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

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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)

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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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