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Estimating intergenerational mobility with incomplete data : coresidency and truncation bias in rank-based relative and absolute mobility measures

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  • Emran,M. Shahe
  • Shilpi,Forhad J.

Abstract

The rank-based measures of intergenerational mobility have become increasingly popular in economics literature. Recent evidence shows that rank-based measures are less affected by measurement error and life-cycle bias compared with other standard measures such as intergenerational regression coefficient and intergenerational correlation. However, most of the available household surveys suffer from sample truncation, because coresidency is used to define household membership. There is no evidence on how sample truncation affects the rank-based mobility estimates relative to intergenerational regression coefficient and intergenerational correlation. This paper provides evidence on this in the context of intergenerational schooling persistence, using two exceptional surveys from India and Bangladesh that include all children irrespective of residency status. The analysis shows that the measures of relative mobility (slopes) are biased downward in coresident samples, but the average bias in rank correlation is less than half of that in intergenerational regression coefficient, and comparable to that in intergenerational correlation in magnitude. The intercept estimates are biased upward, with the largest bias found in the intercept of the regression used for intergenerational correlation. Truncation bias in rank-based absolute mobility estimates is the lowest in most cases. The results strengthen the case for rank-based measures of intergenerational mobility when working with the standard household surveys.

Suggested Citation

  • Emran,M. Shahe & Shilpi,Forhad J., 2018. "Estimating intergenerational mobility with incomplete data : coresidency and truncation bias in rank-based relative and absolute mobility measures," Policy Research Working Paper Series 8414, The World Bank.
  • Handle: RePEc:wbk:wbrwps:8414
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    Keywords

    Educational Sciences; Labor&Employment Law; Gender and Development; Inequality; Public Sector Management and Reform;

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

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