Is Thailand s Labor Market Really Woman Friendly? Revisiting the Declining Gender Wage Gap Asst. Prof. Sasiwimon Warunsiri Paweenawat (UTCC) Asst. Prof. Jessica Vechbanyongratana (Econ Chula) Asst. Prof. Yong Yoon (Econ Chula)
Decline in Thai Wage Gap, 1985 25 (Nakavachara, 21) In 25 the wage gap stood at about 9%.
Narrowing of Thai Gender Wage Gap, 21-214 (LFS).16.14.12.1.8.6.4.2 Log Real Wage Gap (Weighted) 21 22 23 24 25 26 27 28 29 21 211 212 213 214
Narrowing of Thai Gender Wage Gap by Region, 21-214 (LFS).25 Log Real Wage Gap by Region (Weighted).2.15.1.5 21 22 23 24 25 26 27 28 29 21 211 212 213 214 -.5 Bangkok Central North Northeast South
Research Questions Is the Thai labor market really woman friendly? In other words, is the decline and even reversal in the gender wage gap a real phenomenon or can it be explained by a data sampling issue? What happens when we take into consideration the informal and selfemployed workers (data selection issue)?
Previous Literature There are several studies in recent years that have examined trends and explanations of the gender wage gap (Oaxaca-Blinder approach) Nakavachara (21) The gender wage gap in Thailand declined from 34-9% between 1985 and 25 Rapidly increasing female education explains the majority of the decline Khorpetch & Kulkolkarn (211) Female workers were shown to be more productive than the men, but received lower wages than male workers because of their gender The degree of gender discrimination is very strong in the group of young and middle age group (15-24 and 25-54). Nimchaiyanun & Osossathanankul (213) The gender discrimination is the main factor determining gender wage differential in all regions in Thailand. There are different degrees of gender discrimination across regions due to the different socio-economic structure of different regions as well as different campaigns regarding promoting gender balance in each region. This project takes into consideration: Data selection issues Informal sector (large part of the labor force; not covered by minimum wage laws; disproportionately represented by women(?))
Data Part 1 Thai Labor Force Surveys 21-214 Selection criteria Employees (government/government enterprise and private firm workers) who report labor income Working age (15-6 years old) Not currently enrolled in school
Data Part 2 Socio-economic Survey 27-215 (odd years) Individual files Working age (15-6 years old) Not currently enrolled in school Reported labor income or business income from own-account work Types of workers Government/government enterprise workers Private firm workers Own-account workers Identify formal and informal workers according to MoL definition Formal workers: government/government enterprise workers; private firm workers covered by social security or employer-provided welfare Informal workers: own-account workers; private firm workers not covered by social security or other employer-provided welfare
Methodology Descriptive data exploration Dummy variable regressions with interactions to capture wage gap trends Dependent variable Log wages Log (wages + business profits of own-account workers) Independent variables Year (y t = dummy variables for each year) Gender (female = 1, male =) Public-Private (public sector = 1, private sector = ) Informality (informal = 1, formal = )
Wages and Gender Wage Gaps (LFS) Real Monthly Wages Log Real Wage Gap (Weighted) 14 12 1 8 6 4 2 21 22 23 24 25 26 27 28 29 21 211 212 213 214.16.14.12.1.8.6.4.2 Male Female 21 22 23 24 25 26 27 28 29 21 211 212 213 214
Regional Wages and Gender Wage Gaps (LFS) Real Monthly Wages by Region Log Real Wage Gap by Region (Weighted) 25.25 2.2 15.15 1.1 5.5 21 22 23 24 25 26 27 28 29 21 211 212 213 214 -.5 21 22 23 24 25 26 27 28 29 21 211 212 213 214 Bangkok M Central North Northeast South Bangkok Central North Northeast South
Public Sector Employment (LFS).6 Fraction working in public sector by region Fraction working in public sector that are females by region.5.6.4.3.2.1.55.5.45 21 22 23 24 25 26 27 28 29 21 211 212 213 214.4 21 22 23 24 25 26 27 28 29 21 211 212 213 214 Bangkok M Central North Northeast South Bangkok M Central North Northeast South
Public-Private Wage Gaps All Thailand, 21-214 (LFS) lnw ijt = β + β 1 female i + β 2 public j + δ t y t + γ it female i y t + θ jt public j y t + π ijt female i public j y t + ε ijt 1.6 Public-Private Wage Gap Northeast (Weighted) Public-Private Wage Gap All Thailand (Weighted) 1.4 1.2 1.2 1 1.8.8.6.6.4.4.2.2 21 22 23 24 25 26 27 28 29 21 211 212 213 214 21 22 23 24 25 26 27 28 29 21 211 212 213 214 -.2 -.2 Male Private Male Public Female Private Female Public Male Private Male Public Female Private Female Public
Observations About Public-Private Wage Gaps Public-private sector wage gap Public sector workers earn significantly more than private firm workers. Public-private wage has declined significantly, especially after 28. Overall, women have made gains Gender gap in the private sector is narrowing Women s earnings in the public sector are higher than for men by the end of the period and higher for women in the northeast for most of the period The reversed wage gap in the northeast is driven by the fact that a high proportion of employees are public sector workers and the proportion of public employees that are women is growing. The implementation of the new minimum wage/salary laws seem to have disproportionately helped women, possibly due to women working disproportionately low-wage jobs in private firms and in occupations that require higher education in the public sector (i.e. teachers and nurses).
Issues with Analysis Using LFS Analysis largely captures the formal sector Cannot separate out informal workers in private firms in the LFS Does not take into consideration the self-employed, which makes up a significant part of the labor force and are not covered by minimum wage laws. Are women in the informal sector being left behind?
Informal Sector Employment (SES) Fraction Informal by Region Fraction of Informal Sector That Is Female by Region.7.6.6.5.5.4.4.3.3.2.2.1.1 27 29 211 213 215 27 29 211 213 215 Bangkok Central North Northeast South Bangkok Central North Northeast South Note: Informal employment is defined as working for private firms not covered by social security and self-employment.
Formal-Informal Labor Income Gap (SES) lnw ijt = β + β 1 female i + β 2 informal j + δ t y t + γ it female i y t + θ jt informal j y t + π ijt female i informal j y t + ε ijt Formal-Informal Gap Labor Income All Thailand Formal-Informal Gap Labor Income Northeast.2.2 -.2 27 29 211 213 215 -.2 27 29 211 213 215 -.4 -.4 -.6 -.6 -.8 -.8-1 -1-1.2-1.2 Male-Formal Male-Informal Female-Formal Female-Informal -1.4 Male-Formal Male-Informal Female-Formal Female-Informal
Formal-Informal Labor Income Gap, Private Firms Only (SES) lnw ijt = β + β 1 female i + β 2 informal j + δ t y t + γ it female i y t + θ jt informal j y t + π ijt female i informal j y t + ε ijt Formal-Informal Gap Private Firm Workers All Thailand Formal-Informal Gap Private Firm Workers Northeast.4.4.2.2 27 29 211 213 215 27 29 211 213 215 -.2 -.2 -.4 -.4 -.6 -.6 -.8 -.8-1 -1 Male-Formal Male-Informal Female-Formal Female-Informal Male-Formal Male-Informal Female-Formal Female-Informal
Formal-Informal Income Gaps, Labor Income and Business Income for Self-employed (SES) lnw ijt = β + β 1 female i + β 2 informal j + δ t y t + γ it female i y t + θ jt informal j y t + π ijt female i informal j y t + ε ijt Formal-Informal Gap Labor and Business Income All Thailand Formal-Informal Gap Labor and Business Income Northeast.2.2 27 29 211 213 215 1 2 3 4 5 -.2 -.2 -.4 -.4 -.6 -.6 -.8 -.8-1 -1 Male-Formal Male-Informal Female-Formal Female-Informal Male-Formal Male-Informal Female-Formal Female-Informal
Gender Earnings Gap for Own-account Workers (SES) lnw it = β + β 1 female i + δ t y t + γ it female i y t + ε it Gender Earnings Gap Own-account Worker Business Profits All Thailand Gender Earnings Gap Own-account Worker Business Profits Northeast Thailand.3.2.1 -.1 27 29 211 213 215.35.3.25.2.15.1.5 -.2 -.3 -.4 -.5 -.1 -.15 27 29 211 213 215 Male Female Male Female
Preliminary Conclusions and Discussion The gap appears to be declining across most of the country since 28. The public sector has higher wages on average and we can see that women are participating in the public sector in higher percentages over time. This is contributing to the decline in the gap. The implementation of the 212/213 minimum wage law and minimum salary in the public sector appears to have disproportionately helped women. Women in private firms were more likely to be in low-wage jobs that were affected by the implementation of the minimum wage. Between 1/5 and 1/4 of women in the public sector are teachers and nurses which require university degrees, while public sector men were more likely to work as police or other occupations that do not require degrees. This means the minimum salary would disproportionately affect women.
Preliminary Conclusions and Discussion Informal sector Female informal workers earn significantly less than male informal workers (17-24%) Gap between informally employed men and women in private firms remained constant, but the overall gap between informally employed women and formally employed men declined. Surprisingly, much of the gains for informal employees are observed after the implementation of the minimum wage, which suggests spillover effects from the formal sector. Although own-account worker business profits are rising over time, the gender gap in own-account worker business profits is constant over 27-215. However, the overall gap between own-account women and formally employed men is decreasing.
Other Areas to Explore.7 Gender Wage Gap by Age (LFS).6.5.4.3.2.1 -.1 21 22 23 24 25 26 27 28 29 21 211 212 213 214 -.2 Age 21-25 Age 26-35 Age 36-45 Age 46-55 Age 56-6
Other Areas to Explore.4.35.3.25.2.15.1.5 Gender Wage Gap by Education Level (LFS) 21 22 23 24 25 26 27 28 29 21 211 212 213 214 Less than Elementary Elementary Lower Secondary Upper Secondary Upper Vocational University and Above
Next Steps Determine correct weights to use with SES data Further explore the roles of age and gender in driving the gender wage gap. Explicitly estimate the impact of the 212/213 implementation of the minimum wage law on the gender wage gap in different areas of the country. Write the paper!