State and non state wage differentials in VN

THE ECONOMICS UNIVERSITY HOCHIMINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM- THE NETHERLANDS PROJECT ON DEVELOPMENT ECONOMICS STATE AND NON-STATE WAGE DIFFERENTIALS IN VIETNA.M Supervisor NGUYEN VAN NGAI Student TRAN DUONG CHIEN TRANG Hochiminh City, December 2003 ACKNOWLEDGEMENT I thank Dutch government for financial supports and Institute of Social Science (ISS), The Hague for academic program during two-years period of my study I am really grateful to my supervisor, Dr Nguyen Van Ngai for his advices and comments through all stages of thesis making I also owe Dr Youdi Schipper and Mr Michael Palmer a special thank for all their help during the time of thesis proposal I thank Mr Jeff Collins for English correction and Mr Truong Dang Thuy and Mr Phung Thanh Binh for their comments I also want to show my gratitude to all lecturers for providing me academic knowledge background and to the project staff, Ms Dinh Thi Anh Nguyet and Ms Dang Kim Chi, for their help during the courses ii ACKNOWLEDGEMENT I thank Dutch government for financial supports and Institute of Social Science (ISS), The Hague for academic program during two-years period of my study I am really grateful to my supervisor, Dr Nguyen Van Ngai for his advices and comments through all stages of thesis making I also owe Dr Youdi Schipper and Mr Michael Palmer a special thank for all their help during the time of thesis proposal I thank Mr Jeff Collins for English correction and Mr Truong Dang Thuy and Mr Phung Thanh Binh for their comments I also want to show my gratitude to all lecturers for providing me academic knowledge background and to the project staff, Ms Dinh Thi Anh Nguyet and Ms Dang Kim Chi, for their help during the courses 11 ABBREVIATIONS ·CWE Corrected Wage Equation DPE Domestic Private Enterprises FIE Foreign Investment Enterprises GDP Gross Domestic Product GSO General Statistical Office IMR Inverse Mill's ratio ISD Index of Sector Discrimination LSE Likelihood Selection Equation MLA Maximum Likelihood Approaches MLE Maximum Likelihood Estimation NPV Net Present Value OLS Original Least Squared regression SOE State-owned Enterprises UCE Urban Collective Enterprises VLSS Vietnam Living Standards Survey WB World Bank 111 ABSTRACT There is no evidence on the extent of wage differentials between state and non-state sector in Vietnam The main objection of this research is to examine the wage differentials between SOE versus DPE and SOE versus FIE, and to find source of the differentials For those purpose, corrected Mincer earnings equations of sectors, which are the Mincer earnings equations corrected selection bias by Heckman Two-Step method, must be compared by using the Oaxaca-Blinder Decomposition method The data sample of VLSS 97-98 is applied for estimation process The results indicated that there is sector discrimination in wage against state sector, and the difference in wage settings the source of the sector discrimination Besides, there was the hesitation of nonstate participation and gender discrimination in both sectors IV CONTENTS CER TIFICATI0 N Cio····················v····· i A CKNOWLE.DGEMENT ABBREJ!'l"ATIONS ABSTRA CT CONTENTS ii oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooqooooooooooooooooooooooooo oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo;,ooooooooooooooooooooollooooooetoooooooooooooooooo oooe OOOitO • • • • • • • • • • • • • • • • • • It • • • • • • • • 000 0000 • • 0000 • • • • • • • • 0 • • • • • • • • • • • • • • • ooo iii iv ••••••••••••••• 0 ••• oooooooooooooooooooooooooooooooooooooooo•oooooooooooooooooooooooooooooooooooooooooooooooooooooooctooooooooooooo••••••••••• LIST OF TABLES ••.••.••.• ••.•.• • •• • • .• V vi eo •••••••••••••••••••••••••••••••••••••••••••••••••••• LIST OF FIGURES ···················eo·················o·······························································.,····· vi CHAPTER 1:INTRODUCTION• • • 1.1 Problem statement and the objective of the research ~ 1.2 Research question 1.3 Methodology and dataset 1.4 Structure of the thesis o ••••••••••• e •••••••••••••••••••• e CHAPTER 2: LITERATURE & EMPIRICAL REVIEW • 2.1 Definitions 2.2 Theoretical Review 2.3 Empirical studies 18 2.4 Vietnam labor market overview: 21 CHAPTER 3: MODEL SPECIFICATION AND DATABASE 24 3.1 Corrected Wages Model (CWE) 24 3.2 Likelihood Selection Model (LSE): 27 3.3 Calculation ofthe inverse Mill's ratio (IMR): 31 - - · 3.4 Database 31 CHAPTER 4: STATE AND NON-STATE WAGE DIFFERENTIALS IN WETNAM 34 4.1 Descriptive Analysis 34 4.2 Econometric Analysis 57 4.3 Comparison with other researches 79 CHAPTER 5: CONCLUSIONS AND POLICY IMPLICATION 82 Conclusion 82 5.2 Policy implication ~ 84 5.3 Further researches 85 APPENDIX • , • .• .• • .• BIBLIOGRA.PHY•• .•• o •••••••• 94 v LIST OF TABLES Table 2.1: Identification of the earnings and sector choice equations 20 Table 3.1 Specification of the corrected wages model 27 Table 3.2 Specification of the Likelihood Selection Model (LSE) 30 Table 4.1 Types of data and levels ofmeasurement 35 Table 4.2: Descriptive statistics 36 Table 4.2: Descriptive statistics (continue) 37 Table 4.3 Statistic Analysis of Wage 39 Table 4.4 Statistic Analysis ofAge 40 Table 4.5 Statistic Analysis of Experience 41 Table 4.6 Education and wage rate : 42 Table ANO VA results for wage and education relationship 44 Table 4.8 Experience and Wage Rate 44 Table 4.9 ANOVA results for wage and experience relationship 46 Table 4.1 Gender and wage rate Table 4.11 t-testfor wage difference between gender group 47 Table 4.12 Location and Wage Rate 48 Table 4.13 t-testfor wage difference between residua/location groups 49 Table 4.14 Regions and Wage Rate Table 4.15 ANO VA results for wage and regions relationship 51 Table 4.16 Age and Wage Rate 51 Table 4.17 ANOVA results for wage and age relationship 52 Table 4.18.a Pearson correlation coefficients among variables for SOE 54 Table 4.18 b Pearson correlation coefficients among variables for DPE 55 Table 4.18.c Pearson correlation coefficient!/among variables for FIE 56 Table 4.19.a: Heckman model for the logarithm of hourly wage ofSOE, DPE, and FIE in 1998 57 Table 4.19.b: Heckman mode/for the logarithm of hourly wage ofSOE, DPE, and FIE in 1998 (cont) 58 Table 4.20 Wald test offunctional specification 59 T~ble 4.20.1 The significance and sign of difference in size of the coefficients 59 Table 4.21: The likelihood ratio test for the likelihood selection models 61 Table 4.22: Expected Log Hourly Wages by Sector of Employment, Vietnam 1997-98 67 vi Table 4.23: Decomposition ofstate and non-state wage differentials in Vietnam 1997-98 73 Table 4.23: Decomposition ofstate and non-state wage differentials Vietnam 1997-98 (cant) 74 Table 6.1 Pooling Regression 93 vii LIST OF FIGURES Figure 2.1 Employment choice Figure 4.1 Education and Wage rate 44 Figure 4.2 Years ofExperience and Log wage rate 46 Figure 4.3 Gender and Wage rate 48 Figure 4.4 Wage rate and Location groups 49 Figure 4.5 Wage differentials between regions 51 Figure 4.6 The relationship between wage and age 53 Figure Effects of education attainments on (log) hourly wages 69 Figure 4.8 Gender wage differentials among sectors 71 Figure 4.9 Effects of seniority on (log) hourly wages 71 Figure 4.1 Effects of location to expected wages : 72 Figure 4.11 Effects of regions to expected wages 73 viii CHAPTER l:INTRODUCTION 1.1 Problem statement and the objective of the research Since 1986, Vietnam has adopted the doi moi (renovation) policy to transform from the centrally planned economy to a socialist oriented market economy The reform involved expanding the private sector and opening up the economy These changes have contributed impressive results to economic growth During the period 1993-1997, GDP was increased at a rate of approximately 9% per year, of which the share of the nonstate sector in GDP was about 60 per cent (Belser 2000 and GSO 2000) Matters exist where "over-sized" state-owned enterprises (SOE) have become a significant burden to the government budget SOE showed a decreasing trend contribution to the growth of GDP from 11.4 percent to 9.7 percent in 1996 and 1997 respectively but wages and expenditure increased at the rate of 6.2 percent and 6.9 percent At the same time the number of SOE wage employment increased from 15.48 percent to 16.45 percent in the period of 1992-93 to 1997-98 (World Bank 1999 and Bales 2000) There are a difference between the state sector and non-state sector in Vietnam in wage structure and employment practices A non-market process sets wages for SOE A base salary for each education 1evel i s s et and incremented every three years according to seniority There are differentials according to the position occupied Performance seems irrelevant iii promotions SOE employees have lifetime labor contracts and almost 100 percent are union members; however, they are not allowed collective bargaining or the rjght to strike Conversely in the non-state sector, which comprises domestic private enterprises (DPE) and foreign investment enterprises (FIE), wages are set according to the position occupied and collective bargaining Performance is important in the CHAPTER 5: CONCLUSIONS AND POLICY IMPLICATION This study aims to investigate wage differentials between state sector versus non-state sector in Vietnam using data from VLSS 1997-98 The SOE represents the state sector in comparison to the non-state sector comprising DPE and FIE The study used a four way probit model (likelihood selection equation-LSE) with not-wage employment as the base choice to calculate Inverse Mill's Ratio- IMR (called selection tenn), which will correct the selection bias of sectoral Mincer earnings equation The CoiTected Mincer's earnings model - CWE of SOE, DPE, and FIE are separately estimated later to explain the wage determinants of those sectors in Vietnam in 1997-98 The Oaxaca-Blinder Decomposition method decomposes the wage differentials between SOE versus DPE and FIE, and the sector discrimination (or total structure differentials) will indicate which sector worker earn the premium Besides, the estimates of the LSE also indicate factors affecting the probability of sector participation The conclusion section of this chapter will present main findings from the analytical results in Chapter Base on the conclusion, the research should suggest some policies and further researches Further research suggestion is the last section of the Chapter 5.1 Conclusion This research indicates that there was state and non-state wage differentials in favor of the non-state sector when the unobserved factors and sample selection were controlled The premium wage of DPE and FIE were explained by its wage structure and employment practices when the total structure differentials between SOE versus OPE and FIE all are negative Although the rewards to human capital, individual characteristics, and residual location in favor of SOE worker but the premium rent from being the DPE and FIE are large enough to get higher than the premium rent from being the SOE and total of those rewards' gap between SOE versus DPE and FIE 82 Results of the research also confirm the statement there are difference in wage structure and employment practices between state and non-state sector The wage structure of SOE base on human capital and seniority, when return to those factors are high and larger in S OE than those in DPE and FIE While the wage structure of the non-state sector base on market and negotiation when the effect of the premium rent remarkably determinate to wage The state sector employed and promoted the worker who has high education and seniority, while non-state worker have high level of experience Especially, this research indicated the hesitation of non-state participation Although the sector discrimination in wage was in favor of the non-state sector, the expected wages of SOE workers according to DPE or FIE wage settings could be higher or lower than their present wages Moreover, the situation of labor market pointed out that the ,) productivity of SOE workers is higher than those of DPE and FIE workers It means that , ~ there are difference in requirement of employment between SOE, DPE, and FIE Gender discrimination was found in all ownership categories in this research In which the level of the discrimination was higher than for DPE and FIE than for SOE One of main findings of this research is to indicate characteristics of workers who chose to participate sectors People who chose the state sector get high human capital achievement, advantage individual characteristics, and live in urban of all regions While the non-state sector worker is the person who gets middle or low human capital achievement, is young man, and 1ives in urban orr ural in s orne regions such as Red River Delta, South Central Coast, South East, and Mekong Delta Level of human capital, individual characteristics, and the situation of residual location and of available individual and household income determined the choice whether or not pa1iicipate a sector to work Participant is the person who achieve a specific level of human capital, have advantageous individual characteristics such as male or adult, live in urban of all regions, and receive a little bit of benefits from himself or his family properties 83 5.2 Policy implication The problem statement section in Chapter introduced some problems included· the oversized SOE, the constraints of laid-off schemes, and SOE wage budget in refer to the burden of government The result of this research indicated the premium ,.,·age 111 ra, or of non-state sector, SOE worker with high productivity, and the hesitation of non-state participation It means that the oversized SOE and the constraints of laid-off schemes all have emanated from the hesitation of non-state participation, while the burden of state ·wage budget emanates from the wages structure and employment practices Thus, the policy should aim to wages structure and employment practices in the state sector, and the hesitation of the non-state sector participation The SOE employment practices should be corrected in following to "right employees, right position" Because the SOE wages structure base on the level of human capital, it should classify the requirement of the level of human capital for each specific job and position The recruitments and personnel arrangement should base on the classified requirement of job and position Thus the wages will be paid for right worker with right job requirement Besides, the state wages etting should be corrected in base of job requirement rather than in base of worker characteristics The problem statement in Chapter brought up a problem that poor performance of SOE whereas its increasing trend of number of wage employment of SOE had been happening during the period of 1992-93 to 1997-98 The research indicated higher probability of sector participation and higher human capital and individual characteristics in favor of SOE It means that SOE meet the oversized problem and overpay for job requirement Thus the SOE wage setting should base on job requirement to reduce the overpaid problem in relate to the behavior At that time, SOE worker can perceive higher wage in favor of non-state sector so that there is the mobility from state to non-state sector The Labor Code should be strengthened, abided and popularized to reduce the hesitation oft he non-state sector participation The strengthening points are regulations of nonwages compensation The Labor Code 1995 stipulated the mandatory contributions to the social insurance fund and health insurance fund in all enterprises that employ more than 10 workers However, one hundred present of SOE workers have been taken apart into the social insurance fund so the distinction could be the hesitation of the non-state sector participation In 2000, only millions per 40 millions worker were covered by social insurance, and out of these million, only 380,000 are private sector It seems the Labor Code is not abided in the non-state sector in order to worker hesitated to select a non-state employment Labor Code should be popularized to all state and non-state sector worker for increasing the legal knowledge of labor equality among sectors The re-training schemes to laid-off SOE worker must be implemented because there is difference in employment requirement between SOE, DPE, and FIE sector The schemes should be diversified types of training such as opening, on-the job, and supplementary The program of the scheme should be advised by employers in DPE and FIE sector Besides, there is a budget to support those laid-of SOE workers · The gender discrimination problem should be reduced, especially in FIE and OPE Vietnam government and Vietnam women union should incorporate together to improve education achievement and career training for women These works w i 11 enhance the productivity of woman and proportion of worker participation These results will increase the wage paid for woman and gender discrimination can reduce 5.3 Further researches This research investigated the state and non-state sector employment choice and wage differentials between these sectors using data sample of VLSS 97-98 After the data 85 sample of VLSS 2000-2001 is published, this research should be re-implemented to examine the change of the employment choice and the wage differentials' situation This research examined the state and non-state wage differentials, g1ven the nonpecuniary benefits The non-pecuniary aspect of the state sector could provide the attractive employment opportunities that are difficult to come by the non-state sector The further investigation should aim to qualify the state sector's non-pecuniary 86 APPENDIX A Table A.l ANOVA analysis for wage and education relationship in SOE Number of obs = 573 R-squared = 0.0383 Adj R-squared = O.U2lJ8 Root MSE = 700898 Source Partial SS Df MS F Prob > F Model 11.0824988 2.21649976 4.51 0.0005 4.51 0.0005 Edu 11.0824988 2.21649976 Residual 278.543092 567 491257657 Total 289.625591 572 506338445 ANOVA analysis for wage and education relationship in DPE Number of obs = 1546 R-squared = 0.0476 Root MSE = 0.7347 Adj R-squared = 0.0445 Source Partial SS Df MS F Prob > F Model 41.5348938 8.30697876 15.39 0.0000 Edu 41.5348938 8.30697876 15.39 0.0000 Residual 831.267547 1540 0.539784121 Total 872.80244 1545 0.564920673 ANOVA analysis for education and wages relationship in FIE Number of obs = 248 R-squared = 0.1393 Root MSE = 0.649135 Adj R-squared = 0.1216 Df MS F Prob > ·-F Source Partial SS Model 16.5100429 3.30200858 7.84 0.0000 Edu 16.5100429 3.30200858 7.84 0.0000 Residual 101.973173 242 0.42137675 Total 118.483216 247 0.479689135 -·· X7 Table A.2 ANOVA analysis for wage and experience relationship in SOE Number of obs = 573 R-squared = 0.03 79 Root MSE = 0.70477 Adj R-squared = 0.0190 Source Partial SS Df MS F Prob > F Model "10.9761500 11 0.997827775 2.01 0.0256 Exp Level 10.9761500 11 0.997827775 2.01 0.0256 561 0.496701399 Residual 278.649485 Total 289.625591 572 0.506333445 ANOVA analysis for wage -experience relationship in DPE Number ofobs = · 1546 R_.squared = 0.0087 ·Root MSE = 0.751006 Adj R-squared = 0.0016 Source Partial SS Df MS F Prob > F 11 0.691983203 1.23 0.2633 Model 7.61181524 Exp Level 7.61181524 11 0.691983203 1.23 0.2633 Residual 865.190625 1534 0.564009534 1545 0.564920673 Total 872.80244 ANOVA analysis for wage -experience relationship in FIE R-squared = 0.064 Number of obs = 248 = 0.685248 Adj R-squared = 0.0211 Root MSE Source Partial SS Df MS F Prob > F Model 7.66587138 11 0.696897398 1.48 0.1381 Exp.Level 7.66587138 11 0.696897398 1.48 0.1381 Residual 110.817345 236 0.469565021 Total 118.483216 247 0.479689135 Table A.3 The ANOVA analysis for wage -region relationship in SOE Number of obs = 572 R-squared == 0.0978 Root MSE = 0.679982 Adj R-squared = 0.0882 Df ·Ms F Prob > F Source Partial SS o.oooo Model 28.3093237 4.71822061 10.20 Region 28.3093237 4.71822061 10.20 0.0000 Residual 261.24185 565 0.4623 74956 Total 289.551174 571 0.507094876 The ANOVA analysis for wage -region relationship in DPE Number ofobs = 1546 R-squared = 0.0543 = 0.732364 Adj R-squared = 0.0506 Root MSE Df MS F Prob > F Source Partial SS 0.0000 Model 47.3497432 7.89162387 14.71 Region · 47.3497432 7.89162387 14.71 0.0000 Residual 825.452697 1539 0.536356528 Total 872.80244 1545 0.564920673 The ANOVA analysis for wage -region relationship in FIE Number of obs = 248 R-squared == 0.114 Adj R-squared = 0.0964 = 0.658366 Root MSE Source Partial SS Df MS F Prob > F 0.0000 Model 13.5893426 2.71786852 6.27 Region 13.5893426 2.71786852 6.27 0.0000 Residual 104.893874 242 0.433445759 Total 118.483216 247 0.479689135 89 Table A.4 The ANOV A analysis for wage -age relationship in SOE Number of obs = 573 R-squared = 0.0309 = 0.702949 Adj R-squared = 0.0241 Root MSE Source Partial SS Df MS F Prob > F Model 8.95527665 2.23881916 4.56 0.0013 Ag_ F Model 5.52537746 1.38134437 2.45 0.0441 Age Group· 5.52537746 1.38134437 2.45 0.0441 Residual 867.277063 1541 0.562801469 Total 872.80244 1545 0.564920673 The ANOVA analysis for wage -age relationship in FIE Number of obs = 248 R-squared = 0.0064 Root MSE = 0.696019 Adj R-squared = -0.0099 Df MS F Prob > F Source Partial SS Model 0.763614379 0.190903595 0.39 0.8128 Age Group 0.763614379 0.190903595 0.39 0.8128 Residual 117.719602 243 0.484442806 Total 118.483216 247 0.479689135 APPENDIXB The pool test or dummy variable test is the method to test whether or not the difference in intercept and size of the various coefficients between two equations, which are similar model, are statistically significant Other words, the test strongly indicate that the regressions are different (Gujarati 1995) Content of the pool test is presented using Corrected Wage Equation (CWE) of SOE and DPE (see equation inC hapter 3) example Firstly, all observations of SOE and DPE are pooled together to estimate the following regression log(WJ= flo+ flodDi + fl 1AGEi + fl 1d(AGEiDJ+ fl SEX + fl EDU, + fl 3d(EDUiD;)+ fl EXP; + fl d(EXP;DJ+ /35 (EXP;) + fJ 5JEXP,D,Y + fl6LOCi + 'Ifl7JREGJi +nA-i +nd(A-iD;)+Ui (6.1) j=l where Wh and AGEj, SEXi, EDUh EXPi, EXP h LOCh REGji, A.i are respectively dependant and explanatory variables which were introduced in Corrected Wage Model section of Chapter 3, whereas Di =I for observations in SOE and zero for observations in DPE Assuming E(Ui)=O, the Model 6.1 implies - DPE model: E(log(WJD1 = 0) =flo+ fl 1AGEi + fl SEX + fl EDU + fl X~E + (3 (£)~ Y + fl6LOCj +I fl7jREGji + JZ'Ai (6.2) j=l SOEmodel 91 +(/34 +f34d )EX~ +(f3s + f3sd XEXP;Y + fJ6LOCi + LfJ? REGJt + (n + Trd )Ji.l (6.3) j=J In the Model (6.1), ~oct is the differential intercept, and ~ ct, ~ d, ~ d, ~sd, nd are differential slope coefficients of age, education attainments, experience, squared expenence, and selection term respectively indicating by how much the slope coefficient of SOE differs from the slope coefficient of DPE The other explanatory variables included gender (SEX), resident location (LOC), regional location (REGj) are really qualitative variables so that the multiplicative form of the dummy variable (Di) and those variables could indicate the interaction effects rather than the differential in size of those variables between SOE versus DPE (Gujarati 1995) After the Model (6.1) is estimated by OLS regression, t-test or z-test should be appl1cd to coefficients presenting differential intercept and differential slope coefficients of age, education attainments, experience, squared experience, and selection te1111 as mentioned above We will conclude that the differences in size of the intercept and those coefficients between SOE versus DPE are significant if the differential intercept, and the differential slope coefficients differs from zero, and are statistically significant as well Because the thesis investigates the wage differentials between SOE versus D PE, and SOE versus FIE so that the pool test should be also applied to S OE- FIE cas e The results of OLS regressions are shown in Table 92 Table 6.1 Pooling Regression Variable Constant D (SOE=l, DPE/ FIE= 0) Male (M=l, F=O) Age(years) Age (years) x D Education attainment Education attainment x D Experience (years) Experience (years) x D Experience Square (years) Experience Square (years) x D Urban location (U=1, R=O) Regions North Uplands Red River Delta North Central Coast South Central Coast South East Mekong Delta Selection term Selection term x D Number of Obs Prob>F SOE versus DPE 7.061 * -0.328* 0.251 * 0.018 -0.001 0.948 0.024" 0.005 -0.013 -0.00( 0.001 0.103" SOE versus FIE 7.772* -0.959* 0.234" -0.013 0.030 0.1 07 0.026 -0.001 -0.006 0.001 -0.001 0.176 -0.139 -0.059 -0.057 -0.001 0.449* 0.239* 0.117* 0.105* 2127 0.000 0.120 0.284 0.336 0.276 0.793* 0.637 -0.103 0.243 825 0.000 Source: Author's calculation Note: *:Indicate statistical insignificant at 10 percent/eve/ Y3 BIBLIOGRAPHY Assaad, R (1997) The Effects of Public Sector Hiring and Compensation Policies on the Egyptian Labor Market', World Bank Economic Review, Vol.11 (1): 85-118 Bales, S (2000) Vietnam's Labor Situation and Trends- Analysis based on 1992-93 and 1997-98 Vietnam Living Standards Data, Vietnam: Vietnam Development Report 2000 Bedi, S (1998) 'Sector Choice, Multiple Job Holding and Wage Differentials: Evidence from Poland', The Journal of Development Studies, vo1.35, no I: 162-179 Belser, P (2000) Vietnam: on the road to labor-intensive growth?, Vietnam: Vietnam Development Report 2000 Belser, P and Rama, M (2001) 'State Ownership and Labor Redundancy: Estimates Based on Enterprise- 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