The Sensitivity of Structural Labor Supply Estimations to Modeling Assumptions

Max Löffler, Andreas Peichl and Sebastian Siegloch

No 11425, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: There is still considerable dispute about the magnitude of labor supply elasticities. While differences in estimates especially between micro and macro models are recently attributed to frictions and adjustment costs, we show that the variation in elasticities derived from structural labor supply models can also be explained by modeling assumptions. Specifically, we estimate 3,456 different models on the same data each representing a plausible combination of frequently made choices. While many modeling assumptions do not systematically affect labor supply elasticities, our controlled meta-analysis shows that results are very sensitive to the treatment of hourly wages in the estimation. For example, different (sensible) choices concerning the modeling of the underlying wage distribution and especially the imputation of (missing) wages lead to point estimates of elasticities between 0.2 and 0.65. We hence conclude that researchers should pay more attention to the robustness of their estimations with respect to the wage treatment.

Keywords: labor supply; elasticity; random utility models; wages (search for similar items in EconPapers)
JEL-codes: C25 C52 H31 J22 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2018-03
New Economics Papers: this item is included in nep-lma and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Related works:
Working Paper: The Sensitivity of Structural Labor Supply Estimations to Modeling Assumptions (2018)
Working Paper: Structural Labor Supply Models and Wage Exogeneity (2014)
Working Paper: Structural Labor Supply Models and Wage Exogeneity (2014)
Working Paper: Structural labor supply models and wage exogeneity (2014)
Working Paper: Validating Structural Labor Supply Models (2013)
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