Poverty, Inequality and Growth in Developing Countries

Atsushi Maki

• Publisher: Routledge
• Year: 2015
• eBook ISBN: 9781317444794
• Edition: 1
• Topic: Economics
• Subtopic: Economic Theory
• Index: Economics

There are many problems regarding poverty, inequality and growth in developing countries in Asia and Africa. Policy makers at the national level and at international institutions such as the United Nations, World Bank, International Monetary Fund and others have implemented various policies in order to decrease poverty and inequality. This book provides empirical observations on Asian countries and Africa. Each chapter provides theoretical and empirical analysis on regional case studies with an emphasis on policy implications.

The book will be of use to many who wish to assess and improve policies in developing countries and mitigate poverty and inequality, and stimulate growth, by drawing on relevant empirical research and economic theories. Clearly, there have been numerous policy failures and the book aims to provide a basis for improving policies and outcomes based on relevant empirical observations.

1 Introduction

Atsushi Maki

DOI: 10.4324/9781315696058-1

Overview

Developing countries experience many problems stemming from poverty, inequality, and growth. Government policy makers and economists at international financial institutions such as the World Bank and the International Monetary Fund advocate many kinds of economic growth policies to lessen and mitigate poverty and inequality while increasing the standard of living. The present project focuses on analyzing poverty, inequality, and growth in developing countries based on economic theory and empirical observations.

It is generally believed that analysis of economic statistics such as macroeconomic statistics, cross-sectional data, market data, or micro-data is the basis of empirical analysis. However, while acknowledging that the analysis of statistics is a necessary condition for empirical analysis, it is not a sufficient condition in the field of sciences because empirical analysis must be informed by theoretical considerations.

We embrace empirical research in economics based on a seminal paper by Koopmans (1947) entitled “Measurement without Theory.” In his paper, Koopmans introduced the contributions of Tycho Brahé, Johannes Kepler, and Isaac Newton to the field of celestial mechanics. Koopmans described the Kepler stage and the Newton stage in the development of celestial mechanics and identified the difference between the two stages. In the Kepler stage, Tycho Brahé collected accurate data about the movement of planets, while Johannes Kepler used this data to posit empirical regularities called Kepler’s Three Laws regarding the motion of planets around the Sun. During his research, Kepler tested many kinds of hypotheses and conducted numerous calculations to verify his hypotheses. Thus, the Kepler stage, and Kepler’s Three Laws, involves obtaining accurate values through observations and determining empirical regularities by testing various hypotheses. Based on the empirical regularities obtained in the Kepler stage, the Newton stage exists. We know that Newton’s Law of Gravitation builds on the Law of Inertia, the Law of Motion, and the Law of Action and Reaction. In addition, he introduced the Law of Universal Gravitation as F = G(Mm/r²). The difference between the Kepler stage and the Newton stage is in its general applicability.¹

When we conduct empirical analysis in economics, we have to bear in mind three key considerations. The first stage of empirical analysis is to gather accurate observations. Processing observations as raw data, we find empirical regularities in the observations. During the process, we sometimes observe contradictory findings to existing empirical regularities. For example, we have observed an empirical regularity in many countries over many periods that as income increases in cross-sectional data, Engel’s coefficient – namely, the ratio of food expenditure to income – decreases monotonically. This is a famous empirical law called Engel’s Law. However, in poor households in developing countries, Engel’s coefficient increases as income increases, defying existing expectations. When we obtain such kinds of observations repeatedly, we have to reconsider the existing model specification to describe empirical regularities in order to explain real-world observations.

The second stage of empirical analysis requires the selection of a model specification that can be explained in terms of economic theory. Constructing an analytical model, we have to choose suitable specifications consistent with theory.

The third stage is to evaluate empirical models in terms of their power of explaining the real world. Whether or not the model specification is suitable is judged by forecasting and/or making simulations after constructing the model. If the model specification is wrong, we will fail to forecast correctly and/or obtain unsuitable simulation results. In such cases, we have to return to the choice of the model specification and recalibrate it.

It is important to understand key differences between the natural sciences and social sciences and to explain the reason why the accumulation of knowledge about empirical regularities is thick in natural sciences, while it is thin in social sciences. One of the main reasons is the possibility of controlled experiments. In the natural sciences, it is relatively easy to conduct controlled experiments in a laboratory under the same conditions repeatedly. Even so, in natural sciences, a prediction of an earthquake, tsunami, or volcano eruption is difficult. This is mainly due to the difficulty of conducting a controlled experiment regarding seismic events. In fields in which it is difficult to repeatedly conduct controlled experiments, theory plays a critical role.

