Conditional Rank-Rank Regression
Victor Chernozhukov, Iv\'an Fern\'andez-Val, Jonas Meier, Aico van Vuuren, Francis Vella

TL;DR
This paper introduces conditional rank-rank regression, a new method to measure within-group association accounting for covariates, with theoretical foundations and an empirical application to intergenerational income mobility in Switzerland.
Contribution
It proposes the conditional rank-rank regression approach, providing a natural measure of within-group association and a flexible estimation method with large sample inference.
Findings
Stronger intergenerational income persistence between fathers and sons than with daughters.
Within-group persistence explains 62% of income persistence for sons and 52% for daughters.
Smaller families and higher paternal education are associated with greater income persistence.
Abstract
Rank-rank regression is commonly employed in economic research as a way of capturing the relationship between two economic variables. The slope of this regression is the Spearman rank correlation, a classical measure of association. However, in many applications it is common practice to include covariates to account for differences in association levels between groups as defined by the values of these covariates. This is either done by including the covariates or by modeling the residuals obtained after partialing out the impact of the covariates. In each of these instances the resulting rank-rank regression coefficients can be difficult to interpret. We propose the conditional rank-rank regression, which uses conditional ranks instead of unconditional ranks, to measure average within-group persistence. The coefficient of this new regression corresponds to the average Spearman rank…
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Taxonomy
TopicsBayesian Methods and Mixture Models · Control Systems and Identification · Advanced Statistical Methods and Models
