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Minimum wage and employment: Escaping the parametric straitjacket

Author

Listed:
  • Cabras, Stefano
  • Fidrmuc, Jan
  • de Dios Tena Horrillo, Juan

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.

Suggested Citation

  • Cabras, Stefano & Fidrmuc, Jan & de Dios Tena Horrillo, Juan, 2016. "Minimum wage and employment: Escaping the parametric straitjacket," Economics Discussion Papers 2016-17, Kiel Institute for the World Economy (IfW).
  • Handle: RePEc:zbw:ifwedp:201617
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    References listed on IDEAS

    as
    1. Allegretto, Sylvia & Dube, Arindrajit & Reich, Michael & Zipperer, Ben, 2013. "Credible Research Designs for Minimum Wage Studies," Institute for Research on Labor and Employment, Working Paper Series qt3hk7s3fw, Institute of Industrial Relations, UC Berkeley.
    2. S. Petrone & J. Rousseau & C. Scricciolo, 2014. "Bayes and empirical Bayes: do they merge?," Biometrika, Biometrika Trust, vol. 101(2), pages 285-302.
    3. Card, David & Krueger, Alan B, 1995. "Time-Series Minimum-Wage Studies: A Meta-analysis," American Economic Review, American Economic Association, vol. 85(2), pages 238-243, May.
    4. Mark B. Stewart, 2004. "The employment effects of the national minimum wage," Economic Journal, Royal Economic Society, vol. 114(494), pages 110-116, March.
    5. Barry T. Hirsch & Bruce E. Kaufman & Tetyana Zelenska, 2015. "Minimum Wage Channels of Adjustment," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 54(2), pages 199-239, April.
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    7. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    8. Lee, Kevin C & Pesaran, M Hashem & Pierse, Richard G, 1990. "Testing for Aggregation Bias in Linear Models," Economic Journal, Royal Economic Society, vol. 100(400), pages 137-150, Supplemen.
    9. Hristos Doucouliagos & T. D. Stanley, 2009. "Publication Selection Bias in Minimum-Wage Research? A Meta-Regression Analysis," British Journal of Industrial Relations, London School of Economics, vol. 47(2), pages 406-428, June.
    10. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
    11. Arindrajit Dube & T. William Lester & Michael Reich, 2010. "Minimum Wage Effects Across State Borders: Estimates Using Contiguous Counties," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 945-964, November.
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    More about this item

    Keywords

    BART; causal inference; regression approach; matching regression;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • J4 - Labor and Demographic Economics - - Particular Labor Markets

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