SKILLED AND UNSKILLED LABOR ARE LESS SUBSTITUTABLE THAN COMMONL
SKILLED AND UNSKILLED LABOR ARE LESS SUBSTITUTABLE THAN COMMONL
| Autor: | prof. PhDr. Tomáš Havránek Ph.D. doc. PhDr. Zuzana Havránková Ph.D. Mgr. Olesia Zeynalova Lubica Laslopova |
|---|---|
| Typ: | IES Working Papers |
| Rok: | 2020 |
| Číslo: | 29 |
| ISSN / ISBN: | |
| Publikováno v: | IES Working Papers 29/2020 |
| Místo vydání: | Prague |
| Klíčová slova: | Elasticity of substitution, skill premium, meta-analysis, model uncertainty, publication bias |
| JEL kódy: | J23, J24, J31 |
| Citace: | Havranek T., Irsova Z., Laslopova L. and Zeynalova O. (2020): “Skilled and Unskilled Labor Are Less Substitutable than Commonly Thought” IES Working Papers 29/2020. IES FSV. Charles University |
| Abstrakt: | A key parameter in the analysis of wage inequality is the elasticity of substitution between skilled and unskilled labor. We question the common view that the elasticity exceeds 1. Two biases, publication and attenuation, conspire to pull the mean elasticity reported in the lit- erature to 1.9. After correcting for the biases, the literature is consistent with the elasticity in the US of 0.6–0.9. Our analysis relies on 729 estimates of the elasticity collected from 76 studies as well as 37 controls that reflect the context in which the estimates were obtained. We use recently developed nonlinear techniques to correct for publication bias and employ Bayesian and frequentist model averaging to address model uncertainty. Our results sug- gest that, first, insignificant estimates of the elasticity are underreported. Second, because researchers typically estimate the elasticity’s inverse, measurement error exaggerates the elasticity, and we show the exaggeration is substantial. Third, elasticities are systematically larger for developed countries, translog estimation, and methods that ignore endogeneity. |
| Ke stažení: | wp_2020_29_havranek, irsova, laslopova, zeynalova.pdf |
