Demographic factors and economic growth the bi directional causality in south east asia

First, the determination of the impact of a number of the demographic factors on the economic growth by using a various aspect of demographic factors, including: population growth, life

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

DEMOGRAPHIC FACTORS AND ECONOMIC GROWTH:

THE BI-DIRECTIONAL CAUSALITY

IN SOUTH EAST ASIA

BY

VO TAN THANH DIEP

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

HO CHI MINH CITY, November 2015

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

DEMOGRAPHIC FACTORS AND ECONOMIC GROWTH:

THE BI-DIRECTIONAL CAUSALITY

IN SOUTH EAST ASIA

A thesis submitted in partial fulfilment of the requirements for the degree of

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

By

VO TAN THANH DIEP

Academic Supervisor:

PROFESSOR NGUYEN TRONG HOAI

HO CHI MINH CITY, December 2015

iii

ACKNOWLEDGEMENT

Foremost, I would like to express my sincere gratitude to my supervisor, Professor

Nguyen Trong Hoai for his professional knowledge, perceptive guidance and for giving

me valuable opportunities His guidance really helped me for the direction of the research

and writing of this thesis

In addition my advisor, I would like acknowledge the love from my family to me over

the last 24 years A special thank is to my parents for their support throughout my life, to

my sister and my relation in Ho Chi Minh City for valuable support during my studies

Furthermore, I would also like to thank all lecturers and staff at the Vietnam

Netherlands Program and my VNP 20 classmates

Most of all, a special thanks go to my better haft – Nguyen Son Kien - for the

motivation, encouragement and affectionate care that he bring to my life

iv

ABSTRACT

This study has demonstrated new evidence sustaining the idea that variation in demographic factors is an important determinant of growth in per capita income Using an annual panel dataset from 1990 to 2013 at the country-level in the Southeast Asia, this study is conducted to analyze the following key areas in comparing with current literature

First, the determination of the impact of a number of the demographic factors on the

economic growth by using a various aspect of demographic factors, including: population

growth, life expectancy, and age structure Second, the interpretation of the bi-directional

causality among: (i) the population growth and the economic growth; and (ii) the life expectancy and the economic growth Furthermore, the two new econometric techniques, Driscoll and Kraay estimation, and structural equation model, in parallel with the panel regression technique are applied

It is noticeable about the following key contribution, including: (i) the specification

of the various aspects of demographic factors on the economic growth is analyzed in the new context (Southeast Asia) where most countries have experienced the demographic transition, and have received the demographic dividend; and (ii) the worth analysis of the bi-directional causality has been recognized since it is one of the first in its line of current literature that confirms the inverse effect of the economic growth on population growth, and life expectancy simultaneously

