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Effects of family background on crime participation and criminal earnings: an empirical analysis of siblings

Abstracts

This study exploits the sibling structure of the National Longitudinal Survey of Youth data to measure the degree to which family background explains the variance in the propensity to engage in criminal activities and in the intensity and success of crime participation as measured by the level of criminal earnings. A multiple-equation model whose reduced form disturbances are connected by a common unobservable variable having a variance-components structure is developed and estimated. Estimation results indicate a high level of association (net of observable measures of family background) between the unobserved factors affecting siblings' propensity to engage in criminal activities in a family, with estimated intra-family correlations ranging from 0.44 to 0.55. Sharing a common family background explains around 25% of the variance of the unconditional criminal income. The results suggest that ignoring family background effects leads to a significant upward bias in the effects of race and education on the propensity to engage in income-generating crime.

family effects; crime; latent variable; variance components models


Este estudo usa dados do National Longitudinal Survey of Youth para medir a extensão pela qual interações sociais de família explicam a variância na probabilidade de participação em crime e na intensidade e sucesso em atividades criminais. A estimação é baseada em um mo-delo de equações múltiplas cujas perturbações são interligadas por uma variável inobservável comum. A virtude do método proposto é usar dados referentes a irmãos - que compartilham as mesmas características maternas e paternas em relação a fatores de família que possivelmente influenciam a sua própria decisão de engajar em atividades ilegais - para estimar o efeito do background familiar na decisão de participar em crime. Os resultados empíricos indicam um alto nível de correlação entre fatores inobserváveis medindo efeitos de família e a propensão de irmãos em participar de atividades criminosas (0.44 a 0.55). Efeitos de família explicam 25% da variância em renda criminal. Finalmente, os resultados sugerem que estimativas que ignoram o background familiar induzem vieses significantes no efeito de variáveis, tais como raça e educação na propensão de jovens a participar de crimes patrimoniais.

efeitos de família; crime; variáveis latentes; dados longitudinais


Effects of family background on crime participation and criminal earnings: an empirical analysis of siblings

Liliana E. Pezzin

Medical College of Wisconsin - Health Policy Institute and Department of Medicine

ABSTRACT

This study exploits the sibling structure of the National Longitudinal Survey of Youth data to measure the degree to which family background explains the variance in the propensity to engage in criminal activities and in the intensity and success of crime participation as measured by the level of criminal earnings. A multiple-equation model whose reduced form disturbances are connected by a common unobservable variable having a variance-components structure is developed and estimated. Estimation results indicate a high level of association (net of observable measures of family background) between the unobserved factors affecting siblings' propensity to engage in criminal activities in a family, with estimated intra-family correlations ranging from 0.44 to 0.55. Sharing a common family background explains around 25% of the variance of the unconditional criminal income. The results suggest that ignoring family background effects leads to a significant upward bias in the effects of race and education on the propensity to engage in income-generating crime.

Key words: family effects, crime, latent variable, variance components models.

JEL Classification

K42, C33

RESUMO

Este estudo usa dados do National Longitudinal Survey of Youth para medir a extensão pela qual interações sociais de família explicam a variância na probabilidade de participação em crime e na intensidade e sucesso em atividades criminais. A estimação é baseada em um mo-delo de equações múltiplas cujas perturbações são interligadas por uma variável inobservável comum. A virtude do método proposto é usar dados referentes a irmãos - que compartilham as mesmas características maternas e paternas em relação a fatores de família que possivelmente influenciam a sua própria decisão de engajar em atividades ilegais - para estimar o efeito do background familiar na decisão de participar em crime. Os resultados empíricos indicam um alto nível de correlação entre fatores inobserváveis medindo efeitos de família e a propensão de irmãos em participar de atividades criminosas (0.44 a 0.55). Efeitos de família explicam 25% da variância em renda criminal. Finalmente, os resultados sugerem que estimativas que ignoram o background familiar induzem vieses significantes no efeito de variáveis, tais como raça e educação na propensão de jovens a participar de crimes patrimoniais.

