(Luận văn) is gender pay gap low in plants with more female managers evidence from small and medium entreprises of vietnam 2007

Tran Thi Hieu Master’s Thesis VNP20-2015 UNIVERSITY OF ECONOMICS, HO CHI MINH CITY t to VIET NAM – NETHERLANDS PROJECT FOR M.A PROGRAM IN ng DEVELOPMENT ECONOMICS hi ep w n lo ad ju y th yi pl ua al n IS GENDER PAY GAP LOW IN PLANTS WITH MORE n va ll fu FEMALE MANAGERS? EVIDENCE FROM SMALL AND m oi MEDIUM ENTREPRISES OF VIETNAM 2007 nh at o0o - z z ht vb k jm A thesis submitted in partial fulfillment of the requirements for the degree of om Tran Thi Hieu l.c By gm MASTER OF ARTS IN DEVELOPMENT ECONOMICS an Lu ey t re Nov – 2015 n Dr Pham Dinh Long va Supervisor Tran Thi Hieu Master’s Thesis VNP20-2015 ABSTRACT t to The goal of gender equality in income is not only an important matter ng of human rights but also basic requirement for development of fair and hi efficiency Therefore, study on the state of gender inequality in income has ep the significant implications in moving toward the equality in society and w enhancing the efficiency of economic and social growth Actually, there have n lo been many previous studies related to the issues of gender income ad y th difference, particularly the factors impact on reducing the gender gap in ju earnings Inheriting these previous researches, my dissertation attempts to yi investigate whether the gender gap in earnings is low in the establishments pl ua al with more female managers Using a sample size of 1043 employees and n 2492 enterprises were surveyed in the Small and Medium Enterprises (SME) va n in Vietnam in the year of 2007, matching employer and employee data and ll fu distinguishing occupation the study ends up 345 job–cells In addition, oi m ordinary least squares modeling and ordinary least square with job-cell fixed at nh effects are applied to explore the effect on male – female income difference z of proportion of female manager Various explanatory variables for z characteristics of workers and plants are used as control variables Result vb jm ht reveals that there is a negative relationship between the female share in k managers and gender pay gap, and the education has a significant statistic an Lu Key words: Gender pay gap, matched employee – employer data om l.c gm and strong impact on the wage of the labors n va ey t re Tran Thi Hieu Master’s Thesis VNP20-2015 ACKNOWLEDGEMENTS t to This thesis is completed with not only painful process but also enjoyable ng experience Fortunately, throughout the process I always got a lot of helps and hi ep supports from many people in order to make thesis possible On the same occasion, I would like to express my gratitude to all of them w n Foremost, I would like to give my sincere gratitude and special lo ad appreciation to my academic supervisor Dr Pham Dinh Long, for his patience, ju y th motivation, enthusiasm, and immense knowledge His guidance helped me in yi all the time of research and writing of this thesis pl al Similarly, I sincerely thank to the Scientific Committee and staffs of n va during the last time n ua Vietnam-Netherland Program for their willingness to provide information ll fu Last but not the least, I would like to thank my family and classmate at oi m VNP20 for their backing and helping so that I can complete this thesis at nh z z k jm ht vb om l.c gm an Lu n va ey t re Tran Thi Hieu Master’s Thesis VNP20-2015 TABLE OF CONTENTS t to CHAPTER 1: INTRODUCTION .4 ng hi ep 1.1 Problem statement 1.2 Research objective 1.3 Structure of research w n CHAPTER 2: LITERATURE REVIEW 10 lo ad 2.1 The definitions 10 ju y th 2.1.1 Gender 10 yi 2.1.2 Gender equality 10 pl 2.1.3 Gender gap in earnings 11 al ua 2.2 Cause of gender wage gap and the factors impact on gender wage gap 12 n 2.2.1 Cause of gender wage gap 12 va n 2.2.2 The factors impact on gender wage gap 16 fu ll 2.2.2.1 Non-economic factor 16 m oi 2.2.2.2 Economic factors 16 nh at 2.2.2.2.1 Characteristics of employee 16 z 2.2.2.2.2 