Another reason why the accumulation of knowledge on empirical regularities is thin in social sciences has to do with the degree of stability of the object of study. When we consider celestial mechanics as an example, it is relatively stable compared to economic fluctuations in the real world. Through observing the sky, we can record the appearance of new stars and that of comets. However, such events are relatively rare. In history, we experience the disappearance of nations and transformation in economic systems. We also experience relatively frequent crashes of financial markets and contend with the transformative power of war. Such events make it difficult for social scientists to discern empirical regularities.

Stability is necessary for identifying the first approximation of the general interdependence of the system. Regarding celestial mechanics, it is easy to approximate a model of a two-body problem under the assumption of ceteris paribus, other conditions remaining the same. Let us consider Newton’s apple. The apple fell because the Earth’s gravity pulled it. It is true that the Moon and the Sun also pulled the apple, but such effects are too small to perceive. In the case of the Law of Universal Gravitation, the Law is described by the relationship of the two bodies as F = G(Mm/r²). In the real world of space, there are eight planets around the Sun, and therefore the system is specified by the N-body problem in nature. But without introducing the N-body problem, observation is well explained – namely, we obtain suitable forecasting power by applying the two-body problem in the real world. As we mentioned previously, the Law of Universal Gravitation is specified by the two-body problem.

If we consider the collective gravitational effect of the Earth, the Moon, the Sun, and other planets on the apple, the problem ascribed to the N-body problem cannot be solved except in special cases. However, because of the Law of Universal Gravitation, natural scientists ignore the effects from the Moon and the Sun, and therefore the N-body problem is reduced to a two-body problem when considering the fall of Newton’s apple. Thus, it can be solved analytically, and we can obtain good forecasting power using such approximations.

In the social sciences, notably regarding economic activities in the real world, observations are generated by the results of interdependence among many economic factors and markets. This creates a similar problem to that discussed previously regarding celestial movements in natural sciences – i.e. determining what to consider and what to disregard. The essence of empirical analysis in economics consists of finding suitable models to explain the real world in terms of first approximation with the assistance of economic theory.

Our fundamental approach in the present monograph is to:

1. discover empirical regularities in observations
2. explain empirical regularities by applying economic theory
3. examine policies and assess their implications based on empirical models
4. reconfirm the stability of the empirical model used.

Structure of the book

We divided the volume into two parts: the first section analyzes poverty and inequality using micro-data sets from Indonesia, Sri Lanka, the Philippines, Tanzania, and Vietnam. The second section analyzes economic growth in developing countries, mainly using time series data for China, Laos, Myanmar, Taiwan, and Thailand.

Overview of the chapters

The present monograph has eight substantive chapters and an introduction and conclusion. Chapter 2 analyzes consumer behavior in Tanzania, one of the developing countries in Africa. This chapter focuses on the validity of Engel’s Law using the micro-data of the 2007 Tanzania Household Budget Survey (HBS). The National Bureau of Statistics in Tanzania conducted the survey. We found that the inverse U-shaped or quadratic Engel curve is suitable to explain the observation contrary to standard Engel’s Law that has the characteristic of monotonically decreasing Engel’s coefficient as income increases. Our finding means that the Engel curve is upward sloping in very poor households and that after reaching the peak value of Engel’s coefficient, the curve is downward sloping monotonically.

The Engel curve is upward sloping in very poor households in Tanzania, indicating that the total expenditure elasticity for food in very poor households is elastic. This behavior is well described by the specification of the quadratic almost ideal demand (QUAID) system. However, food expenditure is classified as a necessity because own-price elasticity for the food category as a whole is inelastic, as verified by many empirical analyses using time series data and the present cross-sectional data. Based on the previous findings regarding the inverse U-shaped Engel curve, we consider the characteristics of necessities and luxuries utilizing not only total expenditure elasticity but also own-price elasticity in the theory of consumer demand.

Our basic question is: when a commodity is price inelastic (elastic) and total expenditure elastic (inelastic), is the commodity a necessity or a luxury? We proposed the Törnqvist-Wold hypothesis and tested the hypothesis empirically based on past empirical results. We found that the Törnqvist-Wold hypothesis does not contradict past empirical results and observations regarding the classification of necessities and luxuries using the relationship between price and income elasticities.

This information is important for the government to target subsidies and other transfer payments to maintain the standard of living and support the most vulnerable populations. During bad harvests, because of price increases in necessities, the standard of living in the nation decreases. When we have information regarding the price elasticity of demand, it is possible to fine-tune subsidies and the distribution of necessities in order to mitigate the negative impact of inflation and shortages.

Chapter 3 focuses on the Philippines and Vietnam, where poverty alleviation programs play a critical role in maintaining minimum living standards, making it essential to understand how impoverished households make ends meet through in-kind transactions. In the present analysis, we use the micro-data set of the 2006 Vietnam Household Living Standards Survey compiled by the Statistics Bureau in Vietnam and the 2006 Family Income and Expenditure Survey compiled by the National Statistical Office of the Philippines.

Using Engel curves including and excluding in-kind consumption, we found that when we included in-kind consumption in consumption expenditure, the Engel curve was monotonically downward sloping in Vietnam and the Philippines. On the other hand, when we excluded in-kind consumption from consumption categories, the Engel curve was hump-shaped or inverse U-shaped. Contrary to the standard Engel’s Law, we found that the Engel curve excluding in-kind consumption was upward sloping in very poor households – namely, paid food consumption increases with cash income. This result is due to the different characteristics of consumption items between in-kind and cash consumption. In very poor households, there is a strong distinction between in-kind and cash consumption, with the latter treated as a luxury.

Our findings are also suggestive about the different effects of in-kind consumption depending on the stages of economic development that may be relevant in terms of economic and social policies in developing countries, especially those targeting improvement in the standard of living of poor households.

Chapter 4 explains the importance of the role of the informal sector in developing countries using Indonesian micro-data. Indonesia is essentially an agrarian society. This chapter compares the job structure of the Banten (West Java) and Yogyakarta (Central Java) provinces, focusing on the informal economy. Banten encompasses manufacturing and agriculture, while Yogyakarta features services and agriculture. We use the micro-data set of the informal sector collected in 2009 by BPS (Statistics Indonesia).

Since having multiple jobs is common practice in Indonesia, total employment in terms of the number of jobs is greater than that of the working-age population. In Yogyakarta, about 44 percent of total jobs are in the agricultural sector, while the wholesale and retail trade sector accounts for 15 percent of the total number of jobs, followed by the manufacturing sector at 11 percent. In Banten, about 21 percent of total jobs are in the manufacturing sector, while the wholesale and retail trade sector provide 21 percent, followed by the agricultural sector at 17 percent. In both provinces, the incidence of informal employment is higher in rural areas. Informal employment in Yogyakarta’s rural areas is 95 percent – namely, almost every person has two or more jobs – in comparison to 83 percent in urban areas. In Banten, the incidence of informal employment in rural areas reaches 91 percent, while in urban areas it is only 67 percent. Jobs in the agriculture sector are predominantly informal in both provinces.

In Yogyakarta, the estimated contribution of the informal sector to total gross value added (GVA) is 37 percent, while approximately 27 percent of Banten’s GVA can be attributed to the informal sector. Yogyakarta’s informal sector in agriculture contributes Rp5.7 trillion (about US $555 million; $1 = Rp10,255), while the nonagricultural informal sector generates Rp9.8 trillion. On the other hand, Banten’s informal sector in agriculture contributes Rp9.8 trillion (about US $956 million), while the nonagricultural informal sector contributes Rp25.6 trillion.

Households that sustain themselves on informal employment, especially if they are dependent on agricultural work, are most vulnerable to poverty in Yogyakarta, while casual workers in Banten are most likely to live in poverty.

Chapter 5 tests the validity of the new economics of labor migration (NELM) theory using data from the Philippines. Three implications of the NELM theory are examined using the Family Income and Expenditure Survey conducted by the National Statistics Office in 2009.

Remittances from overseas are one of the most important sources of income in the Philippines. The Survey of Overseas Filipinos conducted by the National Statistics Office defines remittances as the amount of cash and in-kind transfers received by families from overseas Filipino workers (OFWs). Remittances during the period of April to September 2013 sent by OFWs amounted to 163.2 billion PHP, with OFWs from Asia remitting the largest proportion. About 2.3 million OFWs worked abroad during that period, including countries such as Saudi Arabia, the United Arab Emirates, Singapore, Qatar, Hong Kong, and other countries in western Asia. Just over half of OFWs were men; male OFWs were generally older than female OFWs. Almost ...

Table of contents

• Cover
• Half Title
• Series
• Title
• Copyright
• Contents
• List of Figures
• List of Tables
• Preface
• Notes on Contributors
• 1 Introduction
• 2 Are luxury goods really luxuries? The validity of the Törnqvist-Wold hypothesis
• 3 Engel’s Law in Vietnam and the Philippines: effects of in-kind consumption on inequality and poverty
• 4 Informal agriculture sector in Indonesia: big in size, small in contribution, and full of the working poor
• 5 Effects of remittances on income inequality and poverty in the Philippines
• 6 Area disparity of income and expenditure in Sri Lanka: based on micro-data sets of the Household Income and Expenditure Survey of 2006–2007
• 7 The agricultural sector in Thailand’s middle-income stage
• 8 The possibility of a border economic zone: Asian Golden Quadrangle
• 9 Development of the fishery systems in modern Taiwan
• 10 Conclusion
• Index