Publication and Identification Biases in Measuring the Intertemporal Substitution of Labor Supply
| Author(s): | Ali Elminejad , prof. PhDr. Tomáš Havránek Ph.D., prof. Roman Horváth Ph.D., |
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| Type: | IES Working Papers |
| Year: | 2020 |
| Number: | 32 |
| ISSN / ISBN: | |
| Published in: | IES Working Papers 32/2020 |
| Publishing place: | Prague |
| Keywords: | Frisch elasticity, labor supply, extensive margin, meta-analysis, publication bias, Bayesian model averaging |
| JEL codes: | C83, E24, J21 |
| Suggested Citation: | Elminejad, A., Havranek T., Horvath R. (2020): "A Meta-Analysis of the Frisch Extensive Margin Elasticity". IES Working Papers 32/2020, IES FSV, Charles University. |
| Abstract: | The intertemporal substitution (Frisch) elasticity of labor supply governs the predictions of real business cycle models and models of taxation. We show that, for the extensive margin elasticity, two biases conspire to systematically produce large positive estimates when the elasticity is in fact zero. Among 723 estimates in 36 studies, the mean reported elasticity is 0.5. One half of that number is due to publication bias: larger estimates are reported preferentially. The other half is due to identification bias: studies with less exogenous time variation in wages report larger elasticities. Net of the biases, the literature implies a zero mean elasticity and, with 95% confidence, is inconsistent with calibrations above 0.25. To derive these results we collect 23 variables that reflect the context in which the elasticity was obtained, use nonlinear techniques to correct for publication bias, and employ Bayesian and frequentist model averaging to address model uncertainty. |
| Downloadable: |
WP_2020_32_elminejad, havranek, horvath |