Key words: Demographic transition, economic growth, population growth, life

expectancy, age structure, Southeast Asia, Panel data, SEM

v

TABLE OF CONTENT

Declaration ii

Acknowledgement iii

Abstract iv

Table of content v

List of tables viii

List of figures ix

Chapter 1 Introduction 1

1.1 Problem statement 1

1.2 Research objective 3

1.3 Research questions 3

1.4 Research scope 3

1.5 Thesis structure 3

Chapter 2 Literature review 5

2.1 Theoretical literature 5

2.1.1 Key concepts 5

2.1.1.1 Demographic factors 5

2.1.1.2 Demographic Transition 6

2.1.2 Demographic factors and economic growth 8

2.1.2.1 The perspective of Malthusian Regime 8

2.1.2.2 The perspective of Post-Malthusian 10

2.1.2.3 The perspective of Modern Growth Regime 11

2.1.3 Demographic transition and economic growth 13

2.1.3.1 The labor supply mechanism 13

2.1.3.2 The savings mechanism 14

2.1.3.3 The Human capital mechanism 14

2.2 Empirical studies 15

2.2.1 Population growth and age structure 15

2.2.2 Life expectancy 18

2.2.3 Bi-directional causality 19

2.2.4 Determinants of economic growth, population growth, and life expectancy 20

2.2.4.1 Economic growth 20

2.2.4.2 Population growth 21

2.2.4.3 Life expectancy 21

vi

2.3 Hypothesis construction and conceptual framework 22

2.3.1 Hypothesis construction 22

2.3.1.1 Demographic factors and economic growth 22

2.3.1.2 Two-way relationship 24

2.3.2 Conceptual framework 25

Chapter 3 Research methodology 27

3.1 Data 27

3.2 Model specification 29

3.2.1 Model specification for one way effects 29

3.2.2 Model specification for the bi-directional causality 30

3.3 Research methodology 32

3.3.1 Models of panel data regression 32

3.3.1.1 The model of Pooled regression 32

3.3.1.2 The model of fixed effects estimation 32

3.3.1.3 The model of random effects estimation 34

3.3.1.4 Driscoll and Kraay standard errors and panel models 34

3.3.2 The structural equation model (SEM) 36

3.3.2.1 The causal effect and mediate mechanism 36

3.3.2.2 The simultaneous (non-recursive) structural equation model 37

3.3.2.3 The logic of SEM 39

Chapter 4: Empirical results 40

4.1 Overviews of demographic transition in Southeast Asian 40

4.2 Data description 42

4.2.1 Descriptive statistic 42

4.2.2 The possible relationship by scatter 44

4.2.3 Correlation 45

4.2.4 Demographic factors by deciles 46

4.3 Panel data regression 47

4.3.1 Diagnostic analysis 47

4.3.2 One-way direction - Driscoll and Kraay estimation 49

4.4 The bi-directional causality estimation 52

Chapter 5 Conclusions and policy implication 56

5.1 Concluding remarks 56

5.2 Policy implication 58

vii 5.3 The limitation and directions for further research 61 Reference 62

viii

LIST OF TABLES

Table 3.1: Variable descriptions 28

Table 4.1: Summary statistic 43

Table 4.2: Pairwise correlations 45

Table 4.3: Demographic variables by GDP per capita deciles 46

Table 4.4: Variance inflation factor (VIF) 47

Table 4.5: Model comparison 48

Table 4.6: Diagnostic problem 48

Table 4.7: Panel regression 51

Table 4.8: SEM regression 54

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LIST OF FIGURES

Figure 2.1: Life Cycle Income and Consumption 6

Figure 2.2: The process of demographic transition and population growth 7

Figure 2.3: Population growth and food supply 9

Figure 2.4: Population growth and economic growth, in period of 1300-2000 10

Figure 2.5: The exogenous growth model 12

Figure 2.6: The endogenous growth model 13

Figure 2.7: Conceptual framework 26

Figure 3.1: The causal effect and mediate mechanism .37

Figure 3.2: The non-recursive mechanism 38

Figure 3.3: The logic of SEM 39

Figure 4.1: Demographic factors during the period of 1960-2013 41

Figure 4.2: The orientation of age structure in Southeast Asian countries 41

Figure 4.3: The population pyramids in Southeast Asia 42

Figure 4.4: Relationship between economic growth and demographic factors 44

CHAPTER 1 INTRODUCTION

1.1 Problem statement

According to United Nations (2015) the world’s population has nearly doubled over the span of the last thirty years and will boom to over 10 billion by 2050 if the fertility is constant As a result of the linkage between population and both the supply and demand of economic production (Crenshaw et al., 1997), understanding the variation in the factors of population seems to be a necessity for the process of economic development In addition, from the best-known Malthusian theory (Malthus, 1798) to the unified growth theory (Galor, 2011), how the factors of demography affect economic performance has remained

as a controversial issue that is of the growing interest for economists and policymakers From the first demographic transition in history was marked by the declining mortality in Europe around 1800 (Lee, 2003), most of countries in the world has experienced demographic transition in different period during the past two centuries Along with that, there was a huge number of studies, focusing on the influence of demographic change on economic growth In recent decades, Asia, and especially East Asia, were the interesting entities for the investigation of the linkage between demographic factors and economic growth This has portrayed the economic leap forward, which elevated the position of some Asian countries in the world, was contributed by the enormous alteration

in demography Proving that, Boom and Williamson (1998) demonstrated a significant improvement in growth due to impact of demographic change in Asia during the period of

1965 to 1990 However, the situation has changed since the world was diversified into two different demographic regimes: some countries has been taking advantage of demographic dividend, while the others has been facing the aging population (Sanderson et al., 2013)

In fact, Asia was not included in the exception, some countries has been receiving demographic bonus such as China, India On the other hand, some developed countries, like Japan, Korea, Hong Kong, have been facing the phenomenon of population aging since fertility reduced considerably and life expectancy rose steadily (Bloom et al., 2003)

Moreover, the story has been more complex after the Asian crisis in 1997 and financial crisis in 2007 which make the economic growth process more stalled (Bloom and Finlay, 2009) Accordingly, the analysis based on different time periods and regions in Asia may provide the distinct results of the impact of demography on process of economic growth There are several reasons why the Southeast Asia seemed to be an interesting sample

to investigate the relationship between demographic factors and economic growth in this study First, as reported of United Nations (2015), if considering Southeast Asia as a single country, its labor force is in the third place of the world in size, just behind China and India Second, at the crossroads of the aging population in East Asian and the baby boom generation in South Asian, most of the countries in South East have just experienced the demographic transition in the last two decade and have been receiving demographic bonus (Bloom and Finlay, 2009) Third, according to the classification of World Bank, the Southeast Asian countries is relatively diversified from high-income countries, middle-income countries to low-income countries Consequently, the sample from Southeast Asia could show a large variation in data across countries, but the homogenous group of countries with many similar characteristic like climate, culture, history may be observed Furthermore, this study also concerns the bi-directional causality between demographic factors (proxied by the population growth and the life expectancy) and economic growth that has not been clarified in most previous researches (Bloom et al., 2010; Cervellati and Sunde, 2011) Particularly, these papers has just dealt with this simultaneous problem to confirm the effect of demography on growth based on the estimation instrumental variables, yet ignored the possible impact of economic growth on demographic factor Therefore, this study will not only focus on the link between economic growth in Southeast Asia and the demography of this area, but also shed light on the influence from the two factors to each other

In conclusion, although a number for publications have been found in the public domain, this study is different with the conducted researches in the past in the four

fundamental areas First, the influence of demographic factor on economic growth has

been clarified in the new context (Southeast Asia) where the phenomenon of demographic

transition and demographic bonus is coming out (in the period of 1990-2013) Second, a

various aspects of demographic factors are utilized simultaneously, including: population

growth, life expectancy, and age structure Third, the bi-directional causality is interpreted

among: (i) the population growth and the economic growth; and (ii) the life expectancy

and the economic growth Fourth, the two new econometric techniques, Driscoll and Kraay

estimation, and structural equation model, in parallel with the panel regression technique are applied

1.2 Research objective

This study aims to analyze the influence of a number of the demographic factors on the economic growth Accordingly, there are two main objectives have been analyzed as following:

(i) Determining the possible effects of a number of the demographic factors on the economic growth

(ii) Interpreting the bi-directional causality among: (i) the population growth and the economic growth; and (ii) the life expectancy and the economic growth

