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Title: Intergenerational Mobility in the United States and Abroad: Quantile and Mean Regression Measures
Resulting in 1 citation.
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Grawe, Nathan D. |
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Intergenerational Mobility in the United States and Abroad: Quantile and Mean Regression Measures Ph.D. Dissertation, The University of Chicago, 2001. DAI-A 62/07, p. 2514, January 2002. Cohort(s): Older Men, Young Men Publisher: UMI - University Microfilms, Bell and Howell Information and Learning Keyword(s): Cross-national Analysis; Earnings; German Socio-Economic Panel (GSOEP); Germany, German; Intergenerational Patterns/Transmission; Mobility; NCDS - National Child Development Study (British); Pakistan, Pakistani; Panel Study of Income Dynamics (PSID); Poverty; Variables, Instrumental This paper provides an international comparison of rates of intergenerational income mobility. Age-dependence of income persistence estimates (explained and quantified in this work) suggests that comparisons of multiple studies using different selection rules will result in erroneous conclusions. While little difference is found in the rate of mean regression between industrialized countries, mobility among exceptional sons is found to be much faster in the US and Canada than in Germany or the UK. I also provide a first look at mobility in five developing and underdeveloped countries: Ecuador, Malaysia, Nepal, Pakistan, and Peru. In general, it appears that mobility is slower in these countries. All of these findings are similar to results found in the occupational mobility literature. In addition to these empirical findings the thesis develops a new test for binding intergenerational credit constraints based on quantile regression. And a method is created to correct quantile regression estimates for the bias resulting from measurement error. A variation of this method allows for a quantile regression analogy to the two-sample instrumental variables estimator. |
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Bibliography Citation
Grawe, Nathan D. Intergenerational Mobility in the United States and Abroad: Quantile and Mean Regression Measures. Ph.D. Dissertation, The University of Chicago, 2001. DAI-A 62/07, p. 2514, January 2002.. |