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Estimating returns to schooling in I...

Pattinasarany, Gregorius Daan Vincent.

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Estimating returns to schooling in Indonesia: Evidence from the Indonesia Family Life Survey, 1993--2000.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Estimating returns to schooling in Indonesia: Evidence from the Indonesia Family Life Survey, 1993--2000./
作者:	Pattinasarany, Gregorius Daan Vincent.
面頁冊數:	239 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-12, Section: A, page: 4555.
Contained By:	Dissertation Abstracts International64-12A.
標題:	Economics, General. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3116017

Estimating returns to schooling in Indonesia: Evidence from the Indonesia Family Life Survey, 1993--2000.
Pattinasarany, Gregorius Daan Vincent.

Estimating returns to schooling in Indonesia: Evidence from the Indonesia Family Life Survey, 1993--2000. - 239 p.

Source: Dissertation Abstracts International, Volume: 64-12, Section: A, page: 4555.

Thesis (Ph.D.)--Michigan State University, 2003.

The rate of return to schooling investment in Indonesia is estimated using the Indonesia Family Life Survey (IFLS) of 1993, 1997 and 2000. This study explicitly takes into account measures to overcome omitted variable and sample selection biases. Parental schooling information is used to correct for omitted variable bias, while sample selection bias is corrected by modeling employment outcomes into several labor market alternatives. Returns to schooling are estimated for adults aged 25–59 years who are self-employed as well as those who are working in the public and private sectors. Separate estimates for men and women are presented for each of the cross section data of 1993, 1997 and 2000.Subjects--Topical Terms:

1017424
Economics, General.

Estimating returns to schooling in Indonesia: Evidence from the Indonesia Family Life Survey, 1993--2000.
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245 1 0 $a Estimating returns to schooling in Indonesia: Evidence from the Indonesia Family Life Survey, 1993--2000.
300 $a 239 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-12, Section: A, page: 4555.
500 $a Adviser: John A. Strauss.
502 $a Thesis (Ph.D.)--Michigan State University, 2003.
520 $a The rate of return to schooling investment in Indonesia is estimated using the Indonesia Family Life Survey (IFLS) of 1993, 1997 and 2000. This study explicitly takes into account measures to overcome omitted variable and sample selection biases. Parental schooling information is used to correct for omitted variable bias, while sample selection bias is corrected by modeling employment outcomes into several labor market alternatives. Returns to schooling are estimated for adults aged 25–59 years who are self-employed as well as those who are working in the public and private sectors. Separate estimates for men and women are presented for each of the cross section data of 1993, 1997 and 2000.
520 $a Some important findings of this study are the following. Individuals with more formal schooling are more favorably rewarded and, thus, have higher returns to schooling. Wage advantage increases in a convex fashion with levels of schooling. Over years, wage advantages within each level of schooling are, in general, declining. Supply shifts among individuals with more schooling might serve as one of the possible explanations for the declining rates.
520 $a Parental education captures part of individuals' family background information as the inclusion of it in the wage regression reduces estimated coefficients of individuals' schooling variables. Although the effects of parental schooling on individuals' returns are limited, the results reveal that having educated parents is associated with an increase in earnings relative to having illiterate parents.
520 $a Sample selection bias does not turn to be important in these wage regressions. Selectivity correction terms are mainly significant in the self-employment wage regressions. Likewise, the potential bias from migration seems to be small. Individuals who were born or are currently living in urban areas do not have a wage advantage that is significantly different from their counterparts who were born or are currently living in rural areas. Stratifying individuals based on their age reveals that younger individuals (aged 25–39) who are working in the private sector have a lower rate of return in comparison to that of the older generation (aged 40–59).
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