Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/284147 
Year of Publication: 
2023
Series/Report no.: 
cemmap working paper No. CWP23/23
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
Slope coefficients in rank-rank regressions are popular measures of intergenerational mobility, for instance in regressions of a child's income rank on their parent's income rank. In this paper, we first point out that commonly used variance estimators such as the homoskedastic or robust variance estimators do not consistently estimate the asymptotic variance of the OLS estimator in a rank-rank regression. We show that the probability limits of these estimators may be too large or too small depending on the shape of the copula of child and parent incomes. Second, we derive a general asymptotic theory for rank-rank regressions and provide a consistent estimator of the OLS estimator's asymptotic variance. We then extend the asymptotic theory to other regressions involving ranks that have been used in empirical work. Finally, we apply our new inference methods to three empirical studies. We find that the confidence intervals based on estimators of the correct variance may sometimes be substantially shorter and sometimes substantially longer than those based on commonly used variance estimators. The differences in confidence intervals concern economically meaningful values of mobility and thus lead to different conclusions when comparing mobility in U.S. commuting zones with mobility in other countries.
Subjects: 
Regression analysis
correlation
inductive statistics
estimation theory
intergenerational mobility
USA
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
900.12 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.