Education 17 z ht vb 2.2.2.2.3 Employment 17 jm 2.2.2.2.4 Geographic factor 18 k 2.3 Measurement of gender pay gap 18 gm 2.4 The impact on economic - social development of gender wage gap 19 l.c 2.5 The impact on male – female income difference of female manager 20 om CHAPTER 3: OVERVIEW OF GENDER WAGE GAP IN VIETNAM 25 an Lu 3.1 Overview the status of gender gap in earnings in Vietnam 25 3.2.3 Employment 32 ey 3.2.2 Education 32 t re 3.2.1 The age of employee 31 n va 3.2 The factors impact on male – female income difference 31 Tran Thi Hieu Master’s Thesis VNP20-2015 3.3.4 Geography 32 CHAPTER 4: METHODOLOGY 34 t to 4.1 The data 34 ng 4.2 The variables 35 hi ep 4.2.1 Education 35 w n Seniority 36 4.2.3 Age of employee 36 4.2.4 Size and Industry 36 lo 4.2.2 ad The Econometrics Models and Results 37 y th 4.3 ju CHAPTER 5: CONCLUSION, POLICY IMPLICATIONS AND LIMITATIONS 42 yi pl 5.1 Conclusion 42 ua al 5.2 Policy implications 42 n 5.3 Limitations 43 va n REFERENCES 44 ll fu Bibliography Error! Bookmark not defined oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re Tran Thi Hieu Master’s Thesis VNP20-2015 LIST OF TABLES t to ng Table1: Human development index and Human development index in Southeast Asia Area 25 hi ep Table2: The share of women’s labor force participation 26 w Table 3: The share of female in plants 27 n lo Table 4: Summary statistics 38 ad Table 5: Wages and female shares in managers 38 y th Table 6: Wages regression 39 ju yi pl n ua al LIST OF APPENDICES va n Appendix 1: Correlation of variables 47 fu ll Appendix 2: Statistics variables 47 m oi Appendix 3: OLS wage regression 48 nh at Appendix 4: OLS wage regression with job – cell fixed effect 49 z Appendix 5: Test for heteroskedasticity 49 z ht vb Appendix 6: Test for multicollinearity 50 k jm Appendix 7: The individual categories of ISIC 50 om l.c gm an Lu n va ey t re Tran Thi Hieu Master’s Thesis VNP20-2015 ABREVIATIONS t to ng hi ep ILO International Labor Organization VGCL The General Labor Confederation of Vietnam SMEs Small and medium enterprises The Convention on the Elimination of all forms of Discrimination w Division of Workers’ Compensation n DWC lo CEDAW ad Organization for economic co-operation and development ju OECD y th against women yi Science, Technology, Engineering and Mathematics WB World Bank GDP Gross domestic product HLM Hierarchical linear modeling OLS Ordinary least square EEOC Equal employment opportunity commission HDI Human Development Index GDI Gender Development Index of Vietnam UNDP United Nations Development Programme WEF World Economic Forum GSO The General Statistics Office of Vietnam VHLSS Vietnam Household Living Standards Survey pl STEM n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re Tran Thi Hieu Master’s Thesis VNP20-2015 CHAPTER 1: INTRODUCTION 1.1 Problem statement t to ng Gender pay gap is a global problem Indeed, according to Nguyet and hi ep Binh (2007), male – female income difference is not only one of the root causes of poverty but also major factor that distributes to hinder the development w n process The greater gender gap in earnings are, the more poverty it has to pay lo ad dearly for that as well as more malnutrition status, illness and other hardships ju y th In addition, economic growth will bring more effective for the reduction of yi poverty level in the country which has a higher level of gender equality pl Moreover, inequalities in income between women and men prevent the equal al n ua development and this makes the use of resources in society inefficient n va In fact, the situation of gender inequality in earnings occurred in many ll fu countries, especially in the developing countries It might be said that the cause oi m of this condition primarily rooted traditional perspectives and preconceived nh ideas in the social about the male-supremacy in many countries Thereby, these at lead to the restriction of opportunities for women to access the education and z z training, the