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231006 ||| eng |
| 100 |
1 |
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|a Ahsan, Md. Nazmul
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| 245 |
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|a What the Mean Measures of Mobility Miss
|h Elektronische Ressource
|b Learning about Intergenerational Mobility from Conditional Variance
|c Md. Nazmul Ahsan
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| 260 |
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|a Washington, D.C
|b The World Bank
|c 2022
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| 300 |
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|a 50 pages
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| 653 |
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|a Risk Adjusted Mobility Measures
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| 653 |
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|a Paternal Educational Attainment
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| 653 |
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|a Father's Educational Influence
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| 653 |
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|a Education Equity
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| 653 |
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|a Education Gender Gap
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| 653 |
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|a Social Development
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| 653 |
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|a Children's Economic Outcomes
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| 653 |
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|a Education
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| 653 |
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|a Primary Schooling
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| 653 |
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|a Intergenerational Educational Mobility
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| 653 |
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|a Family Educational Attainment
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| 653 |
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|a Conditional Variance
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| 653 |
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|a Access and Equity in Basic Education
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| 653 |
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|a Social Capital
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| 653 |
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|a Gender
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| 700 |
1 |
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|a Shilpi, Forhad
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| 700 |
1 |
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|a Hanchen, Jiang
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| 700 |
1 |
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|a Emran, M. Shahe
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b WOBA
|a World Bank E-Library Archive
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| 028 |
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|a 10.1596/1813-9450-10074
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| 856 |
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|u http://elibrary.worldbank.org/doi/book/10.1596/1813-9450-10074
|x Verlag
|3 Volltext
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| 082 |
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|a 330
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| 520 |
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|a The magnitude of underestimation is especially large for the children born into the most disadvantaged households where fathers have no schooling, while it is negligible for the children of college educated fathers. The standard (but partial) measures may lead to an incorrect ranking of regions and groups in terms of relative mobility. Compared to the risk-adjusted measures, the standard measures are likely to underestimate the gender gap and rural-urban gap in educational opportunities
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| 520 |
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|a To understand the role of family background in intergenerational mobility, a large literature has focused on the conditional mean of children's economic outcomes given parent's economic status, while ignoring the information contained in conditional variance. This paper explores the effects of family background on the conditional variance of children's outcomes in the context of intergenerational educational mobility using data from three large developing countries (China, India, and Indonesia). The empirical analysis uses exceptionally rich data free of sample truncation because of the nonresident children at the time of the survey. Evidence from all three countries suggests a strong influence of father's education on the conditional variance of children's schooling. The analysis finds substantial heterogeneity across countries, gender, and geography (rural/urban).
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| 520 |
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|a Cohort-based estimates suggest that the effects of father's education on the conditional variance have changed qualitatively; in some cases, a positive effect in the 1950s cohort turns into a substantial negative effect in the 1980s cohort. A methodology is developed to incorporate the effects of family background on the conditional variance along with the standard conditional mean effects. This paper derives risk-adjusted measures of relative and absolute mobility by accounting for an estimate of the risk premium for the conditional variance faced by a child. The estimates of risk-adjusted relative and absolute mobility for China, India, and Indonesia suggest that the existing evidence using the standard measures of mobility substantially underestimates the effects of family background on children's educational opportunities, and thus gives a false impression of high educational mobility.
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