1.4 Research scope

This thesis has evaluated the relationship between demographic factor and economic growth by using the panel data in the period of 1990 - 2013 The selected area is the South East Asia countries which has experienced the economic miracles, and obtained the advantage of demographic bonus

1.5 Thesis structure

The next content of this thesis includes four chapters, which clarified as following: Chapter 2 exhibits the related theories and the empirical evidence

Chapter 3 explores the research methodology, specifies model and explains data measurement In addition, the applied econometric technique for each of research objectives have been specified

Chapter 4 exhibits the empirical results since the econometric technique is identified After that, the explanation and discussion will be revealed for the findings in comparing with other empirical researches

Chapter 5 formulates the concluding remark, the policy implication, and the limitation and direction for further research

CHAPTER 2 LITERATURE REVIEW

This chapter will review the linkage between the demographic factors and economic growth focusing on the following three fundamental sections: (i) theoretical literature on the influence of demographic factors on growth process; (ii) the summarization of the sizable evidence from the empirical research have been demonstrated for each proxies in demographic factors And (iii) the conceptual framework has been conducted so as to clarify the potentially influential channel

Figure 2.1 Life Cycle Income and Consumption

Sources: Bloom et al (2003)

Another proxy that is examined as a demographic factor in this study is life expectancy As the definition of United Nations (2013), life expectancy at specific age is the expected years that a person at that age could live base on the assumption that age-specific mortality levels is constant In this thesis, life expectancy is the short word for life expectancy at birth which was the number of years that one newborn could live if the age-specific mortality rates was not change Due to the fact that longevity reflect the mortality

as well as the health of country, life expectancy could be an important demographic proxy

in the process of economic development

2.1.1.2 Demographic Transition

In general, the demographic transition or demographic window refers to a period which exhibits the common declination in the mortality and the fertility This period accelerated the economic growth through the higher portion of working age population in comparison to the one of non-working age population, thus improve the productive per capita The United Nations (2004) has defined this period when the proportion of population under 15 years is below 30 percent and the proportion of population over 65 years is still below 15 percent Moreover, the benefit that a nation could obtain during the demographic transition was called the “demographic dividend” or demographic bonus as the definition of UNFPA (2014)

Figure 2.2 The process of demographic transition and population growth

Sources: Bloom et al (2003)

The dawn of demographic transition was marked by the decline in the death rate for

a while, and then, be finished at the time when the birth rate declination ended Nevertheless, this mechanism is quite complex than that when there are two separated dimensions to explain the trend of population growth As depicted in Fig 2.2, at first, the population has started to increase since the death rate decreased Then, this trend will be interrupted, and tend to decline since the birth rate begin to fall It means that baby-boom episode and the increase in population has happened when the birth rate is still maintained for the higher level than the death rate Furthermore, this process can be understood that the initial generation of baby-boom population would reach to the prime level of reproductive that lead to an echo effect of the increase As a result, in spite of the decline

in the population growth, the population could still expand when the replacement level is

still satisfied At this time, the population growth rate would observe a bulge in the number

of population in comparing with previous period before the starting point of the transition (Bloom et al., 2003)

2.1.2 Demographic factors and economic growth

The characterization of modeling the relationship between demographic factors and economic development has been challenged for a long time ago (from the a hundred years ago) which initially debated in the papers of the study of Malthus (1798) It has portrayed the influential dimension of the demographic factor on the economic growth by defining the Malthusian stagnation mechanism Nevertheless, this has been changed in recent year due to the changeable idiosyncratic of demographic factors, the economic situation, or even the changeable modern conception Based on this way of analyzing, a number of researches has been constructed as a summarized framework for the related theories which includes:

(i) the traditional “Malthusian regime” that focused on the stagnation from the relationship

between the controlling process of demographic transition (population growth) and the

food issue; (ii) the “post-Malthusian” state which implied the slight impact of greater population on the growth; (iii) the “modern approach” postulates the steady growth

mechanism with a group of number of factors that impact on growth

2.1.2.1 The perspective of Malthusian Regime

The most basic theory of the role of population in economic growth process is Malthusian controversy The main idea of this view is population without control increases geometrically but food supply only rise arithmetically because of limit of some factor of production such as land and technology Consequently, the demand will overwhelm the supply and people in the world will face up to the terrible famine

As stated by Malthus (1798), the economic performance will be higher with small population, on the one hand, high income per capita have the supportive function to the expansion of population On the other hand, the higher population with circumscribed resource will lead to the increase in price, it will have a preventable effect to the standard

of living Malthus recommended that terrible situation could only be stopped by lower population size There are two solutions were provided: the first is “positive check” which

to rise the death rate (malnutrition, disease, famine, and war), the second is “negative check” (or preventive check) which to decrease the birth rate (later marriages, birth control)

Figure 2.3 Population growth and food supply

Sources: Author’s analysis

The Malthusian theory implies that population size will be self-adjusted to adapt with the supply of production The raise in product will counterbalance by increasing in population size, thus the technologically superior countries only had higher population density and the economic performance did not reflect technological progress As can be seen from the Fig 2.4, the Malthusian regime endured most of human history and characterized by a constant GDP per capita as well as a little change in population size Some evidence from history presented the result consistent with Malthus’s hypothesis The study of Maddison (1982) in Europe reports that growth rate of population and output per capita from 500 to 1500 is quite minuscule In addition, Livi-Bacci (2012) demonstrates the population growth in the world is smaller than 0.1 percent per year between the years

