72
In the case where more than one of the Xs are endogenous it is required that the number of
external instruments be equal to or greater than the number of endogenous variables ( ),
i.e. . When it can be said that there is an exact identification of the equation to be
estimated where “…there are as many excluded instruments as included right hand endogenous
variables” (Baum, 2009, p.12). The Chi-square or F statistic can be used to assess the joint
significance of the IVs. The Sargan test is used to test for over-identification under the
assumption of homoscedasticity while the Hansen’s J statistic is applied when there are
heteroscedastic error terms.
The first disadvantage of the 2SLS framework is that selection of weak variables can yield
estimates just as inconsistent as the OLS procedure. This is made even more challenging because
identification of valid IVs may be difficult because “many variables that have an effect on
included endogenous variables also have a direct effect on the dependent variable” (Baum, 2009,
p. 9).
The second critique of the 2SLS method is based on possible heteroscedasticity that results in the
second stage due to regression coefficients that are stochastic. Estimates of the 2SLS with
heteroscedasticity are inconsistent and this presents an even bigger challenge because “…unlike
the case of constant coefficients, it is not easy to solve the problem of generated regressors in
calculating the standard errors of the coefficient estimators (Kim, 2008, p. 168).
Baum (2009) proposes that in such a case where heteroscedasticity exists the use of the IV-
GMM with robust standard errors will produce different and more efficient estimates than 2SLS.
This is especially the case when there is over-identification of the equation (Baum, 2013).
4.5 Empirical findings and interpretation
Breitung Panel Unit Root Test
The order of integration of each of the time series variable is determined by use of the Breitung
unit root test. Table 4.4 summarizes the results and indicates at levels the null hypothesis of non-
stationarity cannot be rejected. The first differences of the variables are tested where all are
found to be stationary. Thus it can be concluded that each variable is integrated of order one, I(1)
at levels.
73
Table 4.4: Results of Breitung Panel Unit Root Tests
Level First difference
Trend Panel means # lags λ-stat p-value Trend
Panel means
# lags λ-stat p-value
ln No Yes 0 1.9977 0.9771
No No 0 -4.9330 0.0000 ln kit No Yes 0 0.1966
0.5779 No No 0 -6.7801 0.0000
NCDrit No Yes 0 1.7861 0.9630
No No 0 -6.0839 0.0000
Test for homoscedascity
After the tests for unit roots are conducted Equation (13) is estimated using the Fixed Effects
(FE) approach. Based on the p-value of 0.0000 and an F (3,117) statistic of 39.22 the overall
strength of the model shows to be significant. Further, a modified Wald test for panel
heteroscedasticity is conducted where the null hypothesis of homoscedasticity is rejected as p =
0.0000. Similarly, Equation (14) is estimated using FE and evidence of heteroscedasticity is
concluded based of the Wald chi (2) statistic of 432.04 and p-value of 0.0000.
In order to correct for this heteroscedasticity a visual observation of the plotted error terms is
done and several dummy variables constructed for outliers. Both equations are then re-estimated
with the dummies, new error terms predicted and retested for heteroscedasticity. The new
equation with the dummies is then tested using a process of linear restriction of the coefficients
of the dummies. This is done by observing instances where coefficients for different dummies
are similar in magnitude and testing their joint significance by the use of F tests. In cases where
coefficients are shown to be equivalent they are combined as a single dummy and retested in the
equations. This process continues until a single dummy (Str) is defined to account for all
structural breaks in the panel. Str is therefore a weighted average that captures all the negative
and positive effects of policies, crises and natural disasters that affected the panel during the
period under investigation. This includes the effects of the 1999 devaluation Brazil’s currency,
the 2002 crises of Brazil and Argentina and the 2008 global economic crisis amongst other
structural breaks. Thus, the new equations to be estimated are:
(17)
74
(18)
The final modified Wald tests for heteroscedasticity fails to reject the null hypothesis of
homoscedasticity in the level Equation (17) at p = 0.2672 and the growth Equation (18) at p =
0.1330. Therefore further estimation can proceed.
Test for heterogeneity
Equations (17) and (18) are first estimated using the random effects generalized least squares
(GLS) method. Based on the p-values of 0.0000 in both instances, the Wald chi-squared test the
null hypothesis of no fixed effects is rejected. Further, evidence of the need to control for
unobserved heterogeneity is confirmed by the Hausman test of specification where the null
hypothesis is that the random effects are as consistent as the fixed effects. Rejection of the null
with chi (2) = 867.16 and p-value of 0.0000 in Equation (17) and chi (2) = 16.69 and p-value of
0.0002 for Equation (18) indicates the fixed effects to be more appropriate. Thus fixed-effects
(within) regression is used for further estimations of both equations.
