Detail publikace

A Meta-Analysis of the Frisch Extensive Margin Elasticity

Autor: Ali Elminejad ,
doc. PhDr. Tomáš Havránek Ph.D.,
prof. Roman Horváth Ph.D.,
Typ: IES Working Papers
Rok: 2020
Číslo: 32
ISSN / ISBN:
Publikováno v:
Místo vydání: Prague
Klíčová slova: Frisch elasticity, extensive margin, meta-analysis, publication bias, Bayesian model averaging
JEL kódy: E24, J20, J21, C83
Citace: 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.
Abstrakt: A key parameter in structural models is the Frisch elasticity of labor supply at the extensive margin, but empirical estimates vary greatly. We provide a quantitative synthesis of the literature. To this end, we collect 723 estimates from 36 studies along with 22 explanatory variables reflecting studies’ characteristics and address model uncertainty by Bayesian and frequentist model averaging. Using linear and non-linear techniques, we find that publication bias exaggerates the mean of reported elasticities in the literature from 0.25 to 0.49. Our findings also suggest that two principal characteristics affect the magnitude of estimated elasticities systematically. First, identification bias: studies that follow a quasi-experimental approach tend to report smaller estimates. Second, aggregation bias: studies using macro data tend to report larger estimates. Furthermore, estimates associated with prime age or male workers tend to be systematically smaller, while studies relying on specific-industry data, near retirement workers, and probit regression tend to be larger.
Ke stažení: wp_2020_32_elminejad, havranek, horvath
Prosinec 2020
poútstčtsone
 123456
78910111213
14151617181920
21222324252627
28293031   

Partneři

Deloitte

Sponzoři

CRIF
McKinsey
Patria Finance