Does provincial economic development in vietnam foster internal migration

ABSTRACT This paper investigates the impact of provincial economic development on internal migration in Vietnam based on the complex casual relationship between migration and economic de

VIETNAM - NETHERLANDS PROGRAMME

FOR M.A IN DEVELOPMENT ECONOMICS

DOES PROVINCIAL ECONOMIC DEVELOPMENT IN

VIETNAM FOSTER INTERNAL MIGRATION?

-o0o -

Thesis

CLASS 20

Ho Chi Minh City, September 2015

Instructor: Dr Pham Khanh Nam

ACKNOWLEDGEMENT

I would like to express my deepest gratitude to my instructors in Vietnam Netherlands Program, who helped me to achieve the knowledge through interesting lessons, useful assignment, utility seminars and new information during my master studying

I greatly express my special thanks to Dr Pham Khanh Nam for all his academic recommendations through finishing thesis process

I am grateful to all the staffs in the program have helped me to reach books and necessary documents during the learning process My thanks are also extended to all

my classmates, who have companions and share learning experiences with me through over last 2 years

Mental support from my family is one of the most bolster for my effort to finish this program I would like to send my thanks and my love to all my family’s members

ABBREVIATIONS

PGDP Provincial Gross Domestic Product PCI Provincial Competiveness Index GSO General Statistics Office of Vietnam SEM Structural Equation Modeling FEM Fixed Effect Model REM Random Effect Model OLS Ordinary Least Squares VIF Variance Inflation Factor HCMC Ho Chi Minh City VND Vietnam Dong (Vietnamese Currency)

ABSTRACT

This paper investigates the impact of provincial economic development on internal migration in Vietnam based on the complex casual relationship between migration and economic development We examine that impact for further understanding about the determinants could lead to human migration decision beyond the difficulties at the new destinations Tabulations data about migration flows from GSO database in duration 2005-2013 and national statistical datasets from Statistical Yearbook about provincial development are used to analyze the impact of economic development on migration The quantitative results of Structural Equation Modeling (SEM) and Common Panel Methods indicated that the higher economic development provinces have higher immigration attractiveness

Key Words: Migration, economic development, Vietnam, population, origin areas, destination areas, employment, jobs

CHAPTER 1: INTRODUCTION

1.1 Problem statement 1

1.2 Research objectives and research questions 2

1.3 Scope of the study 3

1.4 Organization of the thesis 4

CHAPTER 2: LITERATURE REVIEW 2.1 Concepts of migration 5

2.2 Migration theories 6

2.2.1 Harris – Todaro theory 7

2.2.2 Lee’s theory 8

2.2.3 Lewis’s theory 9

2.2.4 Other cognizance about migration 10

2.3 Empirical studies on migration 11

2.3.1 Economic development and other factors 11

2.3.2 Determinants of migration 13

2.3.3 Linkages between economic development and migration 14

CHAPTER 3: RESEARCH METHODOLOGY 3.1 Analytical framework and hypotheses 17

3.2 Estimation methods 21

3.2.1 Structural equation model (SEM) 21

3.2.2 Other common panel data methods 23

a Pooled OLS model 23

b Fixed effects model (FEM) 24

c Random effects model (REM) 24

3.2.3 Testing for appropriate models 25

a F-test for choosing FEM or OLS 25

b Breusch - Pagan LM-test for choosing REM or OLS 25

c Hausman test for choosing FEM or REM 26

3.3 Model specification 26

TABLE OF CONTENTS

3.3.1 Structural equation model (SEM) 27

3.3.2 Common panel data techniques 29

3.3.3 Migration criteria 30

3.3.4 Instrument variable 31

3.4 Data sources 32

CHAPTER 4: EMPIRICAL RESULTS 4.1 Overview about inter-provincial migration in Vietnam 34

4.2 Descriptive statistics 37

4.3 Regression results 41

4.3.1 Results from simultaneous equation method (SEM) 41

4.3.2 Robustness test - common panel data methods 44

a Ordinary Least Squared Method (OLS) 44

b Fixed Effect Model (FEM) 47

c Random Effects Model (REM) 49

CHAPTER 5: CONCLUSION AND POLICY IMPLICATIONS 5.1 Main findings 53

5.2 Limitation of the study 54

5.3 Policy implications 54

5.4 Suggestions for further studies 55

References 56

APPENDIX 60

CHAPTER 1 INTRODUCTION

1.1 Problem statement

The modernization of the country is always an important work in the context of the economy increasingly dynamic and society moves deeper in integration with the world One of the top priorities for a sustainable development and modern society is to reduce social inequality and eliminate poverty Along with the existence and development of the country, leaders, policy makers and scientists always seek for better solutions and improve the policies in order to match those requirements

However, in a most natural way, it has never been a simple task and can be done in the short - term to get the immediate results but it is a difficult and long - term process Vietnam never could be an exception case in suffering the negative effect from development process These negative effects are the huge factors causing inequality, poverty, stagnation, unkempt for the social and economic developmentnot only in the present but also for future generations One downside is that people often together rushed to the area where the development which is generally higher than other areas,as an allusion proverb “lua thoc dau bo cau theo do” in Vietnamese

It is easily to espy the phenomenon of rural people leave their fields for the big cities to find jobs The nature of that phenomenon can be interpreted as the migrant attempt to come to higher advantage destinations with the expectation of improving their lives (De Jong & Fawcett, 1981) However, the out-control migration cause the imbalance in population density such as overload status at the large city or the slow growth rate in rural areas since the lack of labor In addition, Migration leads to many serious social problems For instance, mass-migration could create environmental pollution because of the inadequate infrastructure (Bilsborrow, 1992) and theft could also be a painful problem for downtown citizen (Deshingkar, 2006) because the migrants fall into deadlock situation

There are enormous difficulties for any migrant when they have to resettle with many different conditions at the new destinations, but in reality a huge amount of

migrants still migrate day by day because of these motives: economic motives, social motives and residental satisfaction motives (De Jong & Fawcett, 1981)

Along with many factors can affect on the internal migration such as distance among provinces, difference in population density, education facilities, recreation facilities, living standard (Dang, Goldstein & McNally, 1997), cost of moving (Greenwood, 1975), et cetera; Difference in provincial economic development is also

a factor contributes to the migration activities since the province has higher development index will more attract migrants than others In other words, high provincial development leads to the expectation in improving migrant living conditions and becomes an economic motive in migration flows

