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Citation Information

Type Working Paper - Center for Economics and Development Studies
Title Earnings differential between male-female in Indonesia: evidence from Sakernas data
Publication (Day/Month/Year) 2006
URL http://lp3e.fe.unpad.ac.id/wopeds/200608.pdf
This Research aims to analyze the earnings inequality in Indonesia and to know whether the earnings inequality can be explained by individual characteristic factors such as education and experience; location both urban-rural and province
where individual reside and work; and based on socio-demography-economic characteristic. Furthermore, this research tries to know how big those factors contribute to the existing inequality, before and after crisis. Using data from
SAKERNAS 1996, 1999, 2002, and 2004, the valid observation is about 145660 individual. Result of analysis clearly indicate that there are significant gender inequalities in earnings in Indonesia, based on education and experience; urbanrural location and province where individual reside and work and based on sociodemography-economic characteristic. The profile of earnings inequality by gender seems to be an “inverted U” fashion, with the male-female earnings gap
narrowing as educational attainment went up, and reached a plateau at the “postsecondary level” and then tapered off. The analysis also suggests that the industrial affiliation of female workers matter.The result of estimating Mincerian
earnings equation shows that such factor as human capital (years of schooling and experience); socio-demography-economic characteristic (being household’s head, gender, marriage status, work sector); and location factors (urban-rural and
province which individual reside and work), significantly affects individual earning in Indonesia. Meanwhile, the result of decomposing this earnings inequality indicate that factor causing earnings inequality between “male” and “female” is about 41.6 percent caused by endowment differences. On the other hand, most of the gap about 58.4 percent attributed to unobserved and unexplained factors, rather than attributed to differences in observable

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