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Conviction, Gender and Labour Market Status: A Propensity Score Matching Approach

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  • Sciulli, Dario

Abstract

This paper applies propensity score matching methods to National Child Development Study dataset to evaluate the effect of conviction on labour market status, paying specific attention to gender differences. Estimation results show that employment is strongly and negatively affected by conviction, while it increases self-employment, unemployment and inactivity. This possibly indicates employers’ stigmatization against convicted and discouragement effect after a conviction. However, conviction acts differently between males and females. It reduces employment probabilities by about 10% among males and by about 20% among females. More important, while males recover part of the reduced employment probability moving toward self-employment, conviction results in a strong marginalization on the labour market for females, as unemployment and, overall, inactivity strongly increase. This suggests a stronger discouragement effect for females and a different attitude toward self-employment. Social and economic policies aimed to fight social exclusion and to promote employment of convicted individuals should take into account also the great disadvantage of convicted females.

Suggested Citation

  • Sciulli, Dario, 2010. "Conviction, Gender and Labour Market Status: A Propensity Score Matching Approach," MPRA Paper 25054, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:25054
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    File URL: https://mpra.ub.uni-muenchen.de/25054/1/MPRA_paper_25054.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    propensity score matching; conviction; gender; labour market status.;

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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