This study aims to examine the impact of provincial economic development on internal migration to interpret whether high economic development provinces attract migrants and whether the encouragement of economic development – an instrument for redistribution population density? Finding out this linkage support the argument that Government could intervene migration flow via encourage development tools in order to avoid the backward contexts had mentioned above

Throughout the history of the country, Vietnam has had numerous migration flows with different scales, from the early primitive times, through thousands feudal years until today Many of them are forced migrations or reluctant migrations due to Government’s policy or natural circumstances such as migrations in

internal-1954 and 1975 or the migration by policy of "new economic zone" However, the forced migrations have its certain limitation such as the unexpected from those forced

to change their habitat This phenomenon leads to the reactions against this compulsion, for example the resistance, escapade or fake declared information

As the arguments stated above, the consequence of residential overcrowding in one area raises the stagnation in the economic development process.This goes against the expectations of migrants with the purpose of improving their living, which included economic factors, the ambivalence is extremely clear.Therefore, in order to limit the downside that caused by these consequences, policy makers need to find solutions to redistribute population density

Recently, along with the development and integration, spontaneous migration almost completely replaced the forced migration, the issuing macroeconomic policies

so that people could freely to migrate by their own decisions but still within the control of the government is the necessary and urgent policies

Stemming from the above practical requirements, we carried out the study “Does provincial economic development in Vietnam foster internal migration?”

1.2 Research objectives and research question

The research is constructed to quantify the relationship between provincial economic development and migration flows across provincial level in Vietnam by specific objectives as follow:

- To have a further understanding about the role of income for migrant’s decision

- To interpret how urbanization impact on migration decision and to identify the migrant’s perception of urbanization for their moving motivation

- To study the impact of industrial structure on internal migration and propose policy implications for the future establishing of industrial areas

Research questions

The transference of human is natural and undeniable in the history of mankind all over the world In order to recognize above realities, it is deserved to assert that migration has possibility to fetch both opportunities and challenges for development

In spatial contexts and specific time, the interaction between migration and development will be different In a specific context of Vietnam, by using secondary data and analytical models, the goal of this study is to find relevant answers for these questions below:

- Do people tend to move to higher income provinces within Vietnam?

- Whether the establishing of industrial park could be seen as a good instrument for entice people to appointed destinations?

- Do Migrants choose high urbanization rate areas for their resettlement purpose in Vietnam?

1.3 Scope of the study

This study focuses on internal migration with economic is the main motivation,

so migrants were mentioned above include people who move from one province to another province, irrespective resettlement duration

We attempt to examine the migration (base on the GSO database) and the provincial development in 63 provinces (base on the statistic yearbook) in the 2005 –

2013 periods

1.4 Organization of the thesis

This thesis contains five chapters, order and names of the chapters are as follows: Chapter 1: Introduction

Chapter 2: Literature review

Chapter 3: Methodology

Chapter 4: Empirical results

Chapter 5: Conclusion and policy implications

Chapter 1 introduces the motivation of studying the effect of economic development

on migration The content of this chapter also stores the ability for application this study in reality Chapter 2 reviews the past theories about migration, the determinants

of migration and the relationship between economic development factors and migration Chapter 3 presents the way to construct this research, testing, hypothesis and model using to achieve the appropriate estimation Chapter 4 analyzes the empirical results after regressions This chapter also interprets the relationship among variables and displaces main findings The last chapter – chapter 5 concludes the content of the study and shows the policy recommendations This chapter also raises the limits of research and suggestions for further studies

CHAPTER 2 LITERATURE REVIEW

2.1 Concepts of migration

Migration is the changing of the domicile of individuals or groups of people It is

an integral part of the population dynamics and has close relationships with many important issues of sustainable development (Goldscheider, 1971) The changes in culture, economics, politics and society impact directly on migration decisions of people Therefore, migration could be seen as changes in demographic, which is synthesized from the changes in accommodation

There is always existed the interaction between migrants and new destination’s environment characteristics Migrants have to suffer the disturbed habitat cause by social characteristics and community nature at destinations Beside, migrants also contribute to the transformation of the destination’s properties, in reverse In addition, Sjaastad (1962) asserted that migratory movements could be relied on each migrant’s characteristics such as health condition, sex, age, literacy and so on

There are many different migration patterns, Fairchild (1925) classified migration

by many different types: migration rely on geographical locations such as low cultural level – high cultural level movement or high cultural level – low cultural level movement; migration rely on peaceful movement such as colonization movement or immigration – the individually motivated; migration rely on warlike movement such

as invasion migration, conquest migration

By another study, Petersen (1958) classified migration in other methods as follow: primitive migration, which is caused by ecological push, is the phenomenon of moving to cope with scarcity of natural resources These types of migration were happened since the dawn of mankind and could be divided into five categories:

“Wandering of peoples”, “Marine wandering”, “Gathering”, “Nomadism” and “Flight from the land”;forced or impelled migration, which is influenced by social institutions and could be also divided into four sub-categories: “Flight”, “Displacement”, “Coolie trade” and “Slave trade”; free migration or spontaneous migration, which is described

as its name: freely movement In this type of migration, people aware that by

settlement at the new destinations, they could reach a better living in the future, so they decide to come there; the last type of migration in this classification system is mass migration The incentives of mass migration are from circumstances, social patterns, milieux, disease outbreaks and so on

Nowadays, along with the development of science and technology and enhancements of social organizations, the delimitation of the country or territory becomes very clearly Thereby, migration could easily to recognize the existence of two major migration flows those are migration among countries (international migration) and internal migration International migration, which is one of greatest concern of economists about relationship between economics and demography, was presented in many scientific researches about the transfer of high skill labors from developing countries to developed countries Gillis, Perkins, Roemer & Snodgrass (1996) identified this phenomenon as “brain drain” problem In another aspect, internal migration just mentions about domestic movement flows and usually divided into three main categories: rural – urban migration, urban – rural migration and urban – urban migration Either internal migration or international migration, the purpose of spontaneous migrants is to improve their future

Our study focuses on investigate the internal migration, the specific case of Vietnam’s context Almost migrants, who decided to migrate by their own in the studied period, would like to find the opportunities at the destinations with their expectations to change their living toward positive direction In another expression, migration could be a motivation for country development and the socio-economic results by the matching of demand and supply in labor force in industrialization process

