A Distributional Framework for Matched Employer Employee Data

By S. Bonhomme, Thibaut Lamadon, Elena Manresa. Econometrica, 2019

231 citations recorded by the source corpus.

We propose a framework to identify and estimate earnings distributions and worker composition on matched panel data, allowing for two‐sided worker‐firm unobserved heterogeneity and complementarities in earnings. We introduce two models: a static model that allows for nonlinear interactions between workers and firms, and a dynamic model that allows, in addition, for Markovian earnings dynamics and endogenous mobility. We show that this framework nests a number of structural models of wages and worker mobility. We establish identification in short panels, and develop tractable two‐step estimators where firms are classified in a first step. Applying our method to Swedish administrative data, we find that log‐earnings are approximately additive in worker and firm heterogeneity. Our estimates imply the presence of strong sorting patterns between workers and firms, and a small contribution of firms—net of worker composition—to earnings dispersion. In addition, we document that wages have a direct effect on mobility, and that, beyond their dependence on the current firm, earnings after a job move also depend on the previous employer.

Subfields: Economics and Econometrics, General Health Professions

View Paper: https://www.semanticscholar.org/paper/6c739caf19af700e3757591099570209d9d60e80

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Citations in the corpus

Firms and the Decline in Earnings Inequality in Brazil (2017, unknown): “Similar conclusions have been reached among others for Germany (Andrews et al., 2008; Card et al., 2013), Italy (Iranzo et al., 2008), Portugal (Card et al., 2016), Brazil (Lopes de Melo, 2015), Sweden (Bonhomme et al., 2016), Denmark (Bagger and Lentz, 2016), and the United States (Abowd et al., 19”
Estimation of a Roy/Search/Compensating Differential Model of the Labor Market (2020, unknown): “…where the premarket skill explained most of the variation, most of the variation in utility is explained by the interaction between compensating differentials 41Bødker (2019) estimates the model by Bonhomme, Lamadon, and Manresa (2019) on Danish data and finds very similar results. and search.”
Estimation and Inference about Heterogeneous Treatment Effects in High-Dimensional Dynamic Panels. (2017, background): “…Weidner (2015), Moon and Weidner (2016), Kock (2016b), Manresa (2016), Lu and Su (2016), Su et al. (2016), Moon et al. (2018), Kock and Tang (2019), Bonhomme et al. (2019a), Bonhomme et al. (2019b), Gao and Li (2019), Chen et al. (2020), Lu and Su (2020)) among many others, see FernandezVal and…”
Imperfect Competition, Compensating Differentials and Rent Sharing in the U.S. Labor Market (2019, unknown): “Following Bonhomme et al. (2019), estimation is implemented using LIML on these moment conditions where the θj are concentrated on the post-move time period (in theory they can be estimated without imposing stationarity).”
Discretizing Unobserved Heterogeneity (2017, methodology): “Hence (12) holds, where s̃i and H̃ are identical to si and H above, except that W (k) it is replaced by W̃ (k) it =Wk(Yit, Xit, αit0), and the expectations are now conditional on both ξi0 and λt0.”
Firms and Labor Market Inequality: Evidence and Some Theory (2018, background): “Firms and Labor Market Inequality S35 A different approach to assessing the additive separability assumption comes from Bonhomme, Lamadon, and Manresa (2015), who estimate a worker-firmmodel with discrete heterogeneity where each pairing of worker and firm type is allowed a different wage effect.”