choice of professions, an opportunity to improve professional vb ht qualifications The distribution of labor between men and women in different k jm occupations, employment arrangements and job positions in the same business gm line is also obvious differences, which greatly affected on the difference in l.c gender income Furthermore, women also have fewer opportunities to access om to these services as well as other basic resources such as water, transportation improvement of the condition and economic status an Lu and marketing, capital, etc These things certainly impact on their ey continuously increasing while the proportion of women in work force was t re 7th March, 2013, the gap of income between men and women in Vietnam was n va In Vietnam, as reported by the International Labor Organization (ILO) on Tran Thi Hieu Master’s Thesis VNP20-2015 higher than other countries in the world Approximately 72% of women participated in the labor force in Vietnam and this ratio was higher than that in t to most of other countries worldwide Nevertheless, Vietnam was one of the few ng countries where the gender wage gap was increasing in contrast with the trend hi ep in most of other countries in the 2008-2011 period compared with the period 1999-2007 Moreover, according to the 2012-2013 Global Wages Report of the w n ILO, gender income gap of Vietnam increased by 2% in the recent period lo ad Statistical data of the General Department of Statistics in 2011 indicated that y th women's income was lower than men’s income, approximately 13% Also, the ju General Labor Confederation of Vietnam (VGCL) conducted a survey of yi pl employees’ salary in enterprises in 2012 This organization saw that wage of al ua female workers was less, only 70-80% of their male colleagues Besides, Labor n Survey Report published in 2012 stated the average monthly income of women va n was less than men’s in all economic sectors, state, non-state and foreign fu ll investment Even in occupations which primarily recruited focus on women m oi such as health care, social work and sales, women still had a lower salary than nh male fellowship More specifically, the VGCL survey found that women often at z did the normal work whereas male undertook the management positions z ht vb Due to the important of this field, there were thus a lot of researches jm about gender pay gap conducted in the past indicating the determinants of k difference in wage of women and men as well as providing solutions to reduce gm l.c this gap such as Anderson, Tracy, et al (2001), Hultin and Szulkin (2003), om Manning (2006), Blau and Lawrence (2007), Cohen and Huffman (2007), an Lu Becker (2010), Cardoso and Winter-Ebmer (2010), Spencer (2015) In Vietnam, studies about gender gap in earnings there are Liu (2002), Pham and Particularly, in the research of Hultin and Szulkin (2003) namely “Mechanisms ey relationship between female share in managers and gender wage gap t re researchers in order to reduce gender income differences, there was the n va Barry (2007) and so on Interestingly, related to the solutions given by the Tran Thi Hieu Master’s Thesis VNP20-2015 of inequality unequal access to organizational power and the gender wage gap”, the authors used the multilevel models in order to analyze the dataset of t to Swedish which combined the information on a large number of private – sector ng enterprises and all their employees The finding showed that gender gap in hi ep income in plants were wider while there were more male representations among managers and supervisors in these enterprises and low relative wage of w n female worker in plants in which there were no or only a few women in lo ad managerial position Another notable research, Hirsch’s paper (2013) is one of y th these above studies, through the evidences from linked employer – employee ju data for Germany, Hirsch found that gender income difference decreased by 0.5 yi pl log point when increased the female share in