1 and 1750 As reported from the book of Galor (2011), life expectancy during the Malthusian regime vacillated around 35 due to the fluctuations in fertility rate as well mortality rate The denser populations without improvement in infrastructure and social service was the reason for such fairly low life expectancy in a long time Nevertheless, the stability of Malthusian only endured until 1750 with developed countries and 1900 with

Food supply

developing countries (Galor, 2011) The evolution of technology considerably increased in conjunction with the advancement of industrialization, sparking a marked periods in history which is described in next part

Figure 2.4 Population growth and economic growth, in period of 1300-2000

Sources: Galor (2011)

2.1.2.2 The perspective of Post-Malthusian

Ironically, the two centuries after Malthus’s influential theory witnessed a number of countries took off from the Malthusian trap and took advantage of the significant increase

in the quick pace technology However, the start point of the take-off and its significance was dissimilar across regions In developed countries, the evolution which was concatenated with the Industrial Revolution occurred at the dawn of the 19th century compared to the delay until the 20th century for developing countries

During Post-Malthusian Regime, the higher population growth participated quite considerable contribution in economic transform The dilute effect on resources per capita

of larger population was counteracted by technological advancement and accumulation of capital, and hence the output per capita was continuing to increase in spite of the raise of population Moreover, the propulsive role of high GDP per capita on the expansion of

population from Malthusian Regime continued to function An dramatic increase in the growth rate of the income per capita is related with a boom of population, portrayed by a simultaneous acceleration of the population growth (from 0.27% to 0.8%) and the income per capita (from 0.05% to 1.3%) from the period of 1500-1820 to the period of 1870-1930 (Maddison, 2007) In particular, in regional technological leaders such as United Kingdom, Western Europe, US, Canada, Australia, the substantial increase in its share of world population due to technology and land abundance was described by Galor (2011) Moreover, the positively significant impact of growing population during the pre-industrial development was investigated by Goodfriend and McDermott (1995), their finding suggested the contribution of larger population was through labor market, hence generated

a better economic performance

The Post-Malthusian Regime finished in developed countries with the downward trend in population growth towards the end of the 19th century, on the other hand, the delayed take-off of developing countries still continued and generated a sharp rise in population over the world (from 0.93% over the period of 1913-1950 to 1.92% over the period of 1950-1973) However, the take-off in developing countries finally ended with the onset of the demographic transition (except for some African countries) in the last half of the 20th century (Maddison, 2007) The theories in this period provided the framework to investigate the relationship between demographic factors and marked growth of economy,

in addition, the technological promotion was considered as the most important factors on this process Notwithstanding, the stagnation during the Malthusian period and the next sustained state would not be captured, hence this problem could be unraveled more clearly

in the next section with the modern growth theories

2.1.2.3 The perspective of Modern Growth Regime

As referred in Galor (2011), the Post-Malthusian and Modern Growth were separated

by the demographic transition with the reduction in population growth There are two main approaches of explaining the economic growth in Modern Growth Regime, the neoclassical theory of exogenous growth and the new theory of endogenous, the predictable results shows the negative effect to per capita output from a raise in population

From one point of view, the exogenous growth model (Solow, 1956) implies that the enlargement of population have contribution to the increase in output process As can be seen from the Fig 2.5, the increase in population shifts the C line upwards to C’ and the equilibrium in long-run upwards from A to B which have the lower output per capita and capital per worker Therefore, the growth of output in new equilibrium is more rapid due

to higher population growth It is noticeable from this transform that the income per capita growth rate is unaltered due to the unchanged technology

Figure 2.5 The exogenous growth model

Sources: Author’s analysis based on Gylfason (1999)

From another point of view, the endogenous growth model reminisces the Malthus’s view that the change made by larger population would lead to the lower growth of output per capita This process could be clearly shown in Fig 2.6, the T line shifts to the left to T’ due to the larger population Compared to the old equilibrium at point A, new equilibrium

B has lesser technological process with the same economic growth The unchanged economic growth, combined with a rise in population, would reduce the growth of income per capita

Figure 2.6 The endogenous growth model

Sources: Author’s analysis based on Gylfason (1999)

It is apparent from these theories that the positive influence of population and demographic transition was neglected despite the fact that demographic change appears to

be essential for considerable growth of output per capita over the development process Meanwhile, there are many theories support for the promotional role of denser population such as the argument of Kuznets (1960) about the contribution of population as the producers, the saver and the consumers in the economy Besides, he also points out that the optimal income per capita may not the only signal for the benefits of country from more population In addition, Steinmann, G (1984) states that technological advancement was boosted by changing in demographic factors through concentration of elites, hence accelerating the economic growth

2.1.3 Demographic transition and economic growth

The transmitted channel of demographic transition has constructed based on the three

major mechanism that includes: (i) the labor supply; (ii) the savings; and (iii) the human capital

2.1.3.1 The labor supply mechanism

The demographic transition will create a crucial effect on the economic growth from the baby-boom generation It will make the working power being strong while the

dependent influence being low A greater supply for the labor market will be captured, and therefore creating and increasing spillover effect in the economy Nevertheless, it is noticed that this effect is essentially depend the cohort of the 15-64 baby-boom generation due to their important contribution on the labor force Besides, the educated generation would be created since the family’s size is decrease Then, the more productivity and the stronger workforce would be created in the economy (Bloom et al., 2001; Bloom et al., 2003)

