Intergenerational Mobility in American History: Accounting for Race and Measurement Error

Ward, Zachary

doi:10.2139/ssrn.3926937

Cited by 4 publications

(8 citation statements)

References 67 publications

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“…income (e.g., occupational status as in Ward (2022a) or human capital as in de la Croix and Goni (2022)). In such cases, pointmasses in the income distribution create ties in the ranks and their presence changes inference in the rank-rank regression in at least three important ways: (i) the interpretation of the estimand in the rank-rank regression changes, (ii) the estimand changes with the way in which ties are handled, and (iii) the statistical properties of the OLS estimator change with the way ties are handled.…”

Section: Rank-rank Regressions With Noncontinuous Marginal Distributionsmentioning

confidence: 99%

“…In this section, we analyze intergenerational mobility in the U.S. as in Song et al (2020) and Ward (2022a), who measure mobility by the rank-rank relationship between fathers' and sons' occupational status. We focus on cohorts covered by the PSID dataset used in Ward (2022a). Data.…”

Section: Intergenerational Mobility In the Us -Occupational Statusmentioning

confidence: 99%

“…These three modifications to Ward (2022a)'s regression specification allow us to interpret the regression slopes as rank-rank regression slopes and the model fits into (10). 10 We estimate the rank-rank regression with and without the covariates used by Ward (2022a). Ranks are defined as in (9) with ω = 1.…”

Section: Intergenerational Mobility In the Us -Occupational Statusmentioning

confidence: 99%

“…1 The resulting measures are important inputs to broader political and public debates about inequality, the importance of the family and the neighborhood into which children are born, and opportunities for children to grow out of poverty (Mogstad and Torsvik (2023)). Besides intergenerational mobility, regressions involving ranks have also been used in a range of other areas in economics such as education (e.g., Chetty et al (2011), Murphy and Weinhardt (2020), Carneiro et al (2023)), crime (e.g., Sharkey and Torrats-Espinosa (2017)), or migration (e.g., Ward (2022b)).…”

Section: Introductionmentioning

confidence: 99%

“…We also apply our inference methods to Ward (2022a), who studies intergenerational mobility in terms of occupational status using PSID data. In this application, the confidence intervals based on our new variance estimators are similar to those based on commonly used variance estimators, except on a small subsample of parent-child cohort pairs in which the homoskedastic variance estimator leads to conservative inference.…”

Section: Introductionmentioning

confidence: 99%

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Inference for rank-rank regressions

2023

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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.

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Section: Rank-rank Regressions With Noncontinuous Marginal Distributionsmentioning

confidence: 99%

Section: Intergenerational Mobility In the Us -Occupational Statusmentioning

confidence: 99%

Section: Intergenerational Mobility In the Us -Occupational Statusmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Inference for rank-rank regressions

2023

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Name-Based Estimators of Intergenerational Mobility

Santavirta,

Stuhler

2024

The Economic Journal

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Recent studies use names—first and surnames—to estimate intergenerational mobility in sources that lack direct family links. While generating novel evidence on intergenerational transmission processes, it remains unclear how different estimators compare and how reliable they are. This paper evaluates the most popular name-based methods, using newly digitised records from Finland and U.S. Census data. We illustrate that their interpretation depends on sampling properties of the data, such as the overlap between the parent and child samples, which differ widely across studies. We correct for the attenuation bias from limited overlap and address other common problems encountered in applications.

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