first level management by 10% al ua points Therefore, follows the cornerstones of Hirsch’s research and applies for n the case of Vietnam in order to investigate the relationship of female share va n managers and gender pay gap, this study is conducted particularly in small and fu ll medium enterprises (SMEs) in Vietnam in the year of 2007 at nh Research objective oi m 1.2 z The objective of the study is an analysis to find out whether or not the z ht vb women have an important role in the case of reducing the gender income jm difference when they stand in the assembly line of managers in small and k medium plants in Viet Nam gm om gender pay gap low in plants with more female managers? l.c This research is also conducted to answer the main question that is an Lu And for the scope of study, it is undertaken in SMEs in Vietnam in the year of 2007 n va ey t re Tran Thi Hieu 4.3 Master’s Thesis VNP20-2015 The Econometrics Models and Results In order to answer the main question whether or not gender pay gap is t to low in plants with more female among managers, the study will be undertaken ng hi based on the method of Hirsch (2013) in which the augmented Mincer wage ep regressions The baseline specification is a fully interacted model w n Lnwi = β1femalei + β2femshmani + β3femalei×femshmani + x’i (γ + femalei lo × δ) + ui ad y th Lnwi: log daily gross wage of employee i ju femalei: female dummy yi pl femshmani: the female share among managers ua al femalei x femshmani: the interaction of these two n xi: a vector of control variables, xi includes variables capturing the va n individual’s human capital endowment and plant characteristics, such as age, ll fu agesq, education, seniority, lnsize, industry variable oi m In this study, β1 is as the average unexplained gender pay gap in the at nh sample β3 is expected to be positive in order to indicate that the unexplained z gender income difference is lower if the female share in management is higher z Ordinary least squares (OLS) regression is a technique of statistical estimation vb jm ht This technique is commonly used in the linear regression model The aim of the k method is from discrete samples, determine the function which approximately l.c gm represents the distribution of these samples, and after that estimate the value which can not be measured Moreover, the assumptions of this model related om to homoscedastic, linearity and the impact of outliers are not difficult to check an Lu (Craven and Sardar, 2011) Besides, in order to control for segregation effects, – female income difference that address unobserved plant and job and thus 37 ey Summary statistics for all explanatory variables are given in the table as bellows: t re employment segregation The model is estimated by carring out in Stata n va the study adds job-cell fixed effects to arrive at the unexplained within job male Tran Thi Hieu Master’s Thesis VNP20-2015 Table 4: Summary statistics Variables Mean t to ng hi ep Age 32.6869 Agesq 1161.2260 Seniority 4.9333 Education 14.7768 lnwage 3.8153 Lnsize 3.4514 Industry 0.9913 Female 0.6086 Female share in managers 0.5580 (Source: Author’s calculation) w Min 9.6466 712.2256 4.9130 5.2351 0.4708 16 256 0 0.9808 64 4096 30 21 5.4524 1.1590 0.0929 0.4887 0.6931 0 7.0535 1 0.2350 0.1470 n Std Dev Max lo ad ju y th yi pl ua al n Table 5: Wages and female shares in managers n va Women Men ll fu Variables m oi Mean nh Std.dev Mean Std.dev 21.4490 57.1753 27.5101 3.9391 0.5053 0.5342 0.2272 45.9795 Log gross daily wage 3.7358 0.4300 Female share in management 0.5733 0.2392 Observations 454 at Gross daily wage (in 1000 vnd) z z k jm ht vb gm om l.c (Source: Author’s calculation) 454 an Lu The table presents some sample statistics Therein, male workers has female workers 38 ey This indicates that there is discrimination about income between male and t re approximately 11.1958 The raw gender pay gap amounts to 20.33 log points n va the average of daily wage is higher than female