2.1.3.2 The savings mechanism

The demographic factors could foster the economy’s prospect based on the incentive

of investment from the savings idiosyncrasy It exhibited the accounting and behavioral effect of the working power Particularly, there is the high consumption, but the low production for the young and the old age people Whereas, the higher level of saving and the greater the output can be observed for the economy due to a concentration of demographic transition on the working-age people who work for the annual salaries, their child, their parent, their family, or their future outlook of the retirement As a result, the demographic transition could create the potential mechanism of encouragement in reinforcing the economy However, it has been noticed on the planning of pension and the living standard for the economy when the transition come Otherwise, the bad scenario of the reduction output, or of the dependent burden of the population would constrain the economy Thereby, a healthy population should concern both case of the demographic transition effect toward the economy (Higgins and Williamson, 1997; Higgins, 1998; Lee

et al., 2000; and Bloom et al., 2003)

2.1.3.3 The Human capital mechanism

The most tangible and significant factors that portray the demographic transition is how people live or their attitude is change It exhibits the crucial effects of demographic factor on the human capital investment As a result, when people experience a longer life expectancy, they would change their way of investing on education as well as family or retirement decision From this prospect, the greater valuation for the population would generate the possible quality workforce for the economic growth (Inter-American Development Bank, 1999; Bloom et al., 2001; and Bloom et al., 2003)

2.2 Empirical studies

Although there are a lot of empirical studies on this topic with different duration, countries and method, the relationship between demographic change and economic growth has been still a debate until now This section provides an overview of the contribution of demographic factors to economic growth through some approaches:

2.2.1 Population growth and age structure

From the Malthus’s theory about the bad influence of population growth on economic performance, there is much paperwork which provides supportive evidence for this pessimistic view Coale and Hoover (1958) built up a hypothesis based on an Indian database about the negative relationship between a raise in young dependence and savings

in a short run which lower the standard of living Albeit, he believes that in the long run with the decrease of fertility rate, low-income countries will benefit more in economics Another supportive idea for this view is from Ehrlich (1970) with the forecast in his book

“The Population Bomb” of the death of millions of people when the resource could not adapt to extremely high population For a time, the catastrophic theory was consolidated

by a number of studies in different level of data Crenshaw et al (1997) confirmed the result of Coale and Hoover (1958) when he found the growth of workforce could not balance out the growth of children, so the rapid increase in population due to the raise in young ratio will damage the output per capita of developing countries during 1965-1990

In addition, Bloom et al (2000) uses data from 1965 to 1990 in 70 countries from different regions to investigate the demographic variables and economic growth Their results shows that the fall of fertility could contribute to the success in some economy especially in East Asia due to lower young dependence, although the power may not last long because of the population grows old in future Bloom et al (2003) show that the rapid growth of population requires a large part of technological improvement and the fixed resources such

as home, infrastructure and so on Thus, the raise in productivity could not make significant change in standard of living Until 1800, the gap between the countries with high technology like England, France, Germany and low-technology countries in Asia and Africa is still small The empirical review in recent decades such as Barlow (1994), Kelly

and Schmidt (1995) also find an evidence about negative correlation between population growth and income per capita with panel database Based on the above figured out facets,

we could concern the influential fabric of the population growth toward the income per capita which is gone through lower fertility rate Furthermore, the idiosyncrasy of the mortality will be clarified more clearly in the section of “life expectancy”

The empirical study in recent decades also provide an inconsistent results, while some papers find the negative effects, others find positive or no relationship The study about

110 countries in the period of 1960-2000 of Azomahou and Mishra (2008) shows that contrary to the negative influence on economic growth in OECD countries, the total population growth make a positive effect in non-OECD countries The argument for the positive effect of population growth on economic growth has quite strong support, Simon (1981) provided the opposite argument to the Malthus’s theory that the resource is not limited and the rapid growth of population could have a beneficial effect on output The promotional role of population growth on economic performance was supported by the rapid growth of technological progress Simon (1986) confirmed that the decrease in resources for more people is compensated by the innovation in both agriculture and industry, thus the higher growth of population, the more benefit it brings out Moreover, Bloom and Williamson (1998) sustained that raise in population bolster the miraculous growth in East Asia during the period from 1965 to 1990, however, the positive impact only happens when expansion of population as a whole is slow compared with workforce growth The results suggests the bright future for the Southeast and South Asia due to the fact that their fertility rate was still high and these countries could get the bonus of the demography as the East Asia countries in the past

The theory focuses mainly on total growth of population and does not concern much about the change of age distribution, despite the fact that this change could have the important influence as population growth In recent times, the empirical studies concern more about the age structure since it provides more information for implied policy Crenshaw et al (1997) found that the economic growth in 75 developing countries was hindered by raise in young dependence, though the effect of increase in working population

still positive In addition, the research of Azomahou and Mishra (2008) into about 110 countries from 1960 to 2000 shed light on the growth of each group (0-14, 14-64, 65 and above) shows some different results The increase in young and working age population have positive contribution to growth in both OECD and non-OECD countries, yet the negative trend was found in non-OECD countries which could be the implication for population-control policy in these countries The ageing population was found in both group of countries, though the effect in OECD was more serious than in non-OECD The results based on micro data show the important role of demographic factors on economic process by its change over time and countries Since the “East Asian miracle”, there is a sizable body for empirical research focused on explaining the high growth during three decades of the four Asian tigers Besides the main factors come from industrialization, globalization, education, policy Liao (2011) proves that contribution of demographic on growth in Taiwan from 1970-2004 is more than 33 percent, the result could also apply in the case of the other Asian Tiger countries like Hong Kong, Korea and Singapore The results from Minh (2009) shows that the effect of demographic change on growth of economic in Vietnam is approximate 15 percent during 2002-2006 period

