An estimation of worker and firm effects with censored data
Ainara González de San Román and
Yolanda F. Rebollo-Sanz ()
No 2014-28, Economics Discussion Papers from Kiel Institute for the World Economy (IfW)
In this paper, the authors develop a new estimation method that is suitable for censored models with two high-dimensional fixed effects and that is based on a sequence of least squares regressions, yielding significant savings in computing time and hence making it applicable to frameworks in which standard estimation techniques become unfeasible. The authors analyze its theoretical properties and evaluate its practical performance in small samples through a detailed Monte Carlo study. Finally, using a longitudinal match employer-employee dataset from Spain, they show that the biases encountered when ignoring censored issues can be significant to the role of firms in terms of wage dispersion: individual heterogeneity explains more than 60% of wage dispersion.
Keywords: fixed effects; algorithm; wage decomposition; censoring; simulation; assortative matching (search for similar items in EconPapers)
JEL-codes: I21 I24 J16 J31 (search for similar items in EconPapers)
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Journal Article: AN ESTIMATION OF WORKER AND FIRM EFFECTS WITH CENSORED DATA (2018)
Working Paper: Estimation of worker and firm effects with censored data (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:ifwedp:201428
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