Quantitative Economics
Journal Of The Econometric Society
Edited by: Stéphane Bonhomme • Print ISSN: 1759-7323 • Online ISSN: 1759-7331
Edited by: Stéphane Bonhomme • Print ISSN: 1759-7323 • Online ISSN: 1759-7331
Quantitative Economics: Jul, 2019, Volume 10, Issue 3
The dispersion of individual returns to experience, often referred to as heterogeneity of income profiles (HIP), is a key parameter in empirical human capital models, in studies of life‐cycle income inequality, and in heterogeneous agent models of life‐cycle labor market dynamics. It is commonly estimated from age variation in the covariance structure of earnings. In this study, I show that this approach is invalid and tends to deliver estimates of HIP that are biased upward. The reason is that any age variation in covariance structures can be rationalized by age‐dependent heteroscedasticity in the distribution of earnings shocks. Once one models such age effects flexibly the remaining identifying variation for HIP is the shape of the tails of lag profiles. Credible estimation of HIP thus imposes strong demands on the data since one requires many earnings observations per individual and a low rate of sample attrition. To investigate empirically whether the bias in estimates of HIP from omitting age effects is quantitatively important, I thus rely on administrative data from Germany on quarterly earnings that follow workers from labor market entry until 27 years into their career. To strengthen external validity, I focus my analysis on an education group that displays a covariance structure with qualitatively similar properties like its North American counterpart. I find that a HIP model with age effects in transitory, persistent and permanent shocks fits the covariance structure almost perfectly and delivers small and insignificant estimates for the HIP component. In sharp contrast, once I estimate a standard HIP model without age‐effects the estimated slope heterogeneity increases by a factor of thirteen and becomes highly significant, with a dramatic deterioration of model fit. I reach the same conclusions from estimating the two models on a different covariance structure and from conducting a Monte Carlo analysis, suggesting that my quantitative results are not an artifact of one particular sample.
Income processes heterogeneity human capital returns identification robustness C23 D31 E24 J24 J31
March 5, 2024
The terms of the Editors of the Econometric Society's three journals end June 30, 2025. We are pleased to announce the incoming Editors and to thank the outgoing Editors for their excellent and continuing service.
Econometrica: Since 2019, Guido Imbens has served as the 14th Editor of Econometrica. On July 1, 2025, Marina Halac will become the Editor.
Quantitative Economics: Stéphane Bonhomme has been the Editor of Quantitative Economics since 2021. His successor will be Bernard Salanié.
Theoretical Economics: The Editor of Theoretical Economics since 2021 has been Simon Board. Taking over for him in July 2025 will be Federico Echenique.
Guido, Stéphane, and Simon have been outstanding Editors. We are grateful to them for the work they have done and will continue to do, and we look forward to further congratulating them next year. We believe Marina, Bernard, and Federico will be outstanding successors and we thank them in advance for their service.
Finally, we are grateful to Larry Samuelson for chairing all three search committees, and we thank the search committee members for their hard and fruitful work:
Econometrica: Christian Dustmann, Lars Hansen, Alessandro Lizzeri, George Mailath, Ariel Pakes, Helene Rey, and Elie Tamer.
QE: Kate Ho, Michael Keane, Felix Kubler, Whitney Newey, and Frank Schorfheide.
TE: Jeff Ely, Johannes Horner, Gilat Levy, Meg Meyer, and Ran Spiegler.