Panel Long-run co-integration test
Since all the variables are I(1) a Breitung test of the residuals of Equation (16) is applied to
determine the existence of a long-run cointegrating relationship. This is confirmed with lambda
of -2.1205 and a p-value of 0.0170. Therefore estimation of these equations is concluded as non-
spurious.
Test for Endogeneity
Table 4.5 summarizes the results of the Durbin-Wu-Hausman test for endogeneity of the
independent variables. Based on the p-values of the test for Equation (17) the capital stock is
shown to be endogenous while there is evidence of weak exogeneity of NCDr. This leads to a
test of joint exogeneity of both variables which confirms both as endogenous (see Table 4.5).
Thus, the estimation of the final results of level of per worker output uses both as endogenous.
However, the results for the growth equation show growth of both NCDr and k to be exogenous.
This therefore supports the estimation of the growth equation by the use of OLS.
75
Table 4.5 Durbin-Wu-Hausman Test for the Null Hypothesis of Exogeneity
Along with the included variables of Equations (17) and (18) external IVs are used to detect if
there is a problem of endogeneity. The validity of the external IVs is tested by use of the Sargan
over-identification test (see Table 4.6). These instruments are correlated with each of the
endogenous variable and jointly have significant explanatory power since the null of over-
identification is not rejected at the five percent level of significance.
For the individual tests of ln k the identified IVs are past income and current lending
rate of commercial banks (interestit). It is rational to assume that ln yi,t-1 is linked to capital
accumulation since a portion of income saved last year may be used to fund this year’s
investment. Closely linked to the level of new investment is the interest rate which can be used
as the cost of capital. The higher the lending rate the lower the rate of capital accumulation. For
the test of ∆ln k the IVs are the growth in per worker income for the previous year
and the growth of the saving ratio . These are likewise justified using the
rationale outlined above.
Variable χ2 stat p-value
Test for individual endogeneity
ln k 22.9600 0.0000
∆ ln k 0.0010 0.9745
NCDr 13.6190 0.0002
∆NCDr 1.2420 0.2652
Test for joint endogeneity
ln k and NCDr 64.4450 0.0000
∆ln k and ∆NCDr 1.2500 0.5352
76
Table 4.6 Sargan Test for the Null Hypothesis of Over-identification of External Instruments
Variable External instruments χ2 stat p-value
Test for individual
endogeneity
ln k 3.2560 0.0712
∆ ln k 1.0530 0.3048
NCDr 0.1320 0.7166
∆NCDr 0.0790 0.7788
Test for joint endogeneity
ln k and NCDr 2.5040 0.2859
∆ln k and ∆NCDr 0.3830 0.8256
A combination of the portion of health care expenditure (Private) funded through out-of-pocket
finances, the saving ratio (Savr), the percentage of population in urban areas, and previous
income are used as IVs for NCDr and ∆NCDr. All these variables have been linked to NCDs
prevalence (refer to Chapter Three). The literature shows that industrialization and urbanization
are linked to chronic diseases such as respiratory infections (see e.g., Elkins, 2008; Drabo, 2010).
The portion of health care expenditure funded from previous savings and current out-of-pocket
finances can also impact the level of diseases and mortality rates.
Table 4.7 shows the results for NCDr in the first stage of the IV approach. The estimation shows
that private out-of-pocket health care cost has a positive and significant impact on the NCD
mortality ratio. It indicates that a 1 percentage point increase in the out-of-pocket cost ratio will
likely lead to an approximate 0.4 percentage point increase in the NCD mortality ratio. These
estimates take into consideration the endogeneity of both capital stock and out-of-pocket cost as
verified also by the Durbin-Wu-Hausman test (see Table 4.7). The use of an additional IV,
calories (supply of daily kilocalorie per capita) also indicates a significant and positive
relationship. This concurs with the literature that shows causal links between calorie intake and
the likelihood of developing an NCD. These instruments are jointly significant based on the
Sargan test p-value of 0.48. The combination of the IVs and external instruments explain
approximately 50 percent of the variations in the NCD mortality ratio. The strength of the model
is further validated by the F test.
