Socioeconomic determinants of fertility in HCM City

THE UNIVERSITY OF ECONOMICS HOCHIMINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS THE VIETNAM-NETHERLANDS PROJECT FOR M.A PROGRAMME IN DEVELOPMENT ECONOMICS SOCIOECONOMIC DETERMINANTS OF FERTILITY IN HOCHIMINH CITY BY NGUYEN LUONG HONG HANH IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS IN ECONOMICS OF DEVELOPMENT SUPERVISOR: HOANG THI CHINH, Ph.D HOCHIMINH CITY, 2003 CERTIFICATION "I certify that the substance of this dissertation has not already been submitted for any degree and is not being currently submitted for any other degree I certify that to the best of my knowledge any help received in preparing this dissertation, and all sources used, have been acknowledged in this dissertation" i ACKNOWLEDGEMENTS First of all, I would like to express an enormous appreciation to my academic supervisor Dr Hoang Thi Chinh for her invaluable guidance along the way ofmakin·g this thesis Great gratitude is also expressed to Dr Karel Jansen and Dr Youdi Schipper for their academic advices on the thesis proposal Dr Nguyen Thi Thieng, who gave me huge support in terms of courage, suggestions and comments from the first stages of doing this research to its completion, is as well truly appreciated I am very grateful to all project teachers and staff for their useful lectures, material and services Many thanks are owned to my classmates, especially Ms Luong Thi Chung Thuy and Mr Luong Vinh Quoc Duy, who lent me a great helping hand in collecting data for this research Last but not least, I thank my dear family for their spiritual encouragement and support during the time of doing this work ii TABLE OF CONTENTS CERTIFICATION i ACKNOWLEDGEMENTS ii TABLE OF CONTENTS iii LIST OF TABLES ~ v LIST OF FIGURES vi ABBREVIATIONS vii ABSTRACT viii Chapter 1: INTRODUCTION 1.1 PROBLEM STATEMENT 1.2 OBJECTIVE OF THE THESIS 1.3 RESEARCH QUESTIONS 1.4 RESEARCH METHODOLOGY 1.5 ORGANIZATION OF THE THESIS Chapter II: LITERATURE REVIEW AND EMPIRICAL STUDIES II.l FERTILITY AND ITS MEASURES II.2 MODELS OF FERTILITY DETERMINANTS , II.2.1 The household demand model II.2.2 Synthesis model 12 1!.2.3 Bongaarts model 15 II.2.4 Reasons for choosing the research model 16 II.3 EMPIRICAL STUDIES ON FERTILITY DETERMINANTS 17 II.4 CHAPTER OUTLINE 22 Chapter III: FERTILITY IN VIETNAM AND HCMC 23 III.1 HCMC GENERAL CONDITIONS 23 III.2 POPULATION 26 III.2.1 Vietnam 26 11!.2.2 HCMC 27 iii III.2.3 Policies on population and fertility 28 11!.3 FEATURES OF FERTILITY IN VIETNAM AND HCMC 30 11!.3.1 Trends 30 111.3.2 Socioeconomic differentials 32 11!.3 CHAPTER OUTLINE 37 Chapter IV: DETERMINANTS OF FERTILITY IN HCMC 38 IV.1 ANALYTICAL FRAMEWORK AND RESEARCH METHODS 38 IV.1.1 Analytical Framework 38 IV 1.2 Research Methods 41 IV.2 DETERMINANTS OF FERTILITY IN HCMC ~ 44 IV.2.1 Descriptive Statistics 44 IV.2.2 Regression Analysis 52 IV.3 CHAPTER OUTLINE 57 Chapter V: CONCLUSION AND RECOMMENDATIONS 59 V.1 CONCLUSION 59 V.2 RECOMMENDATIONS 60 V.3 FURTHER RESEARCH 61 APPENDIX A - QUESTIONAIRE 62 APPENDIX B 64 APPENDIX C ~ 65 BIBLIOGRAPHY 66 iv LIST OF TABLES Table III.l: Education Levels HCMC, 1989-1999 25 Table III.2: Levels of education of population aged over five years HCMC, 19791999 25 Table III.3: TFRs HCMC, 1989-1999 31 Table !11.4: ASFRs and TFRs by urban and rural areas Vietnam, 1989-1999 33 Table 111.5: ASFRs and TFRs by urban and rural areas HCMC, 1999 33 Table iV.l: Calculation for sample size 43 Table IV.2: Description ofvariables 45 Table IV.3: Distribution ofCEB 46 Table IV.4: Relationship between fertility and completed years of schooling 50 Table IV.5: Relationship between fertility and household income 51 Table IV.6: Regression results for CEB 53 v LIST OF FIGURES Figure III.l: Trends ofTFRs Vietnam, 1959-1999 30 Figure III.2: Natural Increase Rates(%) HCMC, 1975-1999 31 Figure III.3: Fertility differentials by education attainment Vietnam, 1999 34 Figure III.4: Fertility differentials by occupation category Vietnam, 1999 35 Figure III.5: Fertility differentials between rural and urban by quintile 36 Figure IV.l: Fertility changes between rural and urban by age group 48 Figure IV.2 Fertility changes between rural and urban by women's schooling 49 Figure IV.3: Relationship between fertility and completed years of schooling 50 