Moreover, research in this field also considers the effect of demographic factors by its change over time Boucekkine et al (2002) argued that the effect of demographic transition takes a long time due to time for new generation, thus the long-term effect of demographic factors just could be analyzed with the data sets longer than 60 years Furthermore, Barlow (1994) debates that the expansion of young population have negative impact in short term, yet it becomes positive in long term As combining both effect, the population growth at current time may not correlate with income per capita in spite of the significant effect in short run The linear model could not be suitable with different influences due to time, the study of Azomahou and Mishra (2008) uses generalized additive model and found out the non-linear relationship between growth of each age group and economic performance Into the bargain, An and Jeon (2006) use data of OECD countries during the period of 1960-2000 and found that the demographic change would rise the

growth of economic at first, then the effect will turn to opposite sign in next period due to the ageing population

2.2.2 Life expectancy

Population growth of a country was almost determined by fertility and mortality rate

As noted in the previous section, the impact of fertility was discussed carefully, and in this section, the role of mortality will be reviewed with another proxy of demographic factor - life expectancy since two proxies have high correlation According to Acemoglu and Johnson (2007), there was a rapid reduction in mortality rate which led to unprecedented improvement in life expectancy in a large number of countries during twenty century Moreover, life expectancy not only be the reflection of mortality rate, but also the common proxy for the health of nation In both two aspects, the role of life expectancy on growth process has been a controversy for economists until now

For a long time, there are a great amount of papers suggest the vital influence of longevity to growth in different level of data In cross-country level, Barro and Lee (1994), Caselli et al (1996), Gallup and Sachs (2000) come into the same results with different econometric method that life expectancy have significantly positive effect on per capita output The recent study from Ashraf et al (2008) proved that per capita output have tended

to be higher by appropriate 15% in the long-term since the life expectancy raises from 40

to 60 With panel database from 1960 to 1990 in 104 countries, the study of Bloom et al (2004) confirmed the promotional contribution of life expectancy on income per capita due

to increase in worker’s productivity is about 4% per year Along the same time, De la Croix

et al (2009) also concerned this nexus and find positive correlation between two proxies The life expectancy and growth nexus which was examined across countries is imitated in within-country regression Cutler et al (1997) suggested that the gain in outcome during the 20th century was maintained by longer life in US In addition, Qin and Hsieh (2014) show the positive correlation between per capita output and life expectancy across 31 provinces in China

On the other hand, some results find that the longer life may not improve income per capita in long run The recent paper of Acemoglu and Johnson (2007) provides an opposite

finding to most of previous studies: the increase in life expectancy contributes to the reduction in economic growth based on cross-country database over the 1940-2000 periods

De la Croix and Licandro (1999) built up an overlapping generations model to consider the relationship between life expectancy and growth, their study suggests that the economic growth may be pushed up by the low levels of life expectancy In contrast, the economic would tend to be exacerbated when the countries is more developed due to the ageing population Evidence from research of McDonald and Roberts (2002) also supports the idea of de la Croix and Licandro, their finding exposes that despite the supportive role of longer life in developing countries, income per capita in OECD countries was depressed because of ageing of their population These finding provide an important entanglement for the policy discussion about the benefit in long run of lower mortality and longevity

2.2.3 Bi-directional causality

This section discusses two pair of simultaneous equations: one that explain the way relationship between population growth and economic growth, and the other observes the linkage between the latter and life expectancy

two-One of the first theories that proves the two-way relationship between population growth and economic growth is Malthus (1798), who claimed that the higher income affect the population positively through both reduction in mortality and raise in birth rate On the other hand, the effect of increase in population growth on economic growth was negative through diminishing returns Existing research on the linkage between population growth and economic growth uses data at both cross-sectional and within countries At the macroeconomic level, as reported in Lutz and Quiang (2002), the GDP per capita has a negative influence on population growth Moreover, Tsen and Furuoka (2005) have found extensive evidence about the bi-directional causality between population and income growth in Japan, Korea, and Thailand The recent papers have more focused on the contribution of population growth on growth process rather than the impact of standard of living on population For instance, Bloom and Williamson (1998), Bloom and Finlay (2009) has explored the reverse causality between income growth and population using the lagged population growth as instrument variable

Naturally, the relationship between life expectancy and economic performance could

be considers as a bidirectional causality The high-income countries able to afford the good infrastructure and social care for their citizen to have a long life On the other site, the longer life help people get the more benefit from education, their higher saving also help

to boost the economy One of the first papers studying the positive relationship between life expectancy and income is Preston (1975), who stated that more than one third of the improvement in life expectancy over the 1930 -1960 period could result from increasing income A general attempt to look for different channels which high income per capita could affect life expectancy was provided by Soares (2007), who argue that the improvement in education, nutrition, sanitation and housing due to income growth was the source for the better health Moreover, Soares (2007) demonstrates the significant contribution of income to life expectancy during the period of 1940-1970 using the cross-sectional dataset The simultaneous effect between life expectancy and growth was also considered in many studies such as Acemoglu and Johnson (2007), Ashraf et al (2008), and Cervellati and Sunde (2011) The results has maintain the causal relationship between two proxies, although the sign of impact was still inconsistent with each other