77
Table 4.7: First stage IV estimates for NCD mortality ratio
Coefficients (z-
statistics)21
time 0.240 (2.78)*
Str -2.156 (-9.25)*
ln k -4.466 (-2.12)*
0.454 (3.75)*
17.405 (2.38)*
F statistic (p-value) 20.86 (0.00)
R2 0.423
Sargan χ2 stat (p-value) 0.498 (0.48)
Durbin-Wu-Hausman χ2 stat (p-value) 11.675 (0.003)
Estimating the effects of NCDs on the level and growth of per worker income
Based on the results of the tests for endogeneity the use of 2SLS is employed to estimate these
effects for the level and growth of per worker income respectively:
(19)
(20)
where k is explained by preceding year’s output per capita and interest rate; NCDr is explained
by level of private-out-of-pocket costs and caloric intake.
The results of Equations (19) and (20) are summarized in Table 4.8 using (i) the 2SLS, (ii) IV-
GMM, (iii) dynamic panel data (DPD), and (iv) the FE estimators. These different estimation
techniques are used as a check of robustness. Further to the variation in estimation techniques,
other variables are tested in both the level and growth equations for this purpose (see Table 4.9).
The tested IVs are used throughout for the various estimation techniques.
21 * indicates 1% level of significance
78
Results and Interpretation
Per capita income level
Equation (19) is first estimated without a time trend and all included variables are shown to be
significant. However, this estimation proves to be inappropriate as the joint significance of the
variables is rejected based an Fstatistic of 4.21, low explanatory power of the R2 and an extremely
high (α=0.99). A time trend is necessarily included to capture the effects of change in technology
(TFP) over time (Bloom et al., 2001).This improves the model’s fit with R2 > 0.30 and marginal
changes to the coefficients of the structural break dummy and NCDr. The coefficient of the time
trend indicates that change in TFP amongst these countries occurs at approximately 0.03 percent
annually and is highly significant (see Table 4.8).
As both k and NCDr are proven to be endogenous, the instrumental variables estimators,
including (i) 2SLS, (ii) IV-GMM, and (iii) DPD, are employed to control for potential biases (see
Table 4.8). Estimations based on (i) and (ii) with the use of robust standard errors to control for
arbitrary heteroscedasticity produce very similar results. The estimated α is 0.03 higher in (ii)
compared to (i) though both measures are marginally in excess of the stylized 0.33. This is
potentially due to the exclusion of human capital in the form of education which is as a result of
insufficient data. However, both produce coefficients for NCDr that are highly significant at the
1 percent level of significance and in expectation of the a priori of a negative effect. Likewise,
the coefficient of the structural break dummy is significant in (i) and (ii) and can be interpreted
as the net effect of the weighted average of shocks that affect the long-run equilibrium in the
sample countries. These include policy changes, natural disasters and cross-country contagion.
Application of the Hausman test for specification between (i) and (ii) where the null states (i) to
be the consistent estimator produces χ2 = 2.73 with p = 0.2554. This indicates that estimates
based on (i) are more appropriate thus it is used for further analysis.
To further verify the effects of deaths due to NCDs on level of per worker income a third
specification is explored. The third estimation (iii) DPD also produces satisfactory results. The
NCDr coefficient reduces by 0.02 and the share of α = 0.17 albeit both remain statistically
significant at the 5 percent level. The coefficient of Str also remains significant but has a smaller
value (see Table 4.8). These estimates are also robust to arbitrary heteroscedasticity. The model
79
is correctly specified and estimates from the Arellano-Bond test of serial correlation suggest that
the null hypothesis of no autocorrelation cannot be rejected at p = 0.11.
Robustness test
Re-estimation of (i) and (iii) with additional explanatory variables debt-to-GDP ratio and the
inflation rate is done as a robustness test (see Table 4.9). Both variables have the expected
negative signs but only debt is significant at the 10 percent level. The coefficient of NCDr in (i)
is slightly higher by 0.002 though still significant.
Estimates in Tables 4.8 and 4.9 using (i) prove to have minimal fluctuations; the only exceptions
being the significant reduction of α from approximately 0.40 to 0.30 and the 0.095 increase in R2
with the inclusion of additional variables. Similarly, the results of (iii) produce satisfactory
estimates of the coefficients with minor fluctuations when additional variables are included and
lower z-values though still significant. The major difference in (iii) with the inclusion of inflation
is the notable increase of α to approximately 0.20.The coefficient of inflation in (i) and (iii) also
proves to be insignificant.
Estimates of mortality due to NCDs using the three different specifications suggest that a 1
percentage point reduction in the mortality ratio will lead to an approximate increase in per
worker income ranging between 0.03 percent and 0.05 percent. Therefore, it can be concluded
that higher NCD mortality rates did lead to lower output in the sample from 1997 to 2009.
80
Table 4.8 Estimates of the relationship between per capita income and deaths due to NCDs
(i)
2SLS
Coefficient (z-statistic)
(ii)
IV-GMM
Coefficient (z-statistic)
(iii)
DPD
Coefficient (z-statistic)
(iv)
FE
Coefficient (t-statistic)
8.64 (6.84)* 5.39 (19.27)* 0.323 (0.63) -0.054 (-3.69)*
time 0.032 (7.16)* 0.031 (7.01)* 0.020 (2.17)** ------
Str -0.137 (-4.90)* -0.127 (-4.82)* -0.081(-3.11)* -0.097 (-13.92)*
----- ----- 0.491 (2.08)** -----
0.397 (3.22)* 0.427 (3.64)* 0.174 (2.05)** ------
-0.055 (-5.51)* -0.052 (-5.31)* -0.033 (2.05)** ------
------ ------ ------ 0.003 (5.19)*
------ ------- ------ -0.013 (-0.23)
No. of countries 10 10 10 10
Total no. of observations 115 115 120 120
Wald chi sq (p-value) 898,390 (0.000) ----- 777.09 (0.000) -----
Centered R2 ------ 0.336 ------ -----
R2 (Within) 0.328 ----- ------ 0.715
Root MSE ------ 0.099 ------ ------
F statistic 38.87 23.77 ------ 89.33
p-value (F statistic) 0.000 0.000 ------ 0.000
Sargan Test p-value (over-identification)
0.2859 0.2554 1.0000 -------
Note: * shows variables are significant at the 1% level, **significant at 5% and ***significant at 10%.
81
Table 4.9 Estimates of the relationship between per capita income and deaths due to NCDs – Robustness test
(i)
2SLS
Coefficient (z-statistic)
(iii)
DPD
Coefficient (z-statistic)
(iv)
FE
Coefficient (t-statistic)
9.794 (6.42)* 0.534 (0.43) -0.046 (-3.30)*
time 0.032 (6.03)* 0.018 (1.95)*** ----
Str -0.138 (-4.91)* -0.079 (-3.01)*** -0.090 (-28.10)*
----- 0.474 (1.95)*** -----
0.302 (2.30)* 0.198 (1.91)*** -----
----- ----- 0.003 (5.07)*
-0.057 (-5.09)* -0.030 (1.81)*** -----
----- ----- -0.007 (-0.07)
Inflation -0.0003 (-0.31) -0.0004 (-0.57) -0.0003 (-1.40)
Debt -0.061 (-1.73)*** ----- ----
∆Debt ----- ----- -0.046 (-2.31)**
No. of countries 10 10 10
Total no. of observations 115 120 120
Wald chi sq (p-value) 1.03e+06 (0.000) 808.48 (0.000) -----
Centered R2 ------ ------
R2 (Within) 0.423 ------ 0.745
Root MSE ------- ------ -----
F statistic 34.43 ------ 11032.99
p-value (F statistic) 0.000 ------ 0.0000
82
Sargan Test (p-value) 0.4646 1.0000 -----
Note: * shows variables are significant at the 1% level, **significant at 5% and ***significant at 10%.
Per capita income growth
Equation (20) is estimated using (iv) FE since both ∆ln k and ∆NCDr are found to be exogenous.
The explanatory power of Equation (20) using ∆ln k, ∆NCDr and the structural break dummy is
significant suggesting that jointly these variables account for 71.5 percent of the variations in per
capita income. Both coefficients of ∆ln k and the dummy are significant and have their expected
signs. The coefficient of ∆NCDr though negative is statistically insignificant (see in Table 4.8).
A robustness test of Equation (20) is conducted with the inclusion of inflation and the growth
rate of the debt-to-GDP ratio. These increase the explanatory power of the model by 0.03 as the
coefficient of ∆ln k remains unchanged and statistically significant. While the change of the
debt-to-GDP ratio and the dummy also show to be significant, inflation and ∆NCDr are both
insignificant. It therefore cannot be concluded that mortality due to NCDs in the sample period
has affected growth rates of per capita income.
4.6 Summary and conclusion
This chapter presented the methodology and empirical findings of this thesis. It demonstrated the
results of the various tests and estimation techniques used to assess the impact mortality due to
diabetes, cardiovascular diseases, cancer and chronicle respiratory diseases have on per worker
productivity in Latin America and the Caribbean.
It was determined that the level of per worker capital stock and the NCD death ratio are
individually and jointly endogenous. This rendered inappropriate the use of OLS technique. As
an alternative route, three different techniques (2SLS, IV-GMM and DPD) were used to estimate
the effects of NCD related mortality on the level of per worker income. The results of all three
techniques show a negative and statistically significant relationship between the two. It was
found that a 1 percentage point reduction in the NCDs mortality rate could potentially lead to an
annual increase in per worker income ranging from 0.03 percent to 0.05 percent.
83
Conversely, changes in the NCD ratio and the capital stock are both exogenous. As such the
fixed effects estimator was used to quantify the impact changes in NCDs ratio have on growth. It
was shown that NCD related deaths had no statistically significant effect on the growth of per
capita income. The inclusion of other variables to further ascertain NCDs effect does not change
this finding. It is worth noting that the debt-to-GDP ratio has both level and permanent growth
effects on per worker income.
Based on the estimation techniques used in this thesis it cannot be concluded that these diseases
affected growth during the sample period. However, there is sufficient evidence to conclude that
they significantly lowered the level of per capita income.
84
CHAPTER FIVE: CONCLUSION AND POLICY IMPLICATION
5.1 Introduction
This chapter summarizes the major findings of this thesis. It commences with a discussion of the
findings and then proceeds to highlight some policy implications for addressing the challenges of
NCDs. It concludes with a summary of the thesis and areas for future research.
5.2 Key findings and discussion
The results of the regression analysis were derived by employing four different approaches.
These were 2SLS, IV-GMM, DPD and FE which showed that during 1997 to 2009 higher ratios
of total deaths due to diabetes mellitus, cardiovascular disease, cancer and chronic respiratory
disease contributed significantly to lower levels of per capita income. Though these diseases
shown a negative effect on per capita income it was statistically insignificant. This leads to the
conclusion that there were effects on the level but not growth of per capita income.
Over the sample period, the average NCD mortality ratio exceeded 50 percent of all deaths in
most of the countries. Five of these countries namely Antigua and Barbuda, Argentina,
Barbados, Chile, and Trinidad and Tobago had ratios greater than 60 percent. The only countries
with ratios lower than 50 percent were Belize and Ecuador. Though these ratios were high during
this period their rates of change fluctuated minimally ranging from a low of 0.2 percentage
points to a maximum of 0.9 percentage points. In the case of Argentina, Barbados, and, Trinidad
and Tobago there was an average reduction in the rate of progression of deaths due to NCDs
ranging from 0.01 percentage points to 0.03 percentage points.
On average the sample group lost 653,846 lives and US$2.3 billion annually due to the four main
NCDs during the period 1997 to 2009. These deaths represent an average of 0.4 percent of the
working age population. With the high rates of mortality this loss of labour supply could
accumulate to greater proportions if the current trend continues. The fact that evidence of the
diseases’ impact is captured in the reduction of per capita income may signal that the reduction
in aggregate output is not fully compensated for in the growth of the labour force. This is a
situation that could have further consequences on social welfare as incomes continue to decline.
85
An additional finding is that the NCD mortality ratio in this sample is positively and significantly
affected by the supply of daily per capita kilocalories and the ratio of out-of-pocket health care
costs borne by households (as reported in Table 4.7). The health care cost funded through private
out-of-pocket finance in these sample countries has averaged 32 percent over the period under
review. The majority of countries had ratios in excess of the 15-20 percent benchmark proposed
by Xu et al. (2010) which could put households at risk of financial catastrophe and/or poverty.
The only exception where the ratio was below 20 percent is Guyana, 16 percent and St. Vincent
and the Grenadines, 17 percent. Estimates from the World Bank (2014b) showed that in 2009
this cost was approximately 55 percent for Ecuador and 43 percent for Trinidad and Tobago. An
annual reduction of 1 percentage point in this ratio over ten years is likely to result in more than
126,000 saved lives. This is done using the 2009 average NCD mortality ratio of 57 percent for
the group as a counterfactual. It does not take into account the potential productivity gains in the
form of added skills and work experience that can contribute to higher levels of per capita
income.
The main concern that arises from these findings is the future impact NCD mortality could have
on growth of per worker income. Indeed in this estimation there is insufficient evidence to
conclude that within the period under investigation these diseases reduced growth of per capita
income. However, a noteworthy point is that the loss of human capital is not taken into
consideration in the measure of NCDs mortality rate. This could account for one possible reason
why there was no evidence of growth effects.
As these diseases take a long time to develop and have an equally long period of morbidity the
impact on growth may not be evident until many years after. As argued by some economists, the
steady state of an economy could take a very long time to be achieved. This may take no less
than two decades in some cases. It is for this reason that phenomena that have transitory or level
effects on income may not have the same effect in the long-run steady state adjustment. This
scenario also gives rise to the fact that the lagged effects of some phenomena like death due to
NCDs may not be transmitted to the economy until several periods after due to extended
morbidity and the intergenerational gap of human capital accumulation that is not captured in the
Solow type models.
86
5.3 Policy implication
Combating the rise of NCDs requires a multifactorial approach. The findings of this thesis show
that indeed there is scope for partnership between individuals and governments to counter this
new challenge of NCDs. There is a need for major lifestyle changes and cost reductions in health
care services.
Individuals’ role in combating NCDs is just as heavily weighted as that of governments’. As
shown by the results, the reduction of calorie intake can contribute significantly to lowering
deaths due to NCDs. It is one’s personal responsibility to eat healthily and engage in lifestyle
habits that help to prolong healthy life years. Daily physical exercise, reduced use of alcohol and
tobacco can also result in improved longevity. This by extension can contribute to higher
incomes as individuals live longer, accumulate more education and skills, and have increased
stints in the workforce. It is therefore important for everyone to take steps in ensuring healthy
habits are adopted.
In the same vein, governments have a responsibility to ensure and promote wellbeing of the
population. As highlighted in the literature review, there are many benefits that accrue from
being healthy. This has been proven by many theorists. Health care service is largely a public
good in many countries. Access to these services is closely linked to disease prevalence and
mortality rate. This reiterates the need for government policies to ensure adequate provision and
delivery of health care services at affordable costs.
Private health care costs in the sample economies affect mortality due to NCDs. Based on other
empirical evidence (see Xu et al., 2007, 2010) these costs can equally lead to poverty. This thesis
shows that as the rate of mortality due to NCDs rise there is a counteracting force that lowers
productivity and per capita income. With this in mind it is pertinent for consideration of these
costs to be regarded by governments when designing strategies and policies aimed at lowering
the incidence, prevalence and mortality due to NCDs.
The results show that reducing the private cost of health care can prove to be a good tool to
directly lower deaths due to NCDs. By extension the reduction in these costs can also be used as
an indirect channel to increase welfare by raising per capita income.
87
In this light, governments have a significant role in assisting to lower these costs. This may be
done either by providing universal health care coverage or facilitating access to private health
insurance (Xu et al., 2010). The chronically ill are faced with higher health care costs as the
diseases are long-term and costs increase due to extended morbidity (Hwang et al., 2001).
Moreover, uninsured persons affected by such diseases face an increase chance of becoming ill,
dying and/or being faced with financial catastrophe. This occurs as there is a dual disadvantage
of suffering from a chronic ailment and being uninsured. The combination of these two
circumstances could result in chronically ill persons being five times less likely to seek medical
attention compared to if they were insured (Hwang et al., 2001).
The threat of increased poverty due to high medical costs of treating a chronic disease is an
additional cause for concern. LAC already records high poverty rate, having in excess of 25
percent of the population living on less than $2 daily in some countries (Godard and Williams,
2003). With poverty there is a compounded downward pressure on income, savings and human
capital accumulation. These are seen as pertinent to achieving growth and if affected could mean
economic stagnation.
Yet, the true economic and social costs of NCDs are not accurately captured because the data
collection for most countries is of poor quality. The governments have a major responsible to put
systems in place to ensure accurate and quality data collection and storage. This can result in an
improvement in estimating the extent to which the cost of treating NCDs and NCD related deaths
affect the economy both on the microeconomic and macroeconomic scales.
5.4 Summary and conclusion
This thesis has focused on the two main concepts of economic growth and health. Economists
have often emphasized the need for economic growth as an important component of
development. The two dominant theories of economic growth, neoclassical and endogenous
growth theories, have advocated different factors and sources that influence an economy to grow
continuously and thus enable development.
In line with the neoclassical growth theory exogenous technical change is promoted as the key to
growth. Alternatively, the endogenous growth theory proposes a number of factors as growth
enhancing, particularly human capital development and knowledge accumulation. Theorists have
88
further proposed health as an important component of human capital. This has led to a recent and
growing body of literature purporting health as crucial to the growth and development process of
an economy. This has further resulted in numerous approaches and measures including life
expectancy, disease prevalence, mortality rates and others to estimate the macroeconomic and
microeconomic effects of health. More so, the use of disease prevalence and mortality rates as
measures of ill-health have been widely applied to study the economic impact of infectious
diseases, especially in developing countries. Most of the empirical works have found a
significant and positive impact of health on growth while a few have reported neutral or
insignificant impacts.
Ill-health in the form of NCDs is currently resulting in more deaths than infectious diseases and
presents a dual challenge to health care systems and economies. Developing countries report the
highest percentages of deaths due to NCDs accounting for more than 30 million of the 36 million
deaths recorded annually in the world. These diseases are increasingly affecting persons below
the age of 64 and present a challenge in both developed and developing economies. The cost of
morbidity and premature mortality due to NCDs affect various aspects of an economy. These
include lower levels of labour supply, labour productivity and human capital accumulation. The
cost of health care also affects household incomes, saving and investment in new capital goods.
Likewise, firms and governments bear an increasing share of these costs resulting in higher
public health bills and reduced outputs and profits in firms. These all accumulate to
macroeconomic losses that may result in future reduction in growth rates.
Recognizing the negative impact NCDs can have on economic outcomes this thesis was designed
to ascertain if mortality due to the four NCDs lowered the levels and growth of per capita income
in ten LAC countries. Most of these countries experienced rising rates of deaths due to NCDs.
These rates also coincided with the low per capita income growth for the sample over the period
under investigation. For most of the economies GDP per capita grew less than 2 percent annually
during 1997 to 2009. The combination of these two scenarios led to the formulation of the
question this thesis attempted to answer.
The empirical evidence of this thesis suggests that if deaths due to NCDs are lowered per worker
income will likely rise. There is insufficient evidence to show that NCD related deaths resulted
in lower per capita income growth in the sample. Thus, it cannot be concluded that the low
89
growth rates were resultant of the growing rates of deaths due to NCDs. However, it is shown
that the level of daily calorie intake increases the chances of dying due of an NCD. Additionally,
policies affecting the portion of private health care cost funded from out-of-pocket expenditure
may have a significant and positive relationship to the portion of deaths due to NCDs. Therefore,
reducing the private out-of-pocket costs is recommended as a means for governments to lower
NCDs death ratio while concurrently increasing per capita income.
5.5 Limitations
There are two limitations of this thesis. The first is the measure of NCDs cost to economies that
was used. This measure (NCD mortality ratio) only accounts for loss due to labour supply which
means that the quality of labour was not captured. The second is due to short sample period. This
was as a result of the inability to access consistent data. Though a time series approach would
have been preferred the data constraints prove this impractical. In an attempt to compensate for
this shortcoming the panel approach was applied.
5.6 Future avenues for research
Based on the fact that this thesis is exploratory, there remains many avenues for further research.
The NCD mortality ratio is merely a measure of units of labour lost. It is not a representative
measurement of total loss due to these diseases. It is therefore recommended that additional
research be pursued in the development of a holistic measure that can capture the loss in labour
supply, human capital and other associated costs due to NCDs.
A better approach to capturing the effect NCD mortality has on per capita growth can be to
consider use of this holistic measure by disease and age specific mortality. Maybe in the next
five to ten years as developing countries adopt better and more standardized reporting
systems/techniques this panel can be extended to reflect a more accurate picture of the growth
impact.
Additionally, based on the premise of the epidemiological transition the reverse of this thesis’
hypothesis can be tested. As shown in the findings both income levels and the NCD mortality
rates are endogenous. This presents a key method to assessing the impact of per capita income
growth on the rates of NCD related deaths.
90
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101
App
endi
x A
Tabl
e 1:
Tr
ends
in th
e de
mog
raph
ic a
nd e
pide
mio
logi
cal t
rans
ition
in L
atin
Am
eric
a an
d th
e C
arib
bean
Perio
d A
vera
ge
1970
-75
1980
-85
1985
-90
1990
-95
1995
-200
0 20
00-0
5 20
05-1
0
Ferti
lity
5.
02
3.93
3.
42
3.02
2.
73
2.53
2.
3
Infa
nt M
orta
lity
(per
100
0)
81
57
47
38
32
26
22
Popu
latio
n gr
owth
2.
41
2.10
1.
92
1.71
1.
55
1.32
1.
15
Life
exp
ecta
ncy
60.9
0 65
.20
67.1
0 68
.90
70.6
0 72
.10
73.4
0
Econ
omic
gro
wth
* 3.
60
1.51
2.
92
3.14
3.
16
3.28
2.
38
Mor
talit
y du
e to
NC
Ds*
-
- -
- 41
.48
50.9
4 47
.7
Cru
de d
eath
rate
(per
100
0)
9.80
7.
80
7.10
6.
50
6.20
6.
00
5.90
Sour
ce: T
able
com
plie
d ba
sed
on e
stim
ates
from
Uni
ted
Nat
ions
(201
1) ,
Wor
ld B
ank
onlin
e da
taba
se, P
AH
O R
egio
nal O
bser
vato
ry.*
Onl
y fo
r the
sam
ple
coun
tries
in th
is
rese
arch
.
102
App
endi
x B
Tab
le 1
: Dat
a D
escr
iptio
n an
d So
urce
s
Var
iabl
e
Des
crip
tion
Dat
a So
urce
GD
P (Y
) A
nnua
l GD
P in
con
stan
t US$
2005
. W
orld
B
ank
Dev
elop
men
t In
dica
tors
(201
4b)
Cap
ital s
tock
(K
) G
ross
fixe
d ca
pita
l for
mat
ion.
W
orld
B
ank
Dev
elop
men
t In
dica
tors
(201
4b)
Labo
ur fo
rce
(L)
Popu
latio
n ag
ed 1
5 to
64.
W
orld
B
ank
Dev
elop
men
t In
dica
tors
(201
4b)
NC
Dr
Ann
ual d
eath
s du
e to
can
cers
, dia
bete
s, ch
roni
c re
spira
tory
dis
ease
s
and
card
iova
scul
ar d
isea
ses a
s a p
erce
ntag
e of
tota
l dea
ths.
PAH
O R
egio
nal
Obs
erva
tory
, M
inis
try o
f
Hea
lth G
uyan
a, M
inis
try o
f Hea
lth T
rinid
ad
and
Toba
go.
Urb
an
Perc
enta
ge o
f the
pop
ulat
ion
in u
rban
citi
es.
Wor
ld
Ban
k D
evel
opm
ent
Indi
cato
rs
(201
4b)
Inve
stm
ent
Inve
stm
ent-t
o-G
DP
ratio
IM
F/W
EO d
atab
ase
103
Tab
le 2
: Dat
a D
escr
iptio
n an
d So
urce
s
Var
iabl
e
Des
crip
tion
Dat
a So
urce
inte
rest
C
omm
erci
al b
anks
’ len
ding
rate
s W
orld
B
ank
Dev
elop
men
t In
dica
tors
(201
4b)
Priv
ate
Out
of
pock
et e
xpen
ditu
re i
s an
y di
rect
out
lay
by h
ouse
hold
s,
incl
udin
g gr
atui
ties
and
in-k
ind
paym
ents
, to
heal
th p
ract
ition
ers
and
supp
liers
of p
harm
aceu
tical
s, th
erap
eutic
app
lianc
es, a
nd o
ther
goo
ds
and
serv
ices
who
se p
rimar
y in
tent
is to
con
tribu
te to
the
rest
orat
ion
or e
nhan
cem
ent
of t
he h
ealth
sta
tus
of i
ndiv
idua
ls o
r po
pula
tion
grou
ps. I
t is a
par
t of p
rivat
e he
alth
exp
endi
ture
.
Wor
ld
Ban
k D
evel
opm
ent
Indi
cato
rs
(201
4b)
Deb
t G
ener
al g
over
nmen
t gro
ss d
ebt-t
o-G
DP
ratio
IM
F/W
EO d
atab
ase
Infla
tion
Infla
tion,
ave
rage
con
sum
er p
rices
IM
F/W
EO d
atab
ase
Savi
ngs
Rat
io o
f nat
iona
l sav
ings
-to-G
DP
Wor
ld
Ban
k D
evel
opm
ent
Indi
cato
rs
(201
4b)