Palavras-chave: efeitos de família, crime, variáveis latentes, dados longitudinais.

Full text available only in PDF format.

Texto completo disponível apenas em PDF.

REFERENCES

AMEMYIA, T. The estimation of a simultaneous-equations generalized probit model. Econometrica 46, p. 1193-1205, 1978.

BECKER, G. Crime and punishment: an economic approach. In: LANDES, W.; BECKER, G. (eds.), Essays in the economics of crime and punishment. 1968.

BECKER, G.; TOMES, N. Child endowments and the quantity and quality of children. Journal of Political Economy, v. 84, n. 4, p. S143-S162, 1976.

BECKER, Gary S. A theory of social interactions. Journal of Political Economy, v. 82, n. 6, p. 1063-93, 1974.

BEHRMAN, J.; TAUBMAN, P. Intergenerational transmission of income and wealth. American Economic Review 66, p. 436-440, 1976.

BEHRMAN, J.; TAUBMAN, P.; WALES, T. Controlling for and measuring the effects of genetics and family environment in equations for schooling and labor market success. In: TAUBMAN, P. (ed.), Kinometrics. New-York: North-Holland, 1977.

BEHRMAN, J.; POLLAK, R.; TAUBMAN, P. Parental preferences and provision for progeny. Journal of Political Economy, v. 90, n. 1, p. 52-73, 1986.

BLOCK, M.; HEINEKE, J. A labor theoretic analysis of the criminal choice. American Economic Review 65, p. 314-325, 1975.

CHAMBERLAIN, G. Panel data. In: GRILICHES, Z.; INTRILIGATOR, M. (eds.), Handbook of econometrics, vol. II, 1984.

CHAMBERLAIN, G.; GRILICHES, Z. Unobservables with a variance component structure: ability, schooling, and the economic success of brothers. International Economic Review, v. 16, n. 2, p. 442-449, 1975.

_______. More on brothers. In: TAUBMAN, P. (ed.), Kinometrics. 1977.

CORCORAN, M.,; JENCKS, C.; OLNECK, M. The effects of family background on earnings. American Economic Review 66, p. 430-435, 1976.

EHRLICH, I. Participation in illegitimate activities: a theoretical and empirical investigation. Journal of Political Economy 81, p. 521-567, 1973.

FARRINGTON, D. Early precursors of frequent offending. In: WILSON, J.Q.; LOURY, G. (eds.), From children to citizens. Vol. 3. Springer-Verlag, 1987.

FREEMAN, R. B. The economis of crime. In: ASHENFELTER; CARD, D. (eds.), Handbook of labor economics. Vol. 3. Amsterdam, Holland: Elsevier Science, 1999.

FREEMAN, R. B.; RODGERS, W. M. Area economic conditions and the labor market outcomes of young men in the 1990s expansion. National Bureau of Economic Research Working Paper 7073, Cambridge University Press, 1999.

GLAESER, E. L.; SACERDOTE, B.; SCHEINKMAN, J. A. Crime and social interactions. Quaterly Journal of Economics 111, p. 507-548, 1996.

GOTTFREDSON, M.; HIRSCHI, T. A general theory of crime. Stanford University Press, 1990.

GOULD, E. D.; WEINBERG, B. A.; MUSTARD, D. Crime rates and local labor market opportunities in the United States. Review of Economics and Statistics, v. 84, n. 1, p. 45-61, 2002.

GREENE, W. Econometric analysis. New York, NY: Macmillan Publishing Company, 1993.

GRILICHES, Z. Sibling models and data in economics: beginnings of a survey. Journal of Political Economy, v. 87, n. 5, p. S37-S64, 1979.

GROGGER, J. Arrests, persistent youth joblessness and black/white employment differentials. Review of Economics and Statistics, v. 74, n. 1, p. 100-106, 1992.

HECKMAN, J. Sample selection as a specification error. Econometrica 47, p. 153-161, 1979.

HECKMAN, J.; WILLIS, R. Estimation of a stochastic model of reproduction. In: TERLECKYJ, N. (ed.), Household production and consumption. Columbia University Press, 1975.