2.2.4 Determinants of economic growth, population growth, and life expectancy

in behavior of population, thus effect the additions on the infrastructure and other fixed assets Third, the inequality gender is the other noticeable feature in the growth model since

women composed over half of the world’s population and their utility is still underused, especially in the developing countries (Cuberes and Teignier, 2014) From a theoretical point of view, Galor and Weil (1996) suggests that reducing gender inequality could result

in increase of economic growth by lower fertility which could be the sign of demographic transition There is a number of recent studies found the significant contribution of the female labor to the economy, for instance, Aguirre et al (2012) observed the raise in GDP due to the increase in the relative ratio between female and male labor force participation rate Finally, the civil liberties was examined as a determinant of growth by Kormendi and Meguire (1985), their finding suggests the significantly positive effect of the high civil liberties on economic growth Moreover, investigating the influence of institutions on growth in a large sample of countries in the period of 1975-1990, Dawson (1998) proved that civil liberties as a proxy of institution affects income growth through an indirect impact

on investment In conclusion, the economic growth could result from many other factors, but this thesis could only focus on some main variables due to framework of some previous literature

2.2.4.2 Population growth

The goal of this section is to provide some factors that could be associated with the expansion of population beside the economic growth Follow the model which was constructed by Lutz and Quiang (2002), GDP per capita, population density, urban population growth, female labor force participation, and food production index was examined as the main component of population growth process Particularly, the decelerated impact of dense population on population growth through lower fertility was considered as a foundation of population ecology (Sibly and Hone, 2002) However, the results from human population sample in Lutz and Quiang (2002) showed the surprising result that higher population density seemed to boost the population growth

2.2.4.3 Life expectancy

This section concerns the contribution of other determinants to life expectancy beside the influence of economic growth First, the death rate could be the indicator for the equation of life expectancy since the greater death rate naturally leads to lower life

expectancy directly Another features could have influence on life expectancy is percentage

of population ages 65 and older In the study of Shaw and Vogel (2005), the portion of older and its interaction with another lifestyle’s factors was considerably significant effect

in OECD dataset over the period of 1960 to 1999 In addition, fertility may the suitable explanatory variable for life expectancy since it have the high correlation with maternal health According to AbouZahr and Roystion (1991), nearly a half of maternal deaths occur

in Asia, which has the highest portion of population Using developing countries dataset, Trussell and Pebley (1984) found that fertility had a significant impact on both child and maternal mortality In addition, the immunization is considered as an important factor that involve the health status The study of Poland et al (2005) proved there is a linkage between immunization and workers health Moreover, Halsey and Galazka (1985) suggested that infants should get the DPT immunization as soon as possible to avoid the risk from natural diseases Last but not least, the contribution of education was examined

as noticeable features that has significant effect on health The nexus between education and health which was analyzed by Ross and Wu (1995) is stated the positive and statistically effect of completed schooling years on health In addition, Adams (2002) maintains the existent relation between the education and health among older people using the dataset of US in 1992 Although, there are many other factors could also affect the life expectancy such as environment, lifestyle, institution, and so on, this thesis could only focus on some main variables due to the lack of data for the other proxies

2.3 Hypothesis construction and conceptual framework

2.3.1 Hypothesis construction

2.3.1.1 Demographic factors and economic growth

Population growth and economic growth

First, despite the aging population that the East Asia has been dealing with in recent time, the considerable demographic change during the period of 1965-1990 was one of the motivation for the miracle growth in East Asia (Bloom and Williamson, 1998) Second, according to Bloom et al (2003) the demographic transition in Southeast Asia has lagged behind East Asia, thus the demographic bonus may come to the former lately It mean that

the potential positive effect could be exist in Southeast Asia The last but not least, this expectation have also been confirmed in current study (Bloom et al., 2010; Bloom and Finlay, 2009) From these literature, it is reasonable to expect that population growth may have a good impact on economic growth process

H1a Population growth has positive effect on economic growth in Southeast Asia

Life expectancy and economic growth

Although the recent paper of Acemoglu and Johnson (2007) provides an opposite finding to almost previous studies: the increase in life expectancy contributes to the reduction in economic growth based on cross-country database over the 1940-2000 periods The positive relationship between life expectancy and economic growth has been confirmed in a number of empirical studies with different econometric method such as Barro and Lee (1994), Caselli et al (1996), Gallup and Sachs (2000), de la Croix et al (2009) Moreover, the study of Cervellati and Sunde (2011) which use framework of Acemoglu and Johnson (2007) as benchmark revealed that the improvement in life expectancy would leads to the increase in income per capita From these finding, life expectancy is expected to positively affect the economic growth

H1b Life expectancy has positive effect on economic growth in Southeast Asia Age structure and economic growth

Age structure was considered as the new aspect in the investigation of effect of demography on development The finding from studies of Crenshaw et al (1997), Azomahou and Mishra (2008) using cross-national dataset suggested the distress of dependence age group to economic growth Moreover, these findings was maintained in the case of Asia countries since both the young and old dependence fraction On the other hand, the increase in portion of working age population seemed to stimulus the economic growth in recent empirical studies (Azomahou and Mishra, 2008; Bloom and Finlay, 2009)

In conclusion, the economic growth could get more benefit from both the raise in

proportion of working age population and the reduction in proportion of dependent population

H1c Age dependency ratio has negative effect on economic growth in Southeast Asia

H1d Working-age share has positive effect on economic growth in Southeast Asia

2.3.1.2 Two-way relationship

The previous research has been examined the simultaneous relationship between population growth and economic growth to confirm the impact of the former on the latter Particularly, the instrument variable technique was observed in the studies of Bloom and Williamson (1998), Bloom and Finlay (2009), Bloom et al (2010) to deal with this problem Similarly, the endogenous problem which results from two-way relationship between life expectancy and economic growth was considered in a number of empirical review such as Acemoglu and Johnson (2007), Ashraf et al (2008), and Cervellati and Sunde (2011) However, most of papers has just handled the simultaneous problem to robust the effect of demographic factors on economic and disregard of the possible impact from the opposite direction Therefore, the objective of this study is not only examining the impact of

demographic factors on economic growth but also clarifying the bi-directional causality of