worker, the difference is Tran Thi Hieu Master’s Thesis VNP20-2015 Table 6: Wages regression t to Variables ng Coefficient Standard error - 0.2882*** 0.1198 -0.1422 0.1663 0.2076 0.2013 0.0052* 0.0032 -0.0004* 0.0002 -0.0043 0.0053 hi OLS regression ep Female w n lo Female share in managers ad managers ju y th Female x Female share in yi n ua n va ll fu Seniority al Agesq pl Age m 0.0356*** Lnsize 0.0249 Industry 0.0856 0.0045 oi Education nh at 0.0226 z z 0.0892 om l.c Female x Female share in - 0.1767** gm Female k OLS wage regression with job – cell fixed effect jm ht vb 0.3031 Age 0.0060* 0.0032 Agesq -0.0003* 0.0002 n va 0.1330 an Lu 0.0620 managers ey t re 39 Tran Thi Hieu Master’s Thesis VNP20-2015 t to ng hi ep -0.0058 0.0053 Education 0.0331*** 0.0069 Lnsize 0.0343 0.0222 Ioccupation_2 -0.0245 0.0921 -0.0707 0.1105 0.1499* 0.0830 -0.0545 0.0761 345 345 w Seniority n Ioccupation_3 lo ad ju y th Ioccupation_4 yi Ioccupation_5 pl n ua al n va Observations ll fu ***significant at percent, **significant at percent, * significant at 10 percent oi m (Source: Author’s calculation) nh at The table shows the key results of the wage regression for sample z including observations from the plants which are surveyed An average z ht vb unexplained gender gap in earnings is 28.82 log points Although the jm interaction effect of the female dummy and the female share in managers has k insignificant statistic, but the positive sign is the same with expectation Age, gm l.c agesq and education variable have a significant statistics at 10 percentage and om percentage level Particular in education variable, it has a strong effect on the wage of labor, the higher the level of education the labors have, the more wage an Lu they receive When control segregation by adding job – cell fixed effects, both dummy and the proportion of female share managers is insignificant statistic, 40 ey control job-cell effect, the interaction impact on gender pay gap of the female t re and female share in managers are reduced For the case of control or non- n va unexplained gender income difference and the interaction impact of female Tran Thi Hieu Master’s Thesis VNP20-2015 but there is the negative relationship among two variables Furthermore, the results are in the line with earlier findings by Hirsch (2013) and Hultin and t to Szulkin (2003), the gender pay gap is lower in plants with more female ng managers hi ep w n lo ad ju y th yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re 41 Tran Thi Hieu Master’s Thesis VNP20-2015 CHAPTER 5: CONCLUSION, POLICY IMPLICATIONS AND LIMITATIONS 5.1 Conclusion t to ng Follows the empirical studies have scrutinized in which ways gender hi ep differentiated representation in manager effect on gender pay gap, when these studies supposed the gender gap in earnings can be explained in the terms of w n discrimination Therefore, the main assumption in this research is that the lo ad gender pay gap is lower in enterprise with more female manager participation ju y th By using matched employer and employee data for SMEs in the year of 2007 yi and controlling for employment segregation by including job – cell fixed effects, pl the study finds that the impact on male – female income difference of female al ua share manager has insignificant statistic, but it has a negative relationship n between the two Thus, the paper can not conclude that the gender pay gap va n reduces in the plants with more female managers However, the education fu ll variable always has significant statistic, and it implies that the wage of the m oi labors will rise if they have a good education level, especially for women nh at workers In addition, the negative relationship between the number of female z on managers and gender pay gap are consistent with the previous studies in z jm ht vb this field k 5.2 Policy implications gm l.c Discrimination in income of women stems from variety of causes, om possibly due to incorrect views about gender roles in society, traditional ideas an Lu or prejudice these factors may be eliminated through educational activities Hence, the government should implement measures about education enterprise to build the fair competitive environment, create equal 42 ey change the view on the role of gender in society, such as policy to encourage t re economic development towards gender equality goals so that the people n va synchronously and systematically as well as carry out the policies of socio- Tran Thi Hieu Master’s Thesis VNP20-2015 opportunities for both women and men worker In addition, in this study the numbers of women involved in manager position have the impact on reducing t to discrimination in income between men and women, for that reason businesses ng need to adopt policies to encourage women participation in manager as a hi ep measure to reduce the income gap Besides, the results also shows that variable of education has strong statistical significant to the income of workers, so for w n worker particular in female, they need to improve their knowledge and skills lo ad more and more in order to shorten the gap in income compared with male y th ju 5.3 Limitations yi pl The matched data for enterprises and employees which participate in al ua SMEs in sample is small, so it can not fully express the population of small and n medium enterprise of Vietnamese Furthermore, due to the lack of data, only va n for the year of 2007, there is not shown the effect of time variable on gender fu ll pay gap as well as reflected the impact on current time oi m nh Moreover, the literature shows that determinants of wage come from at variety of characteristics of employee and plant (Hirsch, 2013) However, in my z z research, I focus on a few of these variables vb jm ht There is another model can be applied in order to investigate the impact k of gender of manager position on gender pay gap, such as multilevel modeling gm – the appropriate model for handling the nested data But, due to the limitation om l.c of time and data, the study has not used this model Mentioned are four limitations in my study that will provide strong an Lu basics for further research n va ey t re 43 Tran Thi Hieu Master’s Thesis VNP20-2015 REFERENCES Anderson, Tracy, et al "The gender pay gap." 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Annual review of n psychology 33.1 (1982): 1-39 va n Torm, Nina The union wage gap among Vietnamese SMEs Working Paper, fu ll Department of Economics, University of Copenhagen, 2011 oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re 46 Tran Thi Hieu Master’s Thesis VNP20-2015 APPENDIX Appendix 1: Correlation of variables t to ng corr cen_age1 cen_age1sq seniority education lnwage lnsize femshman industry female (obs=345) hi ep cen_age1 cen_ag~q senior~y educat~n w n cen_age1 cen_age1sq seniority education lnwage lnsize femshman industry female lnwage lnsize femshman industry lo ad ju y th 1.0000 0.5814 1.0000 0.4729 0.2316 1.0000 -0.0975 -0.1475 -0.1186 1.0000 -0.0011 -0.1375 -0.0521 0.4259 1.0000 -0.0378 -0.0997 -0.0685 0.2870 0.2056 1.0000 -0.0374 0.0583 -0.1019 -0.2046 -0.1364 -0.4531 1.0000 0.0164 0.0250 0.0242 -0.0398 -0.0087 -0.0323 -0.0908 -0.0741 0.0968 -0.0702 -0.0183 -0.2110 -0.1247 0.0813 female yi pl 1.0000 n ua al 1.0000 0.0528 n va Appendix 2: Statistics variables oi at nh lnwage femshman z wage m gender ll Summary statistics: mean, sd by categories of: gender fu tabstat wage lnwage femshman, by(gender) s(mean sd) z om l.c 50.36048 3.815377 5580147 24.58165 4708226 2350819 gm Total k 45.97952 3.735837 5733195 21.449 4300014 2392863 jm N÷ ht 57.17531 3.939105 5342071 27.5101 5053168 2272161 vb Nam an Lu n va ey t re 47 Tran Thi Hieu Master’s Thesis VNP20-2015 Appendix 3: OLS wage regression reg lnwage female femshman fexfesh cen_age1 cen_age1sq seniority education lnsize industry t to ng Source SS df MS hi ep 18.1938474 2.0215386 58.061992 335 173319379 Total 76.2558393 344 221673952 w Model Residual n Number of obs F( 9, 335) Prob > F R-squared Adj R-squared Root MSE = = = = = = 345 11.66 0.0000 0.2386 0.2181 41632 lo ad t ju [95% Conf Interval] 0.017 0.393 0.303 0.102 0.065 0.419 0.000 0.272 0.726 0.000 -.5238961 -.0525541 -.4692586 1848636 -.1883556 6037084 -.0010513 0115216 -.0008497 0000252 -.014674 006119 0266948 0446148 -.0196098 0694377 -.3948212 566127 2.763036 3.955536 n ua al n ll fu oi m -2.41 -0.86 1.03 1.64 -1.85 -0.81 7.83 1.10 0.35 11.08 P>|t| va 1198081 1662681 2013309 0031958 0002224 0052853 004555 0226346 2442587 3031156 pl -.2882251 -.1421975 2076764 0052352 -.0004123 -.0042775 0356548 0249139 0856529 3.359286 yi female femshman fexfesh cen_age1 cen_age1sq seniority education lnsize industry _cons Coef Std Err y th lnwage at nh z z k jm ht vb om l.c gm an Lu n va ey t re 48 Tran Thi Hieu Master’s Thesis VNP20-2015 Appendix 4: OLS wage regression with job – cell fixed effect xi: reg lnwage female fexfesh cen_age1 cen_age1sq seniority education lnsize i.occupation i.occupation _Ioccupatio_1-5 (_Ioccupatio_1 for occ~n==L§ nghiƯp vơ omitted) t to ng Source SS df MS hi ep 19.5891683 11 1.78083349 56.666671 333 170170183 Total 76.2558393 344 221673952 Model Residual Number of obs F( 11, 333) Prob > F R-squared Adj R-squared Root MSE w n = = = = = = 345 10.47 0.0000 0.2569 0.2323 41252 lo ad yi pl ua al 0.048 0.642 0.062 0.086 0.277 0.000 0.124 0.790 0.523 0.072 0.475 0.000 -.3522148 -.0011971 -.199771 3237855 -.0003036 0124673 -.000815 0000539 -.0162982 0046849 0195043 04673 -.0094361 0780563 -.2058677 1568224 -.2882546 1468149 -.0134174 3132854 -.2043593 0953745 3.010889 3.704583 va [95% Conf Interval] ll fu oi m at nh -1.98 0.47 1.87 -1.72 -1.09 4.79 1.54 -0.27 -0.64 1.81 -0.72 19.04 P>|t| n 0892215 1330774 0032461 0002209 0053335 0069202 0222388 0921884 1105858 0830412 0761862 1763228 t n -.1767059 0620072 0060819 -.0003806 -.0058067 0331172 0343101 -.0245227 -.0707198 149934 -.0544924 3.357736 ju female fexfesh cen_age1 cen_age1sq seniority education lnsize _Ioccupatio_2 _Ioccupatio_3 _Ioccupatio_4 _Ioccupatio_5 _cons Coef Std Err y th lnwage z z ht vb Appendix 5: Test for heteroskedasticity k jm estat hettest gm om l.c Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of lnwage an Lu n va chi2(1) = 2.51 Prob > chi2 = 0.1134 ey t re 49 Tran Thi Hieu Master’s Thesis VNP20-2015 Appendix 6: Test for multicollinearity vif t to VIF 1/VIF fexfesh female femshman cen_age1 cen_age1sq lnsize seniority education industry 9.12 6.81 3.03 1.89 1.59 1.37 1.34 1.13 1.02 0.109703 0.146940 0.329786 0.530105 0.628816 0.732004 0.747229 0.886052 0.976830 ng Variable hi ep w n lo ad ju y th yi 3.03 pl Mean VIF n ua al va n Appendix 7: The individual categories of ISIC ll fu oi m nh Divisions Description A 01–03 Agriculture, forestry and fishing B 05–09 Mining and quarrying C 10–33 Manufacturing D 35 Electricity, gas, steam and air conditioning supply E 36–39 F 41–43 Construction G 45–47 Wholesale and retail trade; repair of motor vehicles at Section z z k jm ht vb om l.c gm remediation activities an Lu Water supply; sewerage, waste management and n va ey t re 50 Tran Thi Hieu Master’s Thesis VNP20-2015 and motorcycles 49–53 Transportation and storage I 55–56 Accommodation and food service activities J 58–63 Information and communication w 64–66 Financial and insurance activities 68 Real estate activities t to H ng hi ep n K lo ju y th 69–75 Professional, scientific and technical activities yi M ad L pl 77–82 O 84 va P 85 Education Q 86–88 Human health and social work activities R 90–93 Arts, entertainment and recreation S 94–96 Other service activities Administrative and support service activities Public administration and defense; compulsory n ua al N n social security ll fu oi m at nh z z services-producing Activities of extraterritorial organizations and bodies an Lu 99 om activities of households for own use U employers; l.c goods-and as gm undifferentiated households k 97–98 jm T of ht vb Activities n va ey t re 51