HINDELANG, M.; HIRSCHI, M.; WEIS, J. Measuring delinquency. Beverly Hills: Sage Publications, 1981.

HIRSCHI, T. Crime and the family. In: WILSON, J. Q. (ed.), Crime and public policy. Institute for Contemporary Studies, 1983.

KEARL; POPE. Unobservable family and individual contributions to the distributions of income and wealth. Journal of Labor Economics, v. 4, n. 3, p. S48-S79, 1986.

LAM, D.; SCHOENI, R. Effects of family background on earnings and returns to schooling: evidence from Brazil. Journal of Political Economy, v. 101, n. 41, p. 710-740, 1993.

LAUB, J.; SAMPSON, R. Unraveling families and delinquency. Criminology 26, p. 355-380, 1988.

LEVITT, S. D. Why do increased arrest rates appear to reduce crime: dterrence, incapacitation, or measurement error? Economic Inquiry, v. 36, n. 3, p. 353-72, 1998a.

_______. Juvenile crime and punishment. Journal of Political Economy, v. 106, n. 6, p. 1156-85, 1998b.

LOEBER, R.; STOUTHAMER-LOEBER, M. Family factors as correlates and predictors of juvenile conduct problems and delinquency. In: TONRY, M.; MORRIS, N. (eds.), Crime and justice. Chicago: University of Chicago Press, 1986.

MENDONÇA, M. J. C.; LOUREIRO, P. R. A.; SACHSIDA, A. Interação social e crimes violentos: uma análise empírica a partir dos dados do Presídio de Papuda. Estudos Econômicos, v. 32, n. 4, p. 621-41, out./dez. 2002.

MUSTARD, David B. Re-examining criminal behavior: the importance of omitted variable bias. Review of Economics and Statistics. v. 85, n. 1, p. 205-211, 2003.

OLNECK. On the use of sibling data to estimate the effects of family background, cognitive skills and schooling. In: TAUBMAN, P. (ed.), Kinometrics. New York: North-Holland, 1977.

PEZZIN, L. E. Incentivos de mercado e comportamento criminoso: uma análise econômica dinâmica. Estudos Econômicos, v. 24, n. 3, p. 373-404, jul./set. 1994.

_______. Estimating panel selection models. Working Paper, Agency for Healthcare Research and Quality. Rockville, MD, 2003.

SAH, R. Social osmosis and patterns of crime. Journal of Political Economy 99, p. 1272-1295, 1991.

SCHEINKMAN, J. A.; WOODFORD, M. Self-organized criticality and economic fluctuations. American Economic Review LXXXIV, p. 417-421, 1994.

SCHMIDT, P.; WITTE, A. D. Predicting criminal recidivism using split population models. Journal of Econometrics 40, p. 141-159, 1989.

SJOQUIST, D. Property crime and economic behavior: some empirical evidence. American Economic Review 63, p. 439-446, 1973.

SOLON, G.; CORCORAN, M.; GORDON, R.; LAREN, D. A longitudinal analysis of sibling correlations in economic status. Journal of Human Resources, v. 26, n. 3, p. 509-534, 1991.

TAUBMAN, P. The determinants of earnings: genetics, family and other environments: a study of white male twins. American Economic Review, v. 66, n. 5, p. 858-870, 1976.

VERBEEK, M.; NIJMAN, T. Testing for selectivity bias in panel data models. International Economic Review, v. 33, n. 2, p. 681-703, 1992.

VISCUSI, K. Market incentives for criminal behavior. In: FREEMAN, R. (ed.), Inner city black youth employment. NBER Series. Chicago: University of Chicago Press, 1986.

WILSON, W. J. The truly disadvantaged. Chicago: University of Chicago Press, 1987.

WITTE, A. D. Estimating the economic model of crime with individual data. Quarterly Journal of Economics 94, p. 57-84, 1980.

WOOLDRIDGE, J. Selection corrections for panel data models under conditional independence assumptions. 1992. Unpublished manuscript.

WOLFