Discussion Paper

No. 2016-17 | April 26, 2016
Minimum Wage and Employment: Escaping the Parametric Straitjacket

Abstract

Parametric regression models are often not flexible enough to capture the true relationships as they tend to rely on arbitrary identification assumptions. Using the UK Labor Force Survey, the authors estimate the causal effect of national minimum wage (NMW) increases on the probability of job entry and job exit by means of a non-parametric Bayesian modelling approach known as Bayesian Additive Regression Trees (BART). The application of this methodology has the important advantage that it does not require ad-hoc assumptions about model fitting, number of covariates and how they interact. They find that the NMW exerts a positive and significant impact on both the probability of job entry and job exit. Although the magnitude of the effect on job entry is higher, the overall effect of NMW is ambiguous as there are many more employed workers. The causal effect of NMW is higher for young workers and in periods of high unemployment and they have a stronger impact on job entry decisions. No significant interactions were found with gender and qualifications.

JEL Classification:

C23, C11, C14, J3, J4

Assessment

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Links

Cite As

Stefano Cabras, Jan Fidrmuc, and Juan de Dios Tena (2016). Minimum Wage and Employment: Escaping the Parametric Straitjacket. Economics Discussion Papers, No 2016-17, Kiel Institute for the World Economy. http://www.economics-ejournal.org/economics/discussionpapers/2016-17


Comments and Questions


Anonymous - Referee Report 1
May 17, 2016 - 15:28

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Anonymous - Referee Report 2
June 07, 2016 - 15:45

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Stefano Cabras, Jan Fidrmuc, and Juan de Dios Tena - Replies to Referee Report 1 and 2
December 06, 2016 - 13:55

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Stefano Cabras, Jan Fidrmuc, and Juan de Dios Tena - Revised Version
December 06, 2016 - 13:59

See attached file