Sciulli, Dario (2010): Conviction, Gender and Labour Market Status: A Propensity Score Matching Approach.
Download (224kB) | Preview
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.
|Item Type:||MPRA Paper|
|Original Title:||Conviction, Gender and Labour Market Status: A Propensity Score Matching Approach|
|Keywords:||propensity score matching, conviction, gender, labour market status.|
|Subjects:||J - Labor and Demographic Economics > J2 - Demand and Supply of Labor > J21 - Labor Force and Employment, Size, and Structure
K - Law and Economics > K1 - Basic Areas of Law > K14 - Criminal Law
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
J - Labor and Demographic Economics > J1 - Demographic Economics > J16 - Economics of Gender; Non-labor Discrimination
|Depositing User:||Dario Sciulli|
|Date Deposited:||16. Sep 2010 12:36|
|Last Modified:||20. Mar 2014 02:21|
Becker S. and A. Ichino. 2002. Estimation of average treatment effects based on propensity scores. Stata Journal, vol. 2(4): 358-377. Bertrand M., E. Duflo, and S. Mullainathan. 2004. How much should we trust differences-in-differences estimates?. Quarterly Journal of Economics, vol. 119(1): 249-275. Black D.A. and J.A. Smith. 2004. How robust is the evidence on the effects of college quality? Evidence from matching. Journal of Econometrics, vol. 121: 99-124.
Bushway S.D. 2004. Labour market effects of permitting employer access to criminal history records. Journal of Contemporary Criminal Justice, vol. 20: 276-291.
Caliendo M. and S. Kopeinig. 2008. Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, vol. 22(1): 31-72.
Cho R.M. 2009. The impact of maternal imprisonment on children’s educational achievement – results from children in Chicago public schools. Journal of Human Resources vol. 44(3): 772-797.
Dehejia, R. and S. Wahba. 2002. Propensity score matching methods for nonexperimental causal studies. Review of Economics and Statistics, vol. 84 (1): 151–161.
Entorf H. 2009. Crime and labour market: evidence from a survey of inmates. IZA discussion paper n. 3976, Institute for the Study of Labor.
Freeman R.B. 1992. Crime and the employment of disadvantaged youth. In Drugs, Crime and Social Isolation: Barriers to Urban Opportunity (Eds. A. Harrell and G. Peterson). Washington, DC: Urban Institute Press.
Freeman R.B. 1999. The Economics of Crime. In Handbook of Labor Economics (Eds. O. Ashenfelter and D. Card) vol. 3 chapter 52. Elsevier: Amsterdam.
Grogger J. 1995. The effect of arrests on the employment and earnings of the young men. The Quarterly Journal of Economics, vol. 110: 51-71. Holzer H.J. 2007. Collateral costs: the effects of incarceration on the employment and earnings of young workers. IZA Discussion paper, n.3118, Institute for the Study of Labor.
Holzer, H.J., Raphael S., Stoll M. 2006. Perceived criminality, criminal background checks and the racial hiring practices of employers. Journal of Law and Economics, vol. 49: 451-80.
Home Office 2002. Prison Statistics: England and Wales 2002. Presented to Parliament by the Secretary of State for the Home Department by Command of Her Majesty, November 2003. National Statistics.
Kling J.R. 2006. Incarceration length, employment and earnings. American Economic Review vol. 96: 863-976.
LaLonde R.J., Cho R.M. 2008. The impact of incarceration in state prison on the employment prospects of women. Journal of Quantitative Criminology vol. 24: 243-265.
Lott, J. 1990. The effect of conviction on the legitimate income of criminals. Economic Letters vol. 34: 381-385.
Myers S.L. 1983. Estimating the economic model of crime: employment versus punishment effects. The Quarterly Journal of Economics vol. 98: 157-166.
Nagin D., Waldfogel J. 1995. The effects of criminality and conviction on the labor market status of young British offenders. International Review of Law and Economics, vol. 15: 109-126.
Nagin D., Waldfogel J. 1999. The effect of conviction on income through the life cycle. International Review of Law and Economics, vol. 18: 25-40.
Rasmusen, E. 1996. Stigma and self-fulfilling expectations of criminality. Journal of Law and Economics vol. 39: 519-544.
Rosenbaum P. and D. Rubin (1983) “The central role of the propensity score in observational studies for causal effect”, Biometrika, vol.70 pp. 41-50. Sciulli, D. 2010. Conviction, Partial Adverse Selection and Labour Market Discrimination. Quaderni del Dipartimento di Economia Politica n. 574, University of Siena.
Smith, J A. and Todd, P.E. 2005. Does matching overcome Lalonde’s critique of nonexperimental estimators?. Journal of Econometrics, vol. 125(1-2): 305-353.
Waldfogel, J. 1994. Does conviction have a persistent effect on income and eEmployment?. International Review of Law and Economics, vol. 14: 103-119.