Figure IV.4: Relationship between fertility and household income 51 vi ABBREVIATIONS ASFR Age-Specific Fertility Rate CBR Crude Birth Rate CEB Children Ever Born GFR General Fertility Rate GSO General Statistics Office HCMC HoChiMinh City HSCPH HCMC Steering Committee for Population and Housing Census 01/4/1999 HSO HoChiMinh City Statistics Office NCPF National Committee for Population and Family Planning OLS Ordinary Least Squares TFR Total Fertility Rate VNDHS Vietnam Demographic and Health Survey VLSS Vietnam Living Standard Survey vii ABSTRACT This thesis examines the effect of female schooling and household income on fertility in HoChiMinh City using data collected from the personal survey in 2003 The first method of descriptive statistics presents the correlations between fertility and female schooling, household income and location by summarized data and graphs The second method of regression analysis estimates a reduced form equation in which the number of children ever born is regressed on the mother's age and completed years of schooling, household income and area variables The equation is estimated using ordinary least squares (OLS) The study reveals some findings as follows: schooling reduces fertility, while income raises it Urban residence is negatively associated with fertility Parts of population who still have high fertility rates are of low levels of education or are living in rural districts From these findings, some recommendations are suggested for enhancing population and family planning programs in order to reach the objective of fertility reduction viii Chapter I: INTRODUCTION 1.1 PROBLEM STATEMENT Population is one of the biggest concerns to development economists and policy makers because of its extensive impact on the economic development (Ray, 1998:295) Population growth is strongly determined by fertility level (Tran, 1999:106) The world history has experienced fluctuation in population growth and fertility level, such as an unprecedented and unanticipated 'baby boom' followed by an almost equally startling 'baby bust' And population controlling policies have also been changing from time to time, different from one country to another, from incentives to childbearing in the developed countries facing low fertility in the Great Depression to measures of lowering the fertility rate in the less-developed countries in the post-World War II era (Eatwell et al, 1987 :302) Studying fertility behavior will provide us insights into how population is changing around us Moreover, a better understanding of fertility level and pattern will significantly assist the process of policy making Policies influencing fertility rate could in turn have an effect on population growth On the other hand, according to Nguyen (200 1), mastering of fertility level and pattern will provide more accurate projections For example, to estimate budget on primary education, the analysts need to figure out the number of children going to primary school, which could be accessed through fertility studies Projection of labor force is likewise worked out (Nguyen, 2001:1 ) In the case of Vietnam, a developing country, explosive population growth and high fertility rate attribute to a wide range of social, economic, and ecological problems (NCPF, 1999:3); and the current population growth is not in line with the development high education attainment indicates high opportunity cost of women spending on child bearing and rearing and the demand for children decreases On the supply side, women's education can have an effect on lifetime fertility by delaying age at marriage, or age of first birth Additionally, educated women have better knowledge to maintain their children's health, raise child survival and increase childspacing Another explanation cited in Bouvier L F et al (1999) is that education provides women with alternatives to childbearing as a means of achieving personal satisfaction and social recognition, or it increases their exposure to outside ideas All of these make a substantially inverse effect of education on fertility * Household income: The INCOME variable is significant at the percent level, but unexpectedly it is of a positive sign, or household income raises fertility In comparison, the income impact was found negative by Nguyen and Ainsworth However the size of income effect in this ~ thesis is relatively small By increasing the household income one million units, Vietnam ~ Dong, more, CEB rises 3.14% The theory suggests that as a normal goods, demand for children increases with higher income, but this weak effect could be offset by price effect or quantity-quality tradeoff In this case, however, the strong negative effect is not observed High income is positively linked to fertility It means that there is no quantityquality tradeoff or price effect or they are not strong enough to outweigh the positive effect of high income The increase in income may might lead to easier child bearing and rearing, better nutrition and thereby higher fecundity of a wife, or to shorter breastfeeding as baby food substitutes become available and affordable On the other hand? as we have been seen, the distance in urban and rural income in the working sample is not much 56 large, rural households can earn much money but most of this does not come from wages or women labor Almost rural women not come to work, so their opportunity costs of child care are still lower than urban women's * Urban residence: The AREA of the household has significantly negative effect on the number of children That is not different from Ainsworth's findings and also Nguyen's Fertility differentials by urban-rural residence are substantial Women living in urban districts give fewer births during their lifetime than women in rural These differentials may be due to the following reasons: firstly, access to heath care facilities in rural areas is limited, meaning that availability of contraceptives to rural people is not as broad as it is to metropolitans; secondly, urban areas provide more employment opportunity; both of these reasons raise opportunity cost of children and then reduce demand for them Moreover, in a rural setting, children are supposed to offer hands to help their parents make a living, while children in urban areas require more investment such as food, school fee, scare housing or transportation to school These reasons make children more expensive to urban households than rural ones IV.3 CHAPTER OUTLINE The analytical framework of the thesis is based on the household demand model of fertility A reduced-form equation is estimated using OLS method Data serving for this research was from personal survey via interviewing 141 ever-married women aged 15-49 Relationships between the number of children ever born and completed years of schooling and household income are explored via descriptive statistics and regression 57 analysis The study reveals some important findings First, education has a negative effect on fertility as expected while income is unexpectedly related to fertility with a positive effect The average number of children increases by age of women, and those who living in urban areas have fewer children than those who in rural areas From these findings, some recommendations will be suggested in the next chapter 58 Chapter V: CONCLUSION AND RECOMMENDATIONS V.l CONCLUSION According to Strategy of Population and Family Planning for the period 2001-2010, population task is an important part of the national strategy of development, one of key elements to enhance quality of life of each citizen, each household and the whole society, decisively contributing to implement industrialization and modernization One of the most important factors deciding the population movement is fertility rate Therefore, the key objective of the Strategy is fertility reduction HCMC is a big city of the country, it is also the most populous city Although having low fertility rate of only 1.4 per child, the population size of the city is still large and there still exist parts of population where the fertility rates are quite high The research examines the main socioeconomic determinants of fertility in HCMC in order to find out such high-fertility areas With data from personal survey, and method of descriptive statistics and regression analysis, the author has figured out some findings as follows: Female schooling is associated with lower fertility The higher level of education a woman receives, the fewer children ever born she has Unexpectedly, income raises fertility, although the variable is significant at percent level Variables of age and urban residence were controlled for schooling and income in the regression model The average number of children ever born increases by age of women People who live in the rural areas have a tendency of having more children than who live in the urban districts 59 V.2 RECOMMENDATIONS The effective implementation of Strategy of Population and Family Planning to the year 2000 resulted in rewardable achievements The Strategy in the case of period 2001-2010 was issued to overcome existing shortcomings in order to reach the planned objectives One of the key objectives of the Strategy is fertility reduction In order to complete the tasks, following recommendations are proposed: The high priority should be given to concentrate to reducing fertility in the alertly highfertility rate areas These areas could be population of low education or rural setting From the research, education has a strong effect on the number of children a woman has, therefore, enhancing the level of education of women and continuing invest in education of women is a must for the objective of fertility reduction Relating to this task, there are some suggestions as follows: There still exists a part of population who not receive any schooling, in which women account more The authorities should implement the program of mass education, at least at the primary level, and then continue to upgrade the higher level Alongside with schooling education, forms of propagandization would appreciably influence reproductive behavior of low educated people One of the outcomes of this study is that there was no quantity-quality tradeoff influencing fertility behavior Parents still accept a large family in stead of fewer children with high quality Therefore, family planning programs should focus to raise people awareness of the one or two children norm, advocating the small size family with few children of higher "quality" 60 The difference in fertility rate between rural and urban areas proves that, apart from inherent negative effects to society and environment, urbanization is a good trend to bring down the fertility rate In other words, improving the living conditions especially in the rural districts, industrializing the economy, reducing the distance between urban and rural areas should be considered as sub-targets on the route of stabilizing population of Vietnam V.3 FURTHER RESEARCH This thesis explores socioeconomic determinants of fertility, among these factors, women's education is found the main variable for reducing fertility However, because of constrains of time and resources, several aspects of the matter were not elaborated, initiating further researches Firstly, among limitations of household demand model, the assumption of the 'family' utility should be eliminated In reality, husband and wife not always have the same opinion on reproductive topic A bargaining model should be applied to combine both preferences of father and mother for the demand for children Secondly, the number of observations collected just satisfies an appropriate sample size to analyze fertility determinants for entire sample It is not many enough to observe variables for subsamples of urban or rural areas, schooling specification or age cohorts The impacts of the influencing factors would be much clearer with these specific analyses Finally, son preference is one of important social variables affecting reproductive behavior, especially for the case of an Asian society like Vietnam Examining this factor could suggest more effective policy implications 61 APPENDIX A - QUESTIONAIRE This questionnaire is used to interview women who satisfy the following requirements: - Living in HCMC - Ever-married - Aged from 15 to 49 Respondent: I Tel: Address: Ethnicity: I Religion: Date of interview: Interviewer: 1a How many members are there in your family? : 1b Among them, how many have earnings? 1c Among them, how many adults (over eighteen)? What is your marital status? Married Widowed Divorced Separated Other 0 0 How many children you have ? How many sons/ daughers ? How old they are ? List in oder of age T How many completed years of schooling you have? What is your occupation? 62 How much is your average monthly income? (Fill the blank or check a box) Less than 500,000 VND 500,000 VND- 1,000,000 VND 1,000,001 VND- 2,000,000 VND 2,000,001 VND- 3,000,000 VND 3,000,001 VND- 4,000,000 VND Greater than 4,000,000 VND 0 0 0 How many completed years of schooling does your husband have? ~ What is your husband's occupation? How much is your husban's average monthly income? (Fill the blank or check a box) Less than 500,000 VND 500,000 VND- 1,000,000 VND 1,000,001 VND- 2,000,000 VND 2,000,001 VND- 3,000,000 VND 3,000,001 VND- 4,000,000 VND Greater than 4,000,000 VND 0 0 0 10 Apart from mentioned incomes, does your household have any other incomes? How much? 11 How much is your household's average monthly expenditure? 12 Does your household have electricity? 13 Does your household have a television set? ***** 63 APPENDIXB reg CEB AGE SCHOOLING INCOME AREA Source I ss df MS -+ -Model I Residual I 59.4350931 67.5010771 136 Number of obs F( 4, 136} Prob > F R-squared Adj R-squared Root MSE 14.8587733 496331449 -+ -Total I CEB I 126.93617 Coef 140 90668693 Std Err t 141 29.94 0.0000 0.4682 4526 70451 [95% Conf Interval) P>ltl -+ -AGE SCHOOLING INCOME AREA cons I I I I I 0698024 -.0496063 7.16e-08 -.4137705 -.1385604 0092778 0164185 3.11e-08 1558775 411818 7.52 -3.02 2.30 -2.65 -0.34 0.000 0.003 0.023 0.009 0.737 0514549 -.0820748 1.01e-08 -.7220278 -.9529555 ovtest Ramsey RESET test using powers of the fitted values of CEB Ho: model has no omitted variables F(3, 133} 1.84 Prob > F = 0.1436 corr, coef AGE SCHOOL-G INCOME AREA cons -+ AGE SCHOOLING INCOME AREA cons I I I I I 0000 0.1375 -0.1065 0320 -0.9061 0000 -0.1954 -0 5714 -0.3552 0000 0.0600 -0.1027 0000 -0.0509 1.0000 vif Variable VIF 1/VIF -+ -SCHOOLING AREA INCOME AGE 1.59 1.52 1.05 1.04 0.628037 0.659086 0.952610 0.957656 -+ -Mean VIF 1.30 predict u (option xb assumed; fitted values} sktest u Skewness/Kurtosis tests for Normality Variable I Pr(Skewness} Pr(Kurtosis} adj chi2(2} joint -Prob>chi2 ~ + - u I 0.453 0.043 4.73 0.0940 hettest Cook-Weisberg test for heteroskedasticity using fitted values of CEB Ho: Constant variance chi2(1} 25.46 Prob > chi2 0.0000 64 0881498 -.0171377 1.33e-07 -.1055132 6758346 APPENDIXC reg LNCEB AGE SCHOOLING INCOME AREA Source I ss df MS -+ -Model I Residual I 14.9457973 14.7464738 136 Number of obs 136) F( 4' Prob > F R-squared Adj R-squared Root MSE 73644932 108429954 -+ -Total I LNCEB I 29.6922711 Coef 140 21208765 Std Err t 141 34.46 0.0000 0.5034 0.4887 32929 [95% Conf Interval) P>ltl -+ -AGE SCHOOLING INCOME AREA cons 0369954 -.0169488 3.14e-08 -.2494971 -.6043014 0043364 007674 1.45e-08 0728572 1924837 8.53 -2.21 2.16 -3.42 -3.14 0.000 0.029 0.032 0.001 0.002 0284198 -.0321246 2.7le-09 -.3935766 -.9849497 045571 -.0017729 6.0le-08 -.1054176 -.2236531 ovtest Ramsey RESET test using powers of the fitted values of LNCEB Ho: model has no omitted variables F(3, 133) 0.40 Prob > F = 0.7562 corr, coef AGE SCHOOL-G INCOME AREA cons -+ AGE SCHOOLING INCOME AREA cons 1.0000 0.1375 -0.1065 0.0320 -0.9061 1.0000 -0.1954 -0.5714 -0.3552 1.0000 0.0600 -0.1027 1.0000 -0.0509 1.0000 vif Variable VIF 1/VIF -+ -SCHOOLING AREA INCOME AGE 1.59 1.52 1.05 1.04 0.628037 0.659086 0.952610 0.957656 -+ -Mean VIF 1.30 predict u (option xb assumed; fitted values) sktest u Skewness/Kurtosis tests for Normality Variable I Pr(Skewness) Pr(Kurtosis) adj chi2(2) joint -Prob>chi2 -+ u 0.518 0.018 5.80 0.0550 hettest Cook-Weisberg test for heteroskedasticity using fitted values of LNCEB Ho: Constant variance chi2(1) 0.34 Prob > chi2 0.5583 65 BIBLIOGRAPHY Ainsworth, M (1989) 'Socio-economic Determinants of Fertility in· Cote d'Ivoire' LSMS Working Paper No 53 Washington D.C.: The World Bank Bardhan P and C Udry (1999) Development Microeconomics Oxford: Oxford University Press Benefo K D and T P Schultz (1994), 'Determinants of Fertility and Child Mortality in Cote d'Ivoire and Ghana' LSMS Working Paper No 103 Washington D.C.: The World Bank Bouvier L F and J T Bertrand (1999) World Population - 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"proximate determinants" of fertility That is, the basis determinants influence fertility only indirectly, through their influence on the proximate determinants, or proximate determinants are... model in the tradition of Becker described in Ainsworth (1989) There are some reasons for this choosing Firstly, with the purpose of analyzing socioeconomic determinants of fertility in HCMC,