2.2 Migration theories

There are many researches about migration in the past, these studies are the solid arguments for motivations of migration, including the research of Harris and Todaro about the relationships among migration, unemployment and development was published in 1970; Lucas (1997) published the research about migration in developing countries; Lee (1969) propounded his theory of migration based on factors could affect on migration decision; Lewis (1954) introduced another theory to interpret

migration phenomenon through labor supplying; Marx and Fleischer (2010) proclaimed advantages and disadvantages of internal migration for socio-economic development in Viet Nam in their study published in 2010; Scott and Chuyen (2004) released their study about social mobility, regional disparities, and new trajectories of development in rural Vietnam Sriskandarajah (2005) stated in his study that one of reason for internal migration is the disparity in development among countries

In order to have visualizations about migration and factors impact on migration decision, we recapitulate some representative theory as follow:

2.2.1 Harris – Todaro theory

Harris and Todaro (1970) used the two-sector model to demonstrate the income gap between rural and urban areas is the motivations of rural-urban migration flows

In another specific expression, this is the one-way flow of migration People in rural areas, who have low income, will come to urban area for income improvement purpose only The authors used “expected earning” term to verbalize briefly the motivation of this type of migration By finding equilibrium of income combined with some assumptions, they asserted income disparity between rural areas and urban areas

is one of the most important motivations for migration decision

First of all, they assumed that the abundant labor is the main property in rural areas and the marginal productivity is equal to zero

Secondly, they assumed the price of goods in agricultural sector could be determined by goods in manufacturing sector by the formula: P = ρ(XM

XA) Where P is the price of agricultural goods determined by manufactured good, XM is the output of goods in manufacturing sector and XA is the output of goods in agricultural sector Finally, they assumed people in both rural and urban areas have the same chances

to find jobs, the unemployment status at urban areas and the redundant labor force at the rural areas contributed into the equilibrium conditions of income in both areas then the income equilibrium in their model was as follow:

𝑊𝐴 = 𝐿𝑀

𝐿𝑈𝑆(𝑊̅𝑀) Where:

WA is income in agriculture

LM is labor force in manufacturing

LUS is total labor in urban areas

𝑊̅𝑀 is the minimum wage in urban areas

Figure 2.1: The Harris-Todaro Migration Model

If 𝐿𝑀

𝐿𝑈𝑆 = 1, it means that WA = WM: there in no motivations for people to migrate But in reality, 𝑊𝐴 always different from 𝑊𝑀 Hence, people from rural areas always come to the higher income areas to find jobs This one-way flow creates the rural – urban migration flow

Another evidence to consolidate for above theory, Lucas (1997) stated that the reasons for people migrate in developing countries is to obtain the gain from high income stream at the destinations, to look for suitable jobs, to achieve the gain from their own capital, to access the information at the destinations or motivations cause by policies at the origin places

2.2.2 Lee’s theory

Lee (1969) expressed the migration motivations through “push” and “pull” mechanism: although there are many factors could impact on migration decision of any migrants but the negative factors from the origin areas is the main reason in interpreting leaving decisions In contrast, the positive factors at the destinations are

the dominant factors that people choose to immigrate; For example, climate at the origin areas have both positive and negative impact on residents there, but with many people who feel uncomfortable, they will decide to move At the destinations, there are also exists both signs of effect Some residents choose the suitable conditions there for their settlement Intermediate elements and personal factors, which are not associated with both origin areas and destinations such as perception, intelligence and personal sensitivities, are intervening obstacles factors Diagram below illustrates the most concise way for this theory

Figure 2.2: Lee’s push-pull theory

Source: Lee (1969)

These factors are not only regarded as qualitative factors but also are essentially quantitative factors by creating a threshold of migration Moreover, beside the factors from origin areas and from destination areas, there are many factors do not involve with both origin areas and destinations still have certain effects on migration, those are distances between origin areas and destinations, immigration laws, cost of household appliances transportation or factors involve to the life cycle’s stage

In conclusion, although Lee’s approach only summary in push-pull factors at origin areas and destinations but this theory reflected a full range of factors that impact on migrant selectivity This theory could be viewed as the most fundamental theoretical for further understanding and classification about migration

2.2.3 Lewis’s theory

Many similarities with Harris – Todaro theory, Lewis (1954) interpreted the motivations of migration in his study through the abundance of labors in rural areas

In his “unlimited supplies of labor”, he assumed the close economy with two opposing income from contradictory fields: livelihood wages from agricultural sector and income from industrial sector He compared the extreme low price of labor at rural areas with earning ability in urban areas This gap is one of the important motivations for migrants from rural areas Beside, land – the key input in production process in agricultural sector, suffers the law of diminishing to return because of its limitation characteristic Moreover, there is an increasing trend of natural population in rural areas lead to more labor surplus Simultaneously, the reinvestment activity of profits from business, dividends, extraordinary income could lead to the incessantly evolution

of industrial sector and increasingly labor demand Consequently, the supply of labor

is “unlimited” in both case of new industries are arisen and old industries are expanded People have too many legitimate reasons to leave rural areas where associated with arable land to join metropolitan areas

2.2.4 Other cognizance about migration

Migration decision is a very difficult decision because migrants have to leave their hometown, where they were familiar with the natural constraints such as family, relatives, friends, to come to new areas with the differences in living conditions, so migration decision is always affected by volatility and complexity factors However, Marx and Fleischer (2010), Scott and Chuyen (2004) emphasize the urban citizens have the significantly advantage in achieving the benefits from the development That

is one of the main reasons for rural citizens would like to move to urban areas In Vietnam context, poverty rate still high in rural areas and clearly the rural citizens here have less conditions to contact with those benefits, beside the average income of urban citizens is about double compared to rural citizens (Marx and Fleischer, 2010) Another main factor could have strong impact is the ability to improve migrant’s income (Harris and Todaro, 1970) beside other factors such as health care, living standard, environment factors, et cetera

De Jong (2000) built the model of migration behaviors with factors could influence

to migration decision making: expectations, gender role, family norms, household resources, community characteristics and human capital (migrant’s network) This

model clearly shows that there are many factors that can impact on the migration decision of any individual.

Figure 2.3: Factors impact on migration decision making

Source: De Jong (2000)

Base on the framework above, we could observe many other factors (except those factors are listed) affect on both intentions and behaviors of migrants Those are migration experience, budget, policy of the destinations, occupation and discrimination status

In briefly, there are a lot of factors could influence to migration decision, these factors extremely diversified In each type of migration, these diverse factors have implications in the different levels Hence, to have the understanding about what is the motivation for people to migrate and avoid the distorted glance, we have to investigate

in specific case for each type of migration

2.3 Empirical studies on migration

2.3.1 Economic development and other factors

Dang, Goldstein & McNally (1997) measured the economic development level of each province by two measurements in their study: the percentage of urban population (Urbanization) and number of industrial enterprises per thousand urban citizens

(industrial structure) of each province By using ordinary least square (OLS) method and assumption that everyone has the same living conditions and freely moving, the finding of this research is, migrants will tend to choose the more flourishing areas for their settlement Beside, Skeldon (2006) concluded that the citizens in urban areas could contribute in to the risen process of migration in the future Hence, it is undeniable the impact of urbanization ratio of each province on migration Similarly, industrial structure could be seen as the places to admit the large amount of employees, so provinces with high industrial structure ration have clearly trend to attract immigrants

Vogler and Rotte (2000) indicated that beside many factors could impact on moving decision of migrants such as trade, law, political situation, distance; income of both sending countries and receiving countries also have the certain influence to migration decision Also base on OLS method for their analyzing, they argued that the low income in the sending countries could lead to the exacerbation of migrate out motivation and vice versa In another words, the income differential among countries

is one of the most important factors impulse migration process

There are still exist many other factors could have strong impact on both economic development and migration displaced in many different study Population density, living standard, education facilities, recreation facilities, health services, distance and even policy are proxies could have the certain impact on both side of the research model (Dang, Goldstein & McNally, 1997)

Population density reflect the ability of high migration flow, id-est the opportunities of finding jobs are restricted Fryer (1979); Le and Rambo (1993) indicated that arable land in Vietnam is very limited in comparison to population growth It means that more and more people in rural areas with high population densities become more penury, so people tend to move to another area for subsistence purposes Therefore, positive relationship is expected between population density and migration, or the high population density will lead to the high migration flow Education facilities – another proxy to measure the literacy and the welfare of any administrative unit, showed the importance impact of “non-traded goods” on migration, it seem be seen as an indispensable index of development (Greenwood,

1985) Similarly, health also manifests the development level of any nation or any province In the poor environment, people could only care about their livelihoods so that they cannot care about health care or even they have no condition to reach to the health services because the lack of facilities Of course, health always plays an important role in the assessment of development level of any areas and thereby, also impacts on migration decision Recreation facilities are used to reckon by number of art performances or number of cinema shows, this proxy stands for entertainment attractiveness with the argument that the higher ratio of local entertainment shows, the lower ratio the youth out-migrants Dang, Goldstein & McNally (1997) Distance is measured by the actual distance (km) among the provinces, this measurement stand for the cost of migration and also the hindrance of moving It is clearly that the distance and migration have the negative effect because the long distance lead to high cost of moving and vice versa

2.3.2 Determinants of migration

According to Lee (1969), migration is a selective process, include:

Age factor: Adult and youth tend to migrate more than other groups at any form of migrations (Rogers & Castro, 1981) Youth and adult are often easily in adaptation to the new habitats at the new destinations Their qualifications such as proactive, flexible, youthful and ingenious are very necessary for enterprise Hence, youth and adult often overwhelm other age groups in high immigration rate areas

Figure 2.3: Model of migration by age adapted from Rogers and Castro 1986

Gender factor: Male or female migration flows are often depended on various factors Men’s qualifications are potency and power whereas women’s qualifications are nurture capacity and muliebrity (Keyes, 1987) Single women tend to participant freely in the labor force but married women are encumbered by their family Hence, the migrate decisions become different among men, single women and married

women According to De Jong (2000) about migration decision-making procedures,

the role of gender is expressed very clearly in making the decision to migrate

Marital status: Although in developed countries, it is hard to determine whether unmarried people or married people have high ability to migrate but in developing countries, the celibates have high migration rate than married people (Maxwell, 1988)

It is because the same conditions to move in developed countries for both celibates and married persons whereas there are many family ties in developing countries such

as responsibility to take care for their children or constraints due to habits and customs

Occupation: On both international and internal migration, high skilled labors always contribute highest proportion It is because they have many opportunities for good jobs at the large companies, but these companies often have the fixed locations,

so they have to move to match that labor demand In contrast, low-skilled labors have little chance to move rely on both job demand and their cost of moving (Altonji & Card, 1991)

Education: There are many studies about the relationship between education and migration Likely to occupation, almost these studies indicated the positive relationship between the two It means that the migrants with higher education level have the high trend to migrate, vice versa Rosenzweig (2007) indicated that many highly educated citizens from low income areas tend to move to high income areas for their permanent residence This phenomenon creates the exuberant migration flows among income disparity areas

2.3.3 Linkages between economic development and migration

Deshingkar (2005) stated that along with the economic development, the trend of temporary migration is growing There are many interpretations for this argument Firstly, transportation systems are increasingly improving, the movement of people

will become easier Thus, with the short distance between the origin areas and destinations, everyone can move for their work and come back home every day Secondly, the relative price of moving in developed society will become cheaper than less developed areas The cost of migration is no longer a hindrance People can also choose for their method and expediency transportation Hence, the frequency of moving is likelihood increase as a consequence of temporary migration instead of permanent migration Thirdly, the improvement of infrastructure quality and the high capacity of vehicle will shorten time of moving So, the decisions of moving will become easier These are the reasons for the risen in temporary migration in recent years

“Through virtuous cycles, migration also has certain contribution in reducing poverty and inequality” is the assertion in the study of Deshingkar (2005) This evidence showed that the selectivity and compatibility of migration has driven strong economic development In another interpretation, people with jobless from rural areas could come to the urban areas for job search purposes while factories in the urban areas could match to that labor force for their activities This process benefits for economic development in both rural and urban areas The empirical results in his study indicated that most of rural households have migrants join into urban areas in Indonesia

In the analysis about migration perspective of different among groups of economists, De Hass (2010) reminded the perspective of pessimism that brain drain is the handicap of migration sending areas but after many decades, they recognize the importance of migration in reduce poverty and inequality He also re-quoted from previous studies that migrants after many years resettle at new destinations have the trend to send back remittances to their origin hometown Obviously, their remittances surge as a money flow that influences both origin area and destination He also argued that migration – development nexus is a very complicated relationships, migration is not only an exogenous variable but also integral part of development processes In the opposite way, development has fundamentally heterogeneous impact on migration Kormendi & Meguire (1985) stated a transmission channel that growth rate of population in a certain extent lead to the increasing in labor force, which has an

important contribution in total factor productivity (TFP) growth, a determinant of development was found neoclassical growth theory In addition, the statistical analysis

of data from the General Statistics Office of Vietnam showed that general population growth rate equal to natural population growth rate plus net migration rate Above arguments show a very clearly and close linkage between migration and development Migration could contribute into economic growth process both at national level and household level Migration could also boost the relationship between origin areas and destinations, not only through the remittance that migrants send back their hometown, but also through the transfer of knowledge and skills, and thus contribute

to reducing the differences between regions (Marx and Fleischer, 2010)

In conclusion, the researches indicated the positive relationship between migration and economic development seems to overwhelm the researches showed the ambivalent or negative impact between its other Migration still silently happen every day as a natural process and its contributions to economic development still goes on all over the world The specific real context, however, the level of impact, impact method and the role of migration in economic development will become clearly differentiated Therefore, we attempt to find the quantitative answer for this relationship by specific method in the context of Vietnam with expectation of achieving the consistence estimation for further perception

CHAPTER 3 RESEARCH METHODOLOGY

3.1 Analytical framework and hypotheses

To have easily visualization about this entire study with complex relationships among variables, we first describe the impacts among observations under conceptual framework form as below:

Figure 3.1: The relationship among economic factors and in-migration

Many previous studies on the linkage between economic development and migration indicated the positive relationship trend because of many difference reasons By a study about migration in Vietnam in stage 1984 – 1989 (Dang,

Immigration

Economic factors

Provincial

Competitiveness

Index

Income Urbanization

Industrial structure

Population density Provincial GDP Education facilities Health service

Population

Goldstein, & McNally, 1997) showed the more developed area could lead to more migrants move in and vice versa, the less developed area prompt people to leave Vogler & Rotte (2000) also prognosticated that in the early phase of economic development, the higher development country have the higher migration rate It could

be explained by the improvement of moving conditions Firstly, development in infrastructure or transportation is the most important thing to remove the difficulties in moving among regions Secondly, network effect reinforces the migrant’s decision Migrants could feel secure in contact their relatives without any hindrance In some case, the latecomers have their own migration decision is based on spillover effect Finally, development leads to societal changes Traditional agricultural production is gradually replaced by other industries or many improvements in crop yields surge the huge amount of rural labor

Dang, Goldstein, & McNally (1997) asserted in their study since 1997 that provinces with high urbanization – which is measured by the ratio of urban citizen per total population – could become attractive provinces for migrants Urbanization presents for the development of a province or an administrative area It is undeniable that any province or area concentrate high metropolitan, that province or area could be seen as the higher development level than the others In our study, we appropriate using this measurement as a proxy for presentation of development level for each province Therefore, we could quantitative estimate its impact on in-migration With the real context of Vietnam that people tend to move to the large provinces, we construct the hypothesis as follow:

Hypothesis 1: Province with high ratio of urbanization has high in-migration flow

Similarly, industrial structure – which is measured by the ratio of number industrial enterprises per thousand populations – also a good measurement for economic development The opportunity of nonfarm employment is created by the industrial enterprises Thereby, both high skilled labors and unskilled labors could find jobs in these companies With the characteristics of a developing economy, Vietnam has many industrial enterprises gather in groups, which are concentrative located in industrial zones, or processing zones or high-tech parks Rely on flows of

employees move from everywhere to provinces have many industrial enterprises, we offer the below hypothesis:

Hypothesis 2: Province with high ratio of industrial structure has high

in-migration flow

By evidences of “migration contributes a huge labor force which is very necessary

in production increase” and “the earning at the destinations”, Harris and Todaro (1970) has launched the valuable analysis showed the positive correlation between migration and economic development Their study indicated that the higher potential income could have strong attractiveness of migrants Base on arguments for relationship between income and immigration just mentioned above, we construct the third hypothesis that:

Hypothesis 3: Province with high income per capita has high in-migration flow

Green Wood (1985) confirmed the important role of “non-traded goods” in attractiveness people of any area Hence, two important and familiar control variables – education facilities and health services – are included in to the model to test the influences of provincial amenities “Education facilities” is measured by the number

of schools per thousand populations for each province These schools contain kindergarten, elementary school, junior high school, high school, vocational secondary schools, colleges and universities “Health services” is measured by number

of hospital beds per capital

Population density is used to measure the absorptive capacity of any province This proxy is not only presented for the job opportunity in urban areas but also shows the poorer trend in high man-land ratio areas In our study, we hypothesize the high population density foster high migration rate

An indispensable indicator to estimate the impacts on migration is gross domestic product of each province This measurement clearly shows its impact on migrant’s decision Before decide to change their residences, people tend to collect information

at the destination for their certain faith about future living One of the first information

they need to know is GDP The high GDP province likelihood present for prosperous level and match migrant’s expectations

Vogler & Rotte (2000) believed that most developing countries or low developed countries have two typical characteristics: still keep their own traditional agricultural economies and high population growth A very simple argument that: more people automatically lead to more potential migrants Moreover, high population rate creates low income requirement in the labor market Hence, these two elements increase migration incentives

In other circumstances, some other studies make statements about the complex relationship between economic development and migration Bakewell (2008) emphasized this nexus is not only an ambivalent relationship but also the neglected correlation; Beyond the stage of early economic development, Vogler & Rotte (2000) also asserted that it is difficult to recognize the contribution of migrants come from less developed countries into economic development process The result from study of Maria and Lazarova (2012) showed that on both sending areas and destinations, about 70% migrants in their study sample endured economic backwardness condition The reasons for that phenomenon is high skilled migrants could not find out a suitable job

at destinations in order to maximize their internal resources This argument was sharply proved in countries with obsolete technology Deshingkar (2005) stated the benefit for economic development come from migration refer to many factors such as poverty reducing, inequality levels decreasing or the remittance increase; Phuong, Tam, Nguyet & Oostendorp, (2008) also proposed the same above argument that migration is a typical factor lead to economic development through increase household expenditures at the origin areas

The vague comments above have shown that it is not easy to have the most common vision for migration – economic development relationship unless that claim

is concretized for each region from time to time determined In this paper, we try to use the appropriate models in order to define the impact of provincial economic development factors on migrant’s decisions – whether or not to migrate? The scale of this study is done within 63 provinces during 8 years from 2005 to 2013 (although the

duration contains 9 years but we could not collect information for migration flow in 2006)

In order to capture the content and mechanism of variables and its impacts on migration, we epitomize the definitions and expected signs by the table as below:

Table 3.1: Variable definitions and its expected signs

sign

Industrial structure Number of industrial enterprises per thousand

Population Density Population/square kilometer for each province person/km 2 +/-

Education facility Number of schools per thousand populations

Health service Number of hospital beds per thousand

populations for each province

method could lead to the inconsistent estimation.Model is selected for this study must

be contains the properties to satisfaction these knots

The most appropriate method could be constructed to avoid the bias results cause

by previous problems is structural equation model (SEM), as expressed in the next matter We also implement the common panel methods after SEM as robustness tests

3.2.1 Structural equation model (SEM)

Our final goal is to investigate the quantitative impact of three economic variables (urbanization, income and industrial structure) on in-migration However, as arguments in the first section about the complex relationships among variables such as the economic variables could not only impact on migration but they also impact on each other or in the reverse trend, migration can impact on these economic variables,

it is not simple to achieve an accurate estimation by common panel data methods It is because results obtained from these methods could be biased, which is relied on the endogenous problem, causality problem or other disabilities of data

To solve the complicated nexuses among variables, we have to estimate step by step the predicted value form each single equation, then embed that predicted value into the simultaneous equations This procedure will create phases and return by iterations and therefore exterminate the endogenous problem, so we could obtain appropriate estimation at the final step This process is applied in structural equation model, which is contained both structural equation and behavior equations There are four of equation system types: simultaneous equation system; seemingly unrelated equations system; block recursive equation system and recursive equations system

In our study, the endogenous variables in each single equation play the role of dependent variables in the target equation and the existing of causal chains in the system of equations Hence, the applying of simultaneous equation system is suitable for achieving consistent estimations

The general model of simultaneous equation system is described as follow:

SEM 1: 𝑌1 = 𝑎10+ 𝑎11𝑌2+ 𝑎12𝑌3+ 𝑎13𝑌4+ 𝑎14𝑋1+ 𝑎15𝑋2+ 𝜀1

SEM 2: 𝑌2 = 𝑎20+ 𝑎21𝑌1+ 𝑎22𝑌3+ 𝑎23𝑌4+ 𝑎24𝑋1+ 𝑎25𝑋2+ 𝑎26𝑍1+ 𝜀2

SEM 3: 𝑌3 = 𝑎30+ 𝑎31𝑌1+ 𝑎32𝑌2+ 𝑎33𝑌4+ 𝑎34𝑋1+ 𝑎35𝑋2+ 𝑎36𝑋3+ 𝜀3

SEM 4: 𝑌4 = 𝑎40+ 𝑎41𝑌1+ 𝑎42𝑌2+ 𝑎43𝑌3+ 𝑎44𝑋1+ 𝑎45𝑋2+ 𝑎46𝑋3+ 𝜀4

The models SEM 1, SEM 2, SEM 3 and SEM 4 always have close relationships with each other The result of iteration from equation 1 is assigned in the rest 3 equations for the next step Similarly, result of iteration from equation 2 is the material for estimation in equations 1, 3, 4, et cetera After processes with many iterations and results replacement in each equation, we obtain the expected estimation coefficients:

𝑎4𝑥 This result could be seen as the most consistent estimation in investigation of the impact of economic variables on migration

The most advantage of this model is the solving of endogeneity and causality problem In addition, by using SEM, we could include instrument variables into the model with ensuring consistence final results

3.2.2 Other common panel data methods

We first use Pooled Ordinary Least Square (OLS) model, a common constant method to estimate the influence of economic development proxies on in-migration flow, then we use Fixed effects model (FEM) and Random effects model (REM) respectively in analyzing the impact of economic development factors on migration According to Roberts & Whited (2012), panel data with FEM and REM technique could be seen as solutions for ameliorate endogeneity problem but these methods could not be thorough treatments That is the reason we apply all FEM, REM and other methods in our study

By using many different testing methods such as F-test, Breusch – Pagan LM test and Hausman test, we could find out which is the most appropriate model among all

of them

a Pooled OLS model

Pooled OLS model is one of the most popular method has been used with the general model as follow:

𝑌𝑖𝑡 = 𝛼0+ 𝛼1𝑋𝑖𝑡+ 𝜀𝑖𝑡, 𝑖 = 1, … , 𝑛; 𝑡 = 1, … , 𝑡 This model is a very restrictive model with specific constant coefficient and many assumptions such as the parameters of coefficients and error term 𝜀𝑖𝑡 are linear, there

is no correlation between independent variables and error term over time for a given individual, heteroskedasticity or serial correlation phenomena also do not exist If

these conditions are mentioned above could be satisfied, then estimations from this model could be consistent

However, in reality the error term 𝜀𝑖𝑡 seem to be correlated with the explanatory variables over time for a given observed unit and makes inconsistent estimation then leads to distortion in estimate the relationship between dependent variable (in-migration flow) and explanatory variables (provincial development) That is the main drawback and becomes the reason in using many other models in the next step of this study

b Fixed effects model (FEM)

The purpose of using FEM is to analyze the impact of independent variables on dependent variable that vary over time The general model is described as follow:

𝑌𝑖𝑡 = 𝛼𝑖 + 𝛽𝑋𝑖𝑡+ 𝜀𝑖𝑡Where

𝛼𝑖 (𝑖 = 1 … 63) is the undefined intercept for each province (63 province-specific intercepts)

𝑌𝑖𝑡 is dependent variable where 𝑖 present for province and 𝑡 present for year

𝑋𝑖𝑡 is explanatory variable (provincial development)

𝛽 is the coefficient of 𝑋𝑖𝑡

𝜀𝑖𝑡 is the error term

This model creates constant slopes but different intercept across province, does not vary over time It means FEM ignore the effect of time-invariant characteristics and allows us to evaluate the net effect of the independent variables on the dependent variable

Another important assumption is the correlation between explanatory variables and error term Therefore, if FEM present and have the correlation with independent variables 𝑋𝑖𝑡 then Pooled OLS estimators are inconsistent In the other words, using FEM is the way to investigate the reasons of changing within a province In the case of omitted variables that could correlate with others in the model, FEM could not explore the consistent estimators In order to surmount these limitations, REM could be an effective alternative

c Random effects model (REM)

Unlike FEM, REM assumes the variation across province is random and does not correlate with the explanatory variables included in the model When the differences cross province impact dependent variable happen, REM is one of the appropriate methods to obtain the consistent estimators The structure of equation is described as follow:

𝑌𝑖𝑡 = 𝛼0+ 𝛼1𝑋𝑖𝑡+ 𝜀𝑖𝑡 𝑤ℎ𝑒𝑟𝑒 𝜀𝑖𝑡 = 𝜗𝑖 + 𝛾𝑖𝑡

Where

𝑌𝑖𝑡 is the dependent variable where 𝑖 present for province and 𝑡 present for year

𝑋𝑖𝑡 is explanatory variable (provincial development)

time-of the model could be lead to inconsistent estimators whenever we omit relevant variables

3.2.3 Testing for appropriate models

a F-test for choosing FEM or OLS

In order to find out the model with the most accurate results, we apply many different tests

Firstly, we base on F-test to test whether FE Model or OLS Model have more reliable estimates Rely on functional form of FE model: 𝑌𝑖𝑡 = 𝛼 + 𝜇𝑖+ 𝛽𝑋𝑖𝑡+ 𝜀𝑖𝑡,

we obtain the null hypothesis H0 : 𝜇1 = 𝜇2 = ⋯ = 𝜇𝑛−1 = 0 F-test could be calculated by the formula:

𝐹 =(𝑅𝑆𝑆 − 𝑈𝑅𝑆𝑆)/(𝑁 − 1)𝑈𝑅𝑆𝑆/(𝑁𝑇 − 𝑁 − 𝐾) ~ 𝐹𝑁−1,𝑁(𝑇−1)−𝐾

Where:

RSS is restricted residual sum of square in OLS model

URSS is unrestricted residual sum of square in FE model

If F value > F* value: H0 is rejected, it means that at least one unit of 𝜇𝑖 different from

0, so FEM is better than OLS

In contrast, if F value < F* value: H0 is fail to rejected, it mean that all unit of 𝜇𝑖 = 0,

in this case OLS will better than FEM

b Breusch - Pagan LM-test for choosing REM or OLS

This test is used to determine the appropriate model between OLS method and RE method The functional form of RE model is described as follow:

𝑌𝑖𝑡 = 𝛽 + 𝛽1𝑋𝑖𝑡+ 𝑒𝑖𝑡+ 𝑢𝑖, 𝑎𝑛𝑑 𝑣𝑖𝑡 = 𝑢𝑖+ 𝑒𝑖𝑡

The null hypothesis H0: 𝜎𝑢2 = 0 where 𝜎𝑢2 = 𝑐𝑜𝑣(𝑣𝑖𝑡, 𝑣𝑖𝑠)

The alternative hypothesis Ha: 𝜎𝑢2 ≠ 0

LM test could be calculated by the formula:

𝐿𝑀 = 𝑁𝑇

2(𝑇 − 1)|

∑𝑁 (∑𝑇𝑡=1𝑒̂𝑖𝑡)2 𝑖=1

∑𝑁𝑖=1∑𝑇𝑡=1𝑒̂𝑖𝑡2 − 1| ~ 𝜒

2

In the case of 𝜒2 > 𝜒∗2 : null hypothesis is rejected, FEM is favored than OLS

Vice versa, in the case of 𝜒2 < 𝜒∗2: null hypothesis is fail to rejected, OLS is favored than FEM

c Hausman test for choosing FEM or REM

As mentioned in previous section, there are several different between FEM and REM, while FEM ignore the effect of time-invariant characteristics and allows us to evaluate the net effect of the independent variables on the dependent variable, REM assumes the variation across province is random and does not correlate with the explanatory variables included in the model Hence, to examine what model could propound better estimations, we use Hausman test to find the appropriate method

Hausman test’s result could be calculated by:

(𝛽𝐹𝐸 − 𝛽𝑅𝐸)′[𝑉𝑎𝑟(𝛽𝐹𝐸) − 𝑉𝑎𝑟(𝛽𝑅𝐸)]−1(𝛽𝐹𝐸− 𝛽𝑅𝐸)~ 𝜒2

Null hypothesis H0: estimator of REM is efficient and consistent than FEM Alternative hypothesis Ha: estimator of REM is inconsistent so FEM choosed

In the case of 𝜒2 > 𝜒∗2 : null hypothesis is rejected, FEM is favored than REM Vice versa, in the case of 𝜒2 < 𝜒∗2: null hypothesis is fail to rejected, REM is favored than FEM

3.3 Model specification

With expectation to achieve the consistent estimation for impacts of economic factors on migration, we construct many different models to investigate the advantages and disadvantages in application each of them The characteristics of the vague and complex relationships among variables allow us to in-depth research through many models to solve the data disabilities and causality as well as endogeneity problem

3.3.1 Structural equation model (SEM)

As the arguments about the complex relationships among economic indicators such as in-migration impacts on urbanization, income and industrial structure also impact on urbanization, in-migration impacts on income, urbanization and industrial structure impact on income as well, et cetera We conduct the process of step by step

to solve each impact among interactive proxies whereby we could find out the last results – impacts from three economic variables on in-migration, described by the simultaneous equation as below:

SEM 1: urbanit = α1in_migit+ α2incomeit+ α3in_structit+ α4densityit+

α5pgdpit+ α6eduit+ α7healthit+ εit

SEM 2: incomeit = β1in_migit+ β2urbanit+ β3in_structit+ β4densityit+

β5pgdpit+ β6eduit+ β7healthit+ ϑit

SEM 3: in_structit = γ1in_migit+γ2pciit+ γ3urbanit+ γ4incomeit+

γ5densityit+ γ6pgdpit+ γ7eduit+ γ8healthit+ φit

SEM 4: in_migit = δ1urbanit+ δ2incomeit+ δ3in_structit+ δ4densityit+

δ5pgdpit+ δ6eduit+ δ7healthit+δ8popit+ ωit

First of all, we use the number of migrants who move in a province as the dependent variable then we use three proxies to measure the economic development level of each province, which is described in detail below:

Based on measurements are available and solid arguments about provincial economic development has mentioned in previous chapter, both “urbanization” variable, which is measured by the ratio of people who live in urban area and

“industrial structure” variable, which is measured by the ratio of industrial enterprise per thousand urban citizen in each province, are used to describe the provincial development In addition, we add new index into the models: income This variable is measured by income per capita The reason for this index addition is, income could be seen as a meritorious proxy to measure the development and now available in statistic yearbook datasets, differ from study of Dang, Goldstein, & McNally (1997), they measured the level of economic development index by kilogram rice per head because the lack of information at that time Density stands for population density in each province, is measured by number of population divide by square kilometer PGDP is provincial gross domestic product which is calculated at current price According to GSO, PGDP (GRDP as defined by GSO) is the important eco-socio general index which reflects the final results of production activities within a province in a certain period PDGP could be calculated by 3 methods: Production method, income method and expenditure method but in reality, the calculation of provincial gross domestic product only come from production method because of many reasons such as the lack

of information or the conditional of applying in calculation Whereby, PGDP is calculated as the formula as below:

PGDP = Total all value added of all industries + Provincial import tax – Production subsidies

By adding PCI, which stands for provincial competitiveness index, is used to assess the ease of economic governance in incentive investment or doing business of

63 provinces and cities in Vietnam issued by Vietnam Chamber of Commerce and Industry (VCCI), we could investigate the appropriate estimation of its impact on industrial structure This variable could be seen as the instrument variable, we had specific explanation in the previous section Although on overall, this proxy could influence to the last results through this system of equations but in this section, but in this step we assume that it does not impact on other variables except industrial structure “Edu” means education, this index is the number of schools per thousand

populations in each province, contained kindergarten, elementary school, junior high school, high school and vocational secondary schools, colleges and universities Health is measured by number of hospital beds per thousand citizens in each province The last index, “pop” mean population, which is calculated by thousand people for each province

These equations replace each other through iterative mechanism The last results are demonstrated by the coefficients, which reflect the impacts from urbanization variable, income variable, industrial structure variable and other control variables on in-migration variable

Although SEM procedure have to calculate by many complex operation but the most validity of this estimation method is to solve almost defect of data and extrude endogeneity problem cause by characteristics of this kind of study Hence, by using SEM we might achieve the most accurate results instead using other methods

3.3.2 Common panel data techniques

In common panel data techniques – the necessary methods could not be missed, those are three analysis methods in our process to achieve the estimation of economic development – migration relationship: Pool OLS method, Fixed effects method (FEM) and Random effects method (REM) respectively Although there are certain limitations in applying these models into the research with many complex relationships among variables but they are still necessary tools in verification and determination for economic development and migration relationship Hence, in panel data analysis process, we could not ignore the using of these models as an important step of verification

With the addition of income proxy (which is measured by income per capita) that

we had mentioned in previous sections for its role in the assessment level of economic development, we could obtain solid measurement to measure the development of each province By changing variables which is presented for the development of provinces

in different ways to have more options in interpreting relevant results, we achieve empirical models as follows:

Model 1: In-mig it = α o + α 1 Urban it + α 2 density it + α 3 PGDP it + α 4 edu it +

Model 4: In-mig it = α o + α 1 Urban it + α 2 income it + α 3 in_struct it + α 4 density it +

α 5 PGDP it + α 6 edu it + α 7 health it + α 6 pop it + ε it

Income is measured by income per capita

In_struct stands for industrial structure, which is measured by ratio of industrial enterprises per thousand persons

PGDP is provincial gross domestic product which is calculated at current price Density stands for population density on each province, measured by number of population divide by square kilometer

Edu means education, this index is the number of schools on each province, contained kindergarten, elementary school, junior high school, high school and vocational secondary schools, colleges and universities

Health is measured by number of hospital beds on each province

Pop stands for population, which is measured by number of citizen in each province

3.3.3 Migration criteria

The indicators used to measure migration are very diverse including the simple methods and complex methods Each method is applied a specific technique based on the collected database

 According to General Statistics Office of Vietnam (GSO), net migration rate (NMR) is the difference between the number of immigrants and out-migrants within

NMR: Net migration rate

I: The number of immigration within a year

O: The number of out-migration within a year

Ptb: The average population (or mid-year population)

Or calculation in another method: NMR = IMR – OMR

Where:

NMR: Net migration rate

IMR: Immigration rate

OMR: Out-migration rate

 Immigration rate is the number of people from other areas (out-migrate areas) immigrate to an area during the study period (usually a calendar year) on average over

1000 people of that area (immigrant area)

Immigration rate is calculated by the following formula:

IMR(‰) = I

Ptb∗ 1000

Where:

IMR: Immigration rate

I: The number of immigrants within a year

Ptb: The average population (or mid-year population)

 Out-migration rate is the number of out-migrants of an area in the study period (usually a calendar year) on average over 1000 people of that area

Out-migration rate is calculated by the following formula:

OMR(‰) = O

Ptb∗ 1000 Where:

OMR: Out-migration rate

O: The number of out-migrants within a year

Ptb: The average population (or mid-year population)

3.3.4 Instrument variable

As the definition of Vietnam Chamber of Commerce and Industry (VCCI), PCI is

an index that could assess the ease of economic governance in incentive investment or doing business of 63 provinces and cities in Vietnam Base on this index, any investor

or business man could define the level of provincial promoting in development of private sector, one of expected criteria in business decision PCI comprises 10 indices which measure the influence of economic governance on private development sector

as follow:

 Respond business start-up at a low entry costs level

 Facilitate enterprises easily to access land and security of business premises

 Create an equitable business information and transparent business environment

 Charge the minimal informal fee

 Assist enterprises save their time in bureaucratic procedures settlement and inspections

 Limit private activity infringement from policy biases towards joint venture, foreign, or state

 Help enterprises to overcome difficulties flexibly and creatively

 Support many other services for developed and high-quality business

 Promulgate skilled labor training policies

 Make fair and effective legal procedures in disputes resolution

Thereby, PCI could be seen as a proxy to bushel the effect of differences in policies, in another way opened policies lead to more prosperous provinces, which

may present for the attractiveness of each province on development dynamics Therefore, this index clearly has a tremendous impact on the development of each province but in reality do not impact on decision whether or not to migrate of any citizen

Because of the above characteristics of the PCI, we recognize that there is high ability of its impact on industrial structure, so we use it as an instrument variable to add in to the model in our research

3.4 Data sources

We collect data from GSO (General Statistics Office) for migration flow among

63 provinces from 2005 to 2013 but exclude 2006 because the lack of information This data is about in-migration ratio for provinces By using this ratio, we could measure the number of people who move in every province or city by multiplying with the number of mean population

The 3 main indicators to measure provincial economic development, we collected from many versions of Statistical Year Books and GSO database The first variable is urbanization which is collected from GSO database, the second variable - income - and the third variable industrial structure are collected from Provinces’ Statistic Yearbooks

The instrument variable PCI is collected from Vietnam Chamber of Commerce and Industry (VCCI) Only 44 provinces rated whit PCI in 2005, so there are 19 provinces did not rated Dataset from 2006 to 2013 was enough for all 63 provinces About household level indicators using in other control variables, such as living standards, education and health, we obtained from many different versions of provincial statistical yearbook