Figure 2.7 The conceptual framework

Sources: Author’s analysis

factors

Population growth

Life expectancy

Demographic Factors

Age Structure Control factors

Control factors

(H1) (H2)

CHAPTER 3 RESEARCH METHODOLOGY

The goal of this chapter is to address the methodological perspective of this study in two aspects: (i) the overview of dataset for investigating the influence of demographic factors on growth process; (ii) the model specification of the sizable evidence from the empirical research have been constructed for each proxies in demographic factors; and (iii) the research methodology specifies for the applied econometric techniques that is used for clarifying the research objectives

3.1 Data

For the purpose of examination the impact of demographic components on economic growth, this study construct an annual panel dataset from 1990 to 2013 using country-level data of the Southeast Asia sample as the classification of United Nations 2015 The original sample consisted of eleven countries, however, the observation from Myanmar has been removed due to the lack of the main outcome variable - GDP per capita Therefore, the base sample have just consisted of ten countries (Brunei Darussalam, Kingdom of Cambodia, Republic of Indonesia, Lao People’s Democratic Republic, Malaysia, Republic

of the Philippines, Republic of Singapore, Kingdom of Thailand, Democratic Republic of Timor-Leste, and Socialist Republic of Vietnam) The Southeast Asia seemed to be a suitable sample since most of the countries in this area has been receiving the demographic bonus Moreover, the population in this area takes about 8.62% world’s population and is

in the third place in the world in size, just behind the Southern Asia and Eastern Asia (United Nations, 2015) Last but not least, a range of countries from high to low income in this sample help to capture the variation in income per capita due to the demographic transition, yet remaining the homogenous group of countries with similar characteristic The main outcome – GDP per capita data are from World Bank 2015 The essential data sources for demographic factors are the United Nations 2015, and World Bank 2015 The detail of other control variables which are used in the estimation can be found in Table 3.1

Table 3.1 Variable descriptions

GDP per capita Number GDP per capita based on purchasing power parity (PPP) (constant 2011 international $) WB 15

Life expectancy

1990

Population 0_14 Percentage Ratio of people younger than 15 to total population UN -

Population 15_64 Percentage Ratio of people between the ages 15 and 64 to total population UN +

Dependence old Percentage Ratio of people older than 64 to those ages 15-64 WB 15 -

Dependence

young

Transition Dummy The Population 0_14 below 30% and Population 65_above below 15% (1-yes,0-no) UN +

Civil liberties Index Civil liberties index, 1-7 where 1 is extreme civil liberties and 7 is extreme no civil

liberties

Freedom House

-

Density People per

sq km

Density 1990 People per

sq km

Population divided by land area in the base year (1990) WB 15 -

Human capital Index Human capital per person, based on years of schooling and returns to education PWT 8.1 +

Immunization Percentage Percentage of children ages 12-23 months who received vaccinations WB 15 +

Details of sources: WB 15, World Bank 2015; UN, United Nations; ILO, International Labour Organization; PWT 8.1, Penn World Table version 8.1

Sources: Author’s analysis

3.2 Model specification

3.2.1 Model specification for one way effects

Modifying the Malthus’s vision in the implication for the poor and the rich countries, Fogel (1994) has analyzed the problem of population theory, and of the relevant measurement of itself in the standard growth model from the findings in the current literature It means that, the analysis of population theory in the growth model should be careful concerned due to the mis-specification of various aspects of the demographic factors It is noticed about the adjustment for the omitted idiosyncrasy when there is concerns of the relationship between the demographic factors and the economic growth, instead of focusing on the standard factors of the growth model (Fogel, 1994)

Following this vision, Wei and Hao (2010) has clarified the problem of standard growth model, including: (i) the simple correlation estimation may not exhibit the channels

of how the demographic factors affects the economic growth (Kelley and Schmidt 1999, 2005); and (ii) the production function model may bear a serious difficulties of compiling data, or of measuring variables (Kelley and Schmidt, 1999; Wei and Hao, 2010) As a results, it is noticed about an extended model when assessing the relationship between the demographic factors and the economic growth In this model, there are a numbers of demographic factors has been concerned, such as: the demographic structure, the dependence ratio, the working age group, or the population growth (Wei and Hao, 2010)

In addition, there is a number of papers considers the unique idiosyncrasy of life expectancy as another aspect of demographic factors that can affects the economic growth Actually, Barro (1996); Bloom et al (2000); and Bloom et al (2004) have figure out the separated effects of life expectancy on the economic growth, based on the view of production function framework And, it has been clarified as an additional factor that can

be presented in the growth model

As a results, this thesis is carefully deliberated so as to apply the extended model in which the effects of various aspects of demographic factors on the economic growth are clarified These factors will be combination between a number of demographic structure,

the population growth and the life expectancy Based on this view, the extended model (Wei and Hao, 2010) and the linear regression framework (Cervellati and Sunde, 2011) are considered as following:

transition, civil liberties, log of population density in 1990

3.2.2 Model specification for the bi-directional causality

The current literature has just concerned the presence of the potential endogenous problem in the relationship between demographic factors and economic growth Nevertheless, these papers have not clarified the possibly inverse effect of economic growth on several factors of demographic factors (population growth, or life expectancy)

It means that this study has been concerned the analysis in both two way of the relationship – bi-directional causality – formulated as following equations: