Effects of education on earnings the case of ben tre province

Ben Tre Statistical Office Gross Domestic Product General Statistical Office Human Capital Earnings Function Ordinary Least-Squared Estimation Rate of return to education Vietnam Househo

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

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VIETNAM- NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

EFFECTS OF EDUCATION ON EARNINGS:

THE CASE OF BEN TRE PROVINCE

By

Mr NGUYEN MINH QUANG

A Thesis Submitted in Partial Fulfillment of the Requirements of the Degree of

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! 'IIIt.t Academic Supervisor '

Dr NGUYEN HOANG BAO

HO CHI MINH CITY, 2010

• ACKNOWLEDGEMENT

To be able to complete this thesis, I have been received a great support from many people Firstly, I would like to express my appreciation and special thanks to Dr Nguyen Hoang Bao, the author's supervisor, who has been giving me very valuable instruction, advising and comments for the successfulness of my thesis Secondly, I

am indebted to all teachers and staffs of the Vietnam- Netherlands Program at the University of Economics Ho Chi Minh city Especially, Assoc Prof Karel Jansen, Assoc Prof Nguyen Trong Hoai for their best supports and valuable comments Thirdly, I would like to express sincere thanks to Dr Nguyen Huu Dung who has provided valuable comments and instructions for completion of this thesis Fourthly,

I am grateful to my manager and colleagues for their encouragement and support during my study duration Fifthly, I would like to express my special thanks to all

my friends, especially Mr Le Cong Tam, and Mr Tran Nam Quae having given me

a lot of valuable opinions and support in the process of my thesis completion Finally, I am indebted to my family and others who gives me great encouragement and support for my study

CONTENTS

Page

CERTIFICATION i

ACKNOWLEDGEMENTS ii

ABSTRACT iii

CONTENTS iv

ABBREVIATION ix

LIST OF TABLES X LIST OF FIGURES xi

Chapter 1: Introduction 1.1 Problem statement 1

1.2 Objectives of the thesis 2

1.3 Research question and research hypothesis 3

1.4 Data and methodology 3

1.5 Organization of the research 4

Chapter 2: Literature review 2.1 Theoretical framework 5

2.1.1 Key definitions 5

2.1.1.1 Human capital 5

2.1.1.2 Rate of return 6

2.1.2 The link between education and farm productivity 6

2.1.3 The relationship between education and income 8

2 1.4 The theory for human capital 10

2.1.4.1 Measuring the cost 13

2.1.4.2 Measuring the benefits of education 13

2.1.4.3 The internal rate ofreturn to schooling 14

2.1.5 Mincerian earnings function methods 17

2.1.6 Other methods 19

2.2 Review of empirical studies 20

2.2.1 Impact of schooling and education levels to earning 20

2.2.2 Gender disparity on rate of return to education 21

2.2.3 Regional disparity on rate of return to education 22

2.2.4 Economic sector of employment disparity 22

2.2.5 Impact of education on earnings Vietnam 23

2.3 Chapter remarks 24

Chapter 3: Methodology and analysis framework 3.1 Model specification 2 7 3.2 Definition of variables and measurement 3.2.1 Dependent variable 29

3.2.2 Independent variable 29

3.3 Data set and variable measurement 33 3.4 Steps to estimate parameter in regression model 3 5

Chapter 4: Empirical analysis and research results and discussions

4.1 Overview of education on earning in Ben Tre province

4.1.1 Geographic 36

4.1.2 Educational level of workers 3 7 4.1.3 Human resource of Ben Tre province 3 8 4.1.4 Labor force 39

4.1.5 Number of workers 39

4.2 Descriptive analysis and hypothesis 39

4.2.1 Educational status and labor structure in Ben Tre province 40

4.2.2 Others general information of workers 41

4.3 Earnings of workers classified by categories 4.3.1 Earnings classified by education level 41

·~ 4.3.2 Earnings classified by gender 42

4.3.3 Earnings classified by regions 42

4.3.4 Earnings classified by sectors 42

4.4 Empirical results of effects of education on earnings 4.4.1 Estimation of rate of return with model 1 43

4.4.2 Estimation of rate of return with model 2 45

4.5 Chapter remarks 47

Chapter 5: Conclusions and policy recommendations 5.1 Main findings 49

5.2 Policy recommendations 50

5.3 Limitations of the research and further study suggestions 52

REFERENCES 53

APPENDICES

Appendix 4.1 Geographic of Ben Tre province, period 2004-2006 63

Appendix 4.2 Gini coefficients in the Mekong Delta 63

Appendix 4.3 Region population of Ben Tre province, period 2005-2006 63

Appendix 4.4 Population structure of Ben Tre province, period 2004-2006 64

Appendix 4.5 Population density of Ben Tre province in 2005 in comparison with other provinces of Mekong Delta 64

Appendix 4.6 Working population and employment of Ben Tre province, period 2005-2006 ··· 65

Appendix 4 7 Frequencies classified by educationallevel 65

Appendix 4.8 Frequencies classified by sectors 65

Appendix 4.9 Meaning of earnings classified by educational level 65

Appendix 4.1 0 Meaning of earnings classified by gender 66

Appendix 4.11 Meaning of earnings classified by regions 67

Appendix 4.12 Meaning of earnings classified by sectors 67

Appendix 4.13 Estimation results of model 1 67

Appendix 4.14 Estimation results ofmodel2 68

Appendix 4.15 t-test year schooling and sectors 68

Appendix 4.16 t-test experience and gender 69

Appendix 4.17 t-test year schooling and gender 69

Appendix 4.18 t-test working time and sectors 70

Appendix 4.19 t-test working time and regions 70

-Appendix 4.20 t-test working time and gender 71

Appendix 4.21 t-test land cultivated size and regions 71

Appendix 4.22 Oneway working time and educational level 72

•

Ben Tre Statistical Office

Gross Domestic Product

General Statistical Office

Human Capital Earnings Function

Ordinary Least-Squared Estimation

Rate of return to education

Vietnam Household Living Standard Survey Vietnamese Dong

United States Dollar

LIST OF TABLES

Page

Table 2.1 Summarize the main results of the past studies 26

Table 3.1 Summary and defines dependent variable and all independent variables 32

Table 4.1 Means of per capita income classified by educational level 41

Table 4.2 Means of per capita income classified by gender 42

Table 4.3 Means of per capita income classified by regions 42

Table 4.4 Means of earnings per capita income classified by sectors 43

Table 4.5 Estimation results of model 1 43

Table 4.6 Estimation results ofmodel2 46 Table 4 7 Rate of return of earnings of each educationallevel 4 7

LIST OF FIGURES

Page Figure 2.1 Effect of education on farm production 8 Figure 2.2 Effect of year of schooling on earnings 9 Figure 2.3 Stylized age-earnings profile of secondary and university

graduates 15 Figure 2.4 Relationship between education and income level 16 Figure 4.1 The structure of educational level in Ben Tre province 40

CHAPTER I INTRODUCTION 1.1 PROBLEM STATEMENT

Living standard level is different from everywhere, Knight and Sabot (1990) stated that there was an inequality of income among households In the rural areas, there is

a lot of households which are living in poor condition due to low income Vietnam

is considered as one of the poor countries in the world The average income level is just about one dollar per head per day, and 20.0 percent of population living below poverty line (GSO, 2006) Therefore, the improvement of income is very important, especially for poor households to escape from present bad situation

The benefits of formal education have been known for a long time Mincer (1974) showed that the benefits of formal education on individual earnings Lucas (1988) proved that benefits of education within a village known as the side effect Moreover, education can benefit the entire country at national level In short, education can benefit people from individual, household, local community, and country level

The positive relationship between education of a worker and his/her earnings and productivity has been witnessed in many countries (Schultz, 1988) In addition, educational attainment and earnings inequality still prevails between men and women, rural and urban areas, and between the public and private sectors as well These issues require further understanding and examine the linkage between education and earnings

Ben Tre province, located at the downstream of the Mekong River's basin, is known for agriculture-based society This is one of the smallest inland area 2,315 squared kilometres among Mekong Delta region, but its population density ranks at the fourth place GDP growth rate in 2001-2005 is of 9.22 percent The income per capita is of 4.5 million in 2001, 7.5 million in 2005, 8.5 million in 2006 and 950 USD in 2010

In terms of education level, the literacy ratio of Ben Tre province's population is of

97.4 percent (BSO, 2006) The labor force accounts for 72.73 percent of the population (BSO, 2006) However, the quality of this labor force is poor in terms of education and in terms of working skills In 2006, 60 percent of the labor force is unskilled labor Only 30 percent of the workers get vocational certificates (BSO, 2006) Although there is high literacy (97.4 percent), the general education level of population is still at low rate (52 percent) household heads under primary school In addition, the numbers of poor households accounted for 18 percent of the total households in Ben Tre province and reduce to less than 10 percent in 2010 (BSO, 2006)

The opening of Rach Mieu's bridge in 2008, connecting Ben Tre province to other provinces, and socio-economic conditions of human capital, and comparative advantage to reduce the poverty rate and improve income of its people in Ben Tre province Thus, how to raise people's income is a big concern While the benefit of education has been generally demonstrated, the benefit of education to income is not clearly explored This socio-economic context inspired researcher to conduct a study on the effects of education on earnings in Ben Tre province

The purpose of this study is to analyze the effects of education on earnings of workers, and to examine the rates of return to education levels Especially, it also takes into account the differences in returns to education by controlling wage differences, geographical regions, economic sectors, and gender in order to draw out policy implication for education development in Ben Tre province To fulfill these objectives, rates of return to education are used as an instrument to measure educational effects on earnings It is commonly recognized that higher education is tantamount to higher earnings, or in another words earnings positively relate to education This research justifies the importance of the education level by examining the effects of education on earnings in Ben Tre province by showing how the change in each year of schooling corresponding with the change in earnings

1.3 RESEARCH QUESTIONS AND HYPOTHESES

To match the above objectives, the research focuses on the following questions as:

• Whether years of schooling effect on earnings or not?

• Do education levels significantly determine earnings of wage earners?

• Is earnings differential between experienced and inexperienced workers significant?

• Do public sector workers earn higher return in comparison with private sector?

• Is there any gender and regional disparity in return to education?

In the context of significant market reform towards to more market-oriented economy and with further educational and employment reforms, this research is expected to find out factors affect the rates of return to education in 2006 The main research hypotheses are to test whether there are positive effects of education on earnings and rate of returns, classified in different levels of schooling in Ben Tre provmce

1.4 DATA AND METHODOLOGY

The main data set is drawn from VHLSS 2006 In addition secondary data are collects from various sources including, academic textbooks, publications and policy documents, General Statistic Office (GSO), Ben Tre province Statistic Office (BSO), the World Bank, and Asia Development Bank Both descriptive and multivariate analysis is employed to answer the research questions Data collected from VHLSS 2006 replies on descriptive analysis on general information relating to education in Ben Tre province, and the econometric analysis applied the OLS method to examine the impact of education and earnings This analytical approach

is popularity used in is the study of human capital earnings functions conducted by Mincer (1974) The approach helps calculating the rates of return to year of general schooling and to year of schooling at different levels of education

Our sample is comprised of only the wage earners aged from 15 years to 60 years and above whom having job as their primary and main activity during the past 7 days prior to the survey As a result, the size of the sample is 143 observations in 8

districts and 24 communes Data will be extracted by Stata software Standard statistical tests and estimation of the model parameters are done using SPSS and Stata softwares

1.5 ORGANIZATION OF THE RESEARCH

The thesis is divided into five chapters The first chapter provides and overview of the research and the research methods used The second chapter presents for many conceptual frameworks, theories and empirical studies will be reviewed In that, first section is definitions/concepts of factors effecting education and earnings; describes the theoretical framework analyze education-earnings relation in next section; and a review of empirical studies in education-earning relation and rate of return to education is followed discussing similar issues in other countries The third chapter presents the specification model, which shows the determinants of education on earnings Data sources of the analysis will be introduced in this part The chapter four presents overview of economic reforms in Ben Tre province in 2006, and use regression model to provide empirical support for testing the hypothesis Finally, the chapter five is for main findings from study, which to draw useful policy implications, limitations of the research, and recommendations for further study in Vietnam

CHAPTER2 LITERATURE REVIEW

This chapter presents theoretical, analytical framework and related empirical studies

on the effect of education on earnings The chapter begins with some key definitions that are frequently used in theories Then, the second section presents relevant theories on the links of education and income, human capital, the Mincerian earning function method, and others The third section is to review empirical studies on the relationship between education and earnings conducted in developing countries, countries in transition, and Vietnam in particular The final section is for chapter remarks

2.1.1.1 Human capital: As defined by (Rosen, 1987:681 ), human capital refers to

"the productive capacities of human beings as income producing agents in the economy" The building up of human capital can work through education and training as well as through improvements in health and nutritional status Education and training provides knowledge and skills so as to enhance the efficiency at works; better health and nutritional status assure greater physical strength, and thus ability

to provide more hours of labor

The definition used by (Husz, 1998:9) is as follow: "By human capital we mean the time, experience, knowledge and abilities of an individual household or a generation, which can be used in the production process"

Gillis, et al (1996:256) broadly defined 'education' as all forms of human learning,

or more narrowly, is the process of learning in specialized institutions frequently

called 'school' It is without a doubt that people can accumulate knowledge from wherever they are: at home, at school, at a working place or on the job, and in the community Basically, there are three types of education that has drawn from the channels that educational services come to people

The first type is formal education, which implies the process of learning in institutions and schools It usually targets official school-age population who has not yet started working for an income Formal education normally includes primary, secondary, and tertiary education In Vietnam, secondary education is divided into two stages The first stage is called lower secondary education At the second stage, pupils can enter upper secondary education, technical secondary education, or secondary vocational education Primary and lower secondary education forms basic education Following secondary education is tertiary education, which includes college, university education and higher (World Bank, 1996:9)

The second type is non-formal education, which involves an organized programmed

of learning which takes place outside of schools in the short period of time, often providing occupational skills and application of knowledge rather than theoretical subjects that pupils are taught in formal education

The third type, (Gillis et a/, 1996:255) defines as "informal education is learning

that takes place outside any institutional framework or organized program People learn many important things at home, on the job, and in the community"

The definitions, therefore, are consistent with the traditional concept that expenditure on education, training, medical care are investment in capital (Becker, 1993) Specifically in education sector, expenditure on education whether by the state or the households have been treated as investment flows that build-up human capital (Schultz, 1961 )

2.1.1.2 Rate of return

The fundamental insight of human capital investment is the rate of return Rate of return refers to the compensatory nature of earnings on investment in human capital (Eatwell eta/, 1991) A person who contemplates entering one of the occupations or

profession must look forward to a long period of training and costly investment before any income is generated Consequently, income must compensate for the cost and effort required to practice this occupation or profession

2.1.2 The link between education and farm productivity

To point out the benefits of education in terms of earnings, several aspects of schooling benefit will be mentioned In that, education helps farmers adapt to technical change, improving knowledge which lead to raise the farm household income In rural areas, education has an important influence on farm income Thus,

we should focus on relationship between farm production and education as higher productivity household will bring higher farm income To examine the effect of education on household income, we can examine the effect of education on farm mcome

Several theories has researched and proved that farmer education is more important for modem agricultural practices than for traditional ones As by Weir (1999:4)

"Increasing literacy and numeric may help farmers to acquire and understand information and to calculate appropriate input quantities in a modernizing or rapidly changing environment" Mellor (1976) showed that farmer education in rural areas should be a key ingredient of any strategy and policy to improve agricultural productivity, which will bring to raise total household income through higher farm income Especially, the education level of household head play great role in efficiency As Russian and Byerlee (1995), education brings about both monetary and non-monetary benefits to individuals and to society as a whole We know that education provides skills and knowledge that can help to increase labor productivity and income Moreover, high education level will help farmers to apply and to use technology efficiently, allocate resources more proficiently and increase farm productivity These effects can be illustrated by the following figure 2.1

Figure 2.1: Effects of education on farm production

Those farmers endowed with less knowledge on technical and allocative efficiency started at point B If they have knowledge about technical the efficient point will move from B to T, and afterwards shift to A which represents the allocative efficiency, and further move to the higher production frontier, at point I as a result

of applying new technology and attain higher output and profit

From the above theory, it is seen that the education level affects strongly to technical efficiency and productivity The raises in technical efficiency and productivity help to increase the farm output and income of farmers In summary, higher education will lead to higher farm income

2.1.3 The relationship between education and income

In literature, the positive relationship between education level and income are well documented This relation is presented in the below diagram (Knight and Sabot, 1990) The figure 2.2 shows the relationship between earnings, years of education, personal ability, and human capital

Figure 2.2: Effects of Years of Schooling on Earnings

Source: Knight and Sabot (1990)

Human capital acquired in school

Years of education

Ability

The diagram shows six links between elements in which the link B is the most important for representing the influence of years of education on earnings; and this link causes directly effect to earnings Years of education also have other two direct effect on earnings through link F and link A, where F represents the human capital acquired in school The different value of human capital leads to the results of different earnings Thus, years of education have actually positive effects on earnings The effect of personal ability on earnings can be directed by link C, or/and undirected by link E where personal ability correlated with years of education Link

D shows the effect of A on human capital through cognitive skill In sum, we can conclude that education can effect to income direct in wage sector and indirect through technical efficiency to raise productivity as well as the relationship between income and formal education is positive

2.1.4 The theory of human capital

This theory presents the effect of human capital on earning, employment and other economic variables which can be extended to explain the effects of other kinds of investment in human being especially schooling and education

The treatment of education as a form of investment that could increase the productive capacity of manpower was first considered by Smith (1776), a Classical economist, in his great book "The Wealth of Nations" However, it was since 1960s and due to the significant contributions of Schultz (1961), Becker (1962) and Mincer (1974) that the concept of human capital and the human capital theory have been formally analyzed and developed

Education plays an important role in improving the quality of human resource (Gillis et a!, 1996) It helps people to get better job opportunities, improve health and reduce fertility

Knight and Sabot (1987) argue that persons who have a high number of schooling years will get more cognitive skills than the others This cognitive is a crucial element in engaging the labor market with a hope of better-paid wages

Evans ( 1991) states that educated persons can be successful in both their business and job finding than the others who has less or non education This means those households who obtain higher education will both succeed in self-employment activities or in wage and salary activities

According to Schultz (1993) well-educated people are easier to get better jobs than ill-educated ones An educated person commonly has a good background of knowledge, when learn something; he/she can easily understand and obtain issue quicker than the non-educated person can

In order to find out clearly about rate of return to education based on the analysis of investment in human capital written by Becker ( 1993) and Gillis et a! ( 1996) which have general method to measuring the cost, the benefit of the education and the rate

of return to schooling According to Gillis eta! (1996:263), the net present value of lifetime incremental benefits of university education is measured as:

of a university graduate over the earnings of a secondary graduate at year t (E1 also refers to the incremental earnings a university graduate obtains during his/her learning time at university); m is the number of years of the working life of a secondary graduate plus the learning time at university In this particular case, m is

47 (m = 65- 18); r is the discount rate; and tis indices

It is here assumed that the individuals choose the educational level that maximizes his utility And, both secondary and university graduates enter the labor market immediately after the graduation The discount rate is constant over the whole his/her working life The individual knows in advance the age-earnings profiles associated with different levels of education

The net present value of the costs of university education is defined as

The private rate of return to university education is, thus, the discount rate that equates the discounted present value of lifetime incremental earnings of a university graduate and the discounted present value of costs of university education so as the net present value of the investment equals zero Therefore, the equation to estimate the rate of return to schooling is

Where r is the discount rate, which also is the internal rate of return to the investment in university education The estimated rate of return is now ready to be compared with the rates of return of other forms of investments the individual might make If it is higher, it is worth for him or her making the investment in university education

The benefit of an educational investment is measured as the average additional earnings received by (for example) the graduates of secondary school, over and above the graduates of primary school The cost of the investment comprises direct and indirect costs The direct costs for the individual include all expenditures related

to school attendance, and for society, the full resource costs of providing the educational service, including any subsidized costs not borne by the individual or the individual's family The indirect costs are the average earnings foregone as a result of the investment

This method, while straightforward and requiring fewer 'as if assumptions than other, more elegant methods used to estimate rates of return to educational investments, is data demanding One must have sufficient numbers of observations

in all age-education level cells to be able to construct well-behaved age-earnings profiles (that is, profiles that are non-crossing and concave to the horizontal axis) The private rates of return to other levels of education such as secondary and primary education can be calculated in the same way However, calculating the private rate of return to primary education is a different from calculating the private rates of return to other levels of education We know that children of primary education are mainly of ages from 6 to 12 As most of these children are not qualified to participate in the labor market, their opportunity costs of learning are zero In other words, they do not forego earnings for all their school time However, from the fact that many children of 11 or 12 years old helped in agricultural works

in developing countries, two or three years of foregone earnings have often been taken into account in measuring the private rate of return to primary education (Psacharopoulos, 1995:4)

The estimation of the social rate of return to schooling uses resource costs and benefits to society as a whole The social rate of return to schooling can be used to set investment priorities for future educational investments

2.1.4.1 Measuring the costs of education

Economic analysis of investment in education tries to measure the total cost including opportunity cost rather than the simply monetary expenditures on schooling Regarding private rate of return to education investment, from the point

of view of individual students or families, opportunity costs of pupils or students need taking into account One of the most important resources devoted to education

is the time of student The wages and salaries that students must forgo in order to enroll in education often represent a large part of private cost to education Another major part of the private cost that is often regarded as direct cost includes tuition fees and expenditure on book in general

2.1.4.2 Measuring the benefits of education

Education brings about both monetary and non-monetary benefits to individuals and

to society as a whole We know that education provides skills and knowledge that can help to increase labor productivity and income This is monetary benefit of education According to Haveman and Wolfe (1984), private non-monetary benefits

of education can include: i) Better health for learners themselves and their family The World Bank has showed that "child mortality declines and nutritional status rises with increased parental education, contributing greatly to children's welfare and development" (World Bank, 1980) ii) Better household management Knowledge, ideas and skills obtained through education allow individuals to make choices concerning consumption, fertility and family size more efficiently iii) Higher productivity in knowledge production According to Haveman and Wolfe

' (1984:382), there is evidence that "schooling increases the productivity in the production of additional human capital" iv) Education brings us more enjoyments

of life as music, art

Education yields direct and indirect benefits to both individual and society The most apparent direct benefit is that educated workers receive higher income than those who are less educated Thus, we focus on the direct benefit of education for individual is higher lifetime earnings and for society it is the higher productivity of educated workers and additional contribution to national income over their entire working lives

2.1.4.3 The internal rate of return to schooling

As in the case of other forms of investment, the investment in education will be made only when it is estimated to be profitable The profitability of educational investments can be assessed by the use of the internal rate of return to education If this rate of return is higher than rates of return of alternative forms of investments, the investment in education is considered as profitable

According to McConnell and Brue (1995:88), the internal rate of return to the investment in education can be defined "the rate of discount that equates the present values of future costs and benefits of education so that the net present value is zero"

a The private rate of return to schooling

In order to see how the private rate of return to schooling is estimated, we take an example of 18 years old with a secondary graduate, who is considering whether to continue his learning into university education or to enter the labor market

According to Psacharopoulos (1995:3), the monetary benefits associated with a certain level of education are the incremental lifetime earnings (after-tax) individuals of that level gets over and above the earnings of the control group The control group refers to individuals of the previous, adjacent level of education In the case of university education, the control group comprises of individuals of secondary education

From data in age-earnings profile, it is possible to calculate rate of return to each year of schooling as well as rate of return to each educational level The private return to an investment in a given level of education in such a case can be estimated

by finding the rate of discount (r) that equalizes the stream of discounted benefits to

the stream of costs at a given point in time For example, in the case of university education, the formula is:

Figure 2.3: Stylized age-earnings profile of secondary and university graduates

Annual

earnings

s

u Noted:

(1 ): Explicit cost of

- - - I S university education

(2): Implicit cost of university education

(3): Incremental

18 J - - - - 1 - - - /

u (1) _ , 22 65 Age

Source: Psachropoulos (1995) and Patrinos el al (2004)

From figure 2.3, the curve SS shows the age-earnings profile of a secondary graduate The curve UU shows the age-earnings profile of a university graduate, who has taken 4 years of university education after the completion of secondary school and then enters the labor market at the age of 22 Area (1), which shows negative benefits, represents the explicit (or direct) costs of university education Area (2) represents the implicit (or indirect) costs of university education The sum

of area ( 1) and (2) reflects the total costs of the investment in university education Area (3) indicates the benefits of taking university education, which are incremental earnings of a university graduate over and above the earnings of a secondary school for all their working life Here, the working life is assumed to last until the age of

65

b The social rate of return to schooling

The estimation of the social rate of return to schooling also uses the equation similar

to that in calculating the private rate of return However, the estimation now uses social costs and gross or before-tax incremental earnings As income tax is paid to the government, it is not included in benefits of education to individuals being taxed But income tax is social benefit of education because it forms a part of government budgets, which, then, may be used to finance public goods and services that are beneficial to society as a whole Thus, the difference between the social and the private rate of return to education depends on the degree of subsidization and income tax of the government

A number of studies on rural Vietnam showed that households in high-income class were said to have higher levels of knowledge, which covers a mixture of education level, access to information, skill and technical know-how (World Bank, 1999) For low-income households, children were either not going to school or were dropping out of school at low levels of attainment This can be seen clearly that the relationship between education and income level in rural areas in the following figure 2.4

Figure 2.4: Relationship between Education and Income Level

Lack of

education

Source: World Bank (1999)

Low education level

Low productivity and output

Low income

Lack of information, technology

The above figure shows that the households, which attain low education level and low capacity to access information and technology, will have low productivity and output The low productivity and output lower income of households The low-income households cannot afford the fee for children go to school or children are drooping out of school at low level This process will continue and might set a

"vicious cycle" for low education level, low-income households in rural areas

2.1.5 Mincerian earning function methods

The "human capital earnings function" (HCEF) is a fundamental tool in research on earnings, wages and incomes in developed and developing countries The tool was first researched and developed by Chiswick and Becker (1966) and extended to include on-the-job training in Mincer (1974) HCEF have used in studied in earnings which find and make educational policy decision based on the estimates of the rate of return from schooling The theory about Mincer earning functions will show following

Mincerian earnings functions

Mincer developed human capital earning function based on Chiswick and Becker (1966) Mincer was very successful in studying the earning function and education

He found that formal schooling is only half of the story in human capital accumulation and skill development The investment in education include before and after schooling Formal schooling sets stage for accumulation of specific skills and learning in concrete work situations via on-the-job training The term "on-the-job training" is interpreted broadly in human capital literature The major term is associated with learning from experience Thus, like schooling, on-the-job training

is a form of investment in human capital that might be expected to affect both employment and earnings

In additional, to accommodate a monotonically declining rate of on-the-job training human capital investment by workers after finishing schooling, Mincer ( 197 4) developed the rationale for the standard quadratic form for the experience variable The argument is that earnings rises rapidly in the first several years of working life

but the rate of growth falls towards mid career and tends to tum negative toward retirement In panel data, wage rate rises throughout the life cycle with the greatest

of increase in the early years The interpretation of these observations is that the increase in earnings with work experience is due to increasing productivity and human capital accumulation over the entire life cycle Mincer illustrated how a quadratic in post-schooling labor market experience, square experience, could describe proportionate changes in wages, net of on-the-job training costs

Measures of employment or labor supply can also be incorporated into the analysis Normally, number of working hours per week or numbers of working weeks per year are fitted into the model in logarithm form as independent variable but compensatory factor (Chiswick, 1997) Its coefficient is thus interpreted as elasticity

of earnings with respect to time units worked Note, however, that labor supply decision (time worked) are not exogenous with respect to wage rate This raises issues of endogenous explanatory variables which are typically ignored

Basic earning function

Private returns to schooling are estimated first using the human capital earnings function (Mincer, 1974):

Where lnYi ts the log ot monthly labor market eammgs, Si is the number of years of schooling of individual i, and EXPi and EXPi2 are years of experience and its square In this semi-log specification the coefficient on S W) is interpreted as the average private rate of return to one additional year of schooling, regardless of the level of education Expected the sign of coefficient y1 is positive and negative signs

of coefficient y2•

Extended earnings functions

The earnings function method is used to estimate hours worked per week are added

as a compensatory factor (lnHi) and average private returns to different levels of schooling by converting the continuous years of schooling variable (S) into a series

r(PRIM) = ~/SPRIM

r(voq = (~3- ~I)/(Svoc- SPRIM)

r(sEC) = (~z - ~~)/(SsEc - SPRIM) r(UNIV) = (~4 - ~z)/(SUNIV - SsEd

[2.7]

Where SPRIM=6, SsEc=7, Svoc=6 and SUNiv=4, the average number of years of schooling for the four levels of education However, it is incorrect to assume that primary school graduates forego earnings for the entire duration of their studies Therefore, only one year of foregone earnings are assumed for primary school graduates, for example, SPRIM= 1

2.1.6 Other methods

Besides with methods above, there was another method to study returns to education

as short-cut method and reverse cost-benefit method

Short-cut method bases on assumption of flat curve in age-earnings profile as figure 2.3 This method is very easy to apply but it is inferior relative to any other methods described above (Psacharopoulos, 1995) Rate of return earning can be shown as:

Where W refers to the mean earnmgs of an individual with the subscripted educational level, and 5 is the length of the university cycle Therefore, the rate of return to education is estimated simply as the difference in mean earnings between two successive levels dividing by the length of studying years in the higher level

In the absence of good outcome data (as wages may not well reflect productivity differences), we used reverse cost-benefit method is another method based in the

short-cut rate of return The question is framed as follow: given the cost of the investment, what level of annual benefits would produce a given rate of return on investment (assuming 10 percent to be the social opportunity cost of capital, for instance) The reserve cost-benefit method can be shown as:

Where Ds1s_1 is the required productivity differential between a person who has graduated from school level S and one who has graduated from level S-1; ts is the number of years required to complete level S; Cs is the per student direct resource cost of each year of the investment; and W s-1 is the earnings foregone during each year of the investment This method provides guidance on investment in education

in the absence of reliable earnings information Furthermore, this method is rough and only able to precipitate further analysis on how to reduce the costs or increase the benefits, rather than to estimate approximate rate of return (Psacharopoulos, 1995)

2.2 Reviews of Empirical Studies

This section is to review several empirical studies on the effects of education on earnings in some developing countries and some transitional economies in general and in Vietnam in particular Preference has been given to reporting returns based

on Mincer as earnings function method in most of studies on rate of return to education More concerns are given to specific topics of interest such as rate of return to education with earning, gender effect, economics sector effect, regional, numbers of schooling years of household head effect although review efforts have been distributed unevenly This studied are worth in the researches in Ben Tre provmce

2.2.1 Empirical studies on impact of schooling and education levels to earnings

Since the advent of the human capital theory, empirical researches concerning the relationship between education and earnings have been carried out for many countries in the world These studies, for developed as well as developing countries, have shown that more educated people receive more earnings and produce more

output than less educated people do m a wide range of activities (Schultz, 1988:544)

Nguyen and Cheng (1999) conducted the research in China After the Ordinary Least Squares Estimation (OLS) regression, they found that the coefficient of variable numbers of schooling years of household head is significant at 0.1 percent level and has expected positive sign

Vijverberg and Van der Gaag (1995) in their study of wage determinants in Cote d'Ivoire applied standard Mincerian framework and confirmed that schooling is an important determinant of wage differentials Estimation results showed returns to an additional year of schooling were very high 20.0 percent

Farchamps and Quisumbing (1998) evaluated the effect of human capital on of household income in rural Pakistan in 1998 The result indicate that education level help to raise household income, one additional year of schooling of adult males leads to increase household income by 4.5 percent, very strong effect

King (1990), revealed some findings supporting the above patterns In the study of labor force participation and earnings of women in Peru, indicated that the average rate of return to primary education is about 12 percent per year which is significantly larger than the rate of return estimated for secondary and post-secondary education The estimated rates of return to post-secondary education without receiving a diploma are negative for both non-university tertiary and university education Gaining a diploma greatly increases the return to post-secondary education; the rate of return to earning a diploma is 19 percent in all Peru estimates

2.2.2 Empirical studies on the effect of gender disparity on rate of return to education

Tam (2002) conducted the research in Vietnam, with VLSS 1992-1993 and

1997-98, to find that the education have strongly determines gender has a positive effect

on earnings (1.2%) between male and female

Most of empirical studies show that the returns to female education are higher than those for males (Psacharopoulos, 1994) Estimating by Mincerian earning function, Psacharopoulos found that in general, return to year of schooling for men is lower than that for women, about 11.1 and 12.4 percent correspondingly This is similar to the pattern found in China in the mid 1980s when earnings functions were estimated separately for males and females (Jaminson and Vander Gaag, 1987)

Behrman et al, 1985, using Mincerian earnings function method for men and women

in Nicaragua, showed that men had lower return to schooling than women: 10 percent versus 13 percent in urban areas and 4 percent versus 5 percent in rural areas

2.2.3 Empirical studies on regional disparity on rates of return to education Quoc (2009) conducted the research education and earning in Mekong Delta Research findings showed that the regions have strong influence on earnings in surveys of 2004 (11.18%) and in 2006 (10.68%) Similarly, Huy (2001) has also applied the Mincerian earning function method to estimate the rate of return to education using data of wage labor extracting from Vietnam in 1998 is 8.5%

Psacharopoulos (1994) has also calculated the average returns for those regions and income groups from empirical studies of the rates of return to education for 62 countries (many of them are present in the above-mentioned 78 countries too) using Mincerian earnings function method He shows that in Asia region and the low-income group, where Vietnam is located, the average rates of returns to education are 9.6% and 11.2% respectively

Estimating earnings functions for women in Nicaragua, Behrman et al (1985) found relatively high rates of return to schooling 13 and 12 percent for women in the central metropolis of Nicaragua and other urban areas, in contrast with 5 percent for the rural samples

2.2.4 Empirical studies on economic sector of employment disparity

Mincerian approach is based in the assumption that wage are set equal to the marginal productivity of the wage earners In non-competitive market forces may

influence the wage structure in many ways Minimum wage legislation drives a wedge between marginal productivity and the wage rate

World Bank (1996) and Moock et al (1998) studied m the relation between education and earnings in Vietnam By fitting earnings function separately to different sub-groups, these studies found disparities in rate of return to education between male and female, between workers in public and private sector, between regions and between inexperienced and experienced wage earners

Vijverberg and Van der Gaag (1995) have focus on public-private sector differentials using data from recent survey in Cote d'Ivoire, where 41 percent of all wage earners work in the public sector Results of years of elementary schooling show no effect in both sectors Junior school years are rewarded in the public (19 percent rate of return) but not in the private sector, university training is valuable in both sectors but technical training pay only in the private sector with 10 percent rate

of return

Stelcner et al (1987:5), the results showed that secondary education yields higher return in the public sector: 9.4 percent per year as compared to 3.8 percent in private sector Post-secondary education yields 2 percent more per year in the private sector

2.2.5 Empirical studies on impact of education on earnings in Vietnam

Quoc (2009) conducted the research education and earning in Mekong Delta The findings showed that the education have strongly effects on earnings of workers in both surveys in 2004 (3.46%) and in 2006 (4.13%)

Tam (2002) conducted the research in Vietnam Findings of the research found that the education have strongly determines rate of return to earnings in both surveys in 1992-1993 at 2.8% and in 1997-1998 at 4.0%; gender has a positive effect on earnings (1.2%)

Quyen et al (2001) concentrated exclusively on earnings components of income such as wages, non-farm income and agriculture income They also found that more years of schooling contribute to higher wages and the influence of diploma on

earnings is significant However, the interesting feature of the wage curve is that they are not linear, extra years of primary education do not appear to help very much but university education boost wages substantially

The relation between education and earnings in Vietnam, were those of the World Bank (1996) and Moock et al (1998) The results estimated by Mincerian method with VLSS (1992-93), the estimates rates of returns for Vietnam are still low compared with the returns to education estimated for other developing countries Return to one additional year of schooling is 5 percent in average while private return to primary education reaches 13 percent per year, to university education is

11 percent per year Secondary and vocational education earns lower returns of 4 to

5 percent per year

In conclusion, the above evidences from other areas show that the relationship between effects of education on earnings is positive Empirical studies to analyze impact of education level on earnings were conducted in many places with different objectives, goals, and findings Therefore, how these factors impact to earnings of workers in Ben Tre province is interested to be examined

2.3 Chapter Remarks

This chapter presents reviews in the literature about determinants of education on earnings which related to the issues addressed by this thesis With the review of the literature above, the Mincerian methods can be applied to assess the impact of education on earnings This method can provide several desirable features: comparison across places as from countries to countries, and less data-demanding method This feature is valuable in the case of developing countries such as Vietnam Though findings of previous researches are not same, several significant features can be summarizing as table 2.1 and drawn from these empirical studies as follow:

Firstly, there are disparities in returns to workers of different economic sectors, different regions and gender Secondly, employment can help to solve the problems

of rural poverty, unemployment, underemployment, unstable agricultural to increase

income Then, education improvement of individuals is one possible way Thirdly, education, in the view of the human capital theory, is an investment that brings about monetary and non-monetary benefits Education provides laborers with knowledge and skills that can enhance their productivity, and thus, income Further, education can also lead to stronger health, better household management, and more enjoyments of life As other forms of investment, the internal rate of return to education is often used to assess the efficiency of the investment in education The rate of return to the investment in education can be calculated by the full discounting method and the method of Mincerian earnings function Finally, education and training are valued the most important investment in human capital since they improve and increase a person's income after netting out the cost of schooling Therefore, with high educated people is higher earning above average Human capital analysis assumes that schooling raises earnings and productivity mainly by providing knowledge, skills and a way of analyzing problems (Becker, 1993) This theory finds out the methods to access the effects of education on earning for developing countries, countries in transition The nature of approach is

an estimation of rates of return to education

Regarding to the case of Vietnam, few systematic studies assessing the relationship between education and earnings are found in many previous studies by applying the human capital theory and extended Mincerian earning model The empirical model applied to investigate the impact of education on earnings in Ben Tre is presented in the next chapter

Table 2.1: Summarize the main results of the past studies

World Bank ( 1996) K::ross sectional IY ear of schooling has positive association with earnings

~ietnam: Education ~ata VLSS 92-93; !Males experience resulted in lower returns to schooling than do females

Sector Financing and ~he majority of workers with secondary and upper level were assigned to jobs in the public Study And, Moock et japplication of sector

al (1998).Education logit model Workers in the public sector get higher private rates of return to schooling than do private sector

ransition economy 1Primary and university education is a good investment as high private return to schooling

he case of Vietnam Working hour has positive association with earnings between the gender and sectors

Orazem et al (1997) Data set in 1995; Average returns to years of education rose dramatically following transition relative to earnings

!Value ofhuman and application pf the least educated group

capital in transition to logit models ~elative wage gains for educated women are similar but slightly smaller

lmarket in Slovenia !Returns to the most experienced rise relative to those with the least experience, for men and

!women

Quoc, Tran Nam Cross sectional Year of schooling has positive association with earnings

(2009) ~ata VHLSS 2004 !Females experience and earnings resulted in higher returns to schooling than do males

Education on Earnings jand 2006,and The majority of workers with secondary and upper level were assigned to jobs in the public The case in Mekong japplication of sector

Delta, Vietnam logit model Workers in the public sector get higher private rates of return to schooling than do private sector

CHAPTER3

METHODOLOGY AND ANALYTICAL FRAMEWORK

This chapter presents the methodology and analytical framework applied in the research The first part presents the model specification and definition of variables The second part presentd the data sets The last part is to estimate the coefficients

3.1 Model specification

In order to analyze the relationship between education and earnings, in literature there are at least two relevant methods: the full discounting method and the Mincerian earnings function method The paper is uses the Mincerian earnings function method of the research Firstly, this method has been widely used to estimate the rates of return to the education investment in many countries including Vietnam Secondly, data for the empirical analysis is draw from the VHLSS 2006, the Mincerian earnings model, which requires less data, is more appropriate Finally, parameters of the Mincerian earnings model can be estimated by OLS regression

From the basic model of Mincer (1974), the earnings of workers (Y) are specified as

a function of schooling or highest educational level obtained, and experience:

[3.1] where Y is the dependent variable measured by income per capita; schooling, level expressed by the schooling years, or categorical variables showing the highest education level; experience represented by years of working

The empirical model is modified and specified as follows:

ln Y = ~o + ~~Schooling + ~2Experience + ~3Experience 2

~ 5 Cutivated land size+ A 1Region + A 2Gender + A 3Sector + ui [3.2]

In this semi-log specification the coefficients on schoolings variable is interpreted as the average private rate of return to one additional year of schooling Besides

schooling and experience variables, other independent variables are included These are dummy variables represented for urban versus rural area; gender; sector represented for private or public sector; working hours per month; and cultivated land size The coefficient of schooling variable is assumed a flat age-earnings regardless of different levels of education

This problem can be solved by converting the continuous years of schooling variable (S) into a series of dummy variables denoting the highest education level a person obtained correspondingly to estimate rate of return to education (ROR) The extended earnings function is specified as follow:

lnY = ~0 + LYiEducation leveli + ~1Experience + ~2Experience2

+ ~3 Lnworking hour+ ~ 4 Cutivated land size+ A 1Region + A 2Gender + A 3Sector + ui [3.3] Parameters of education levels, namely, Yt y2, and y3,, then are used to calculate the rates of return to education via the following formula:

1 SLevel i - SLevel (i-1)

[3.4]

Where r i are parameters of education estimated in model two SLeveii are schooling years spent to completed education level i SLeveli equal to 5, 9, 12, and 16 years for primary, secondary, high school, and university or higher, respective!/

The parameters are estimated by OLS method The F-test and R-square are used for testing the goodness of fit of the model Model Breusch-Pagan I Cook-Weisberg test

is applied to test for heteroscedasticity problem2•

3.2 Definition and measurement of variables

1

It is incorrect to assume that primary school graduates foregone earnings for the entire duration of their studies so only one year of foregone earnings is assumed for primary graduates, so Sp should equal to 1 when return to primary is estimated (Quoc, 2009)

2 www.nd.edu/~rwilliam/stats2/125.pdf, assessed on 17 January 2010 Breusch-Pagan I Cook-Weisberg tests the null hypothesis that the error variances are all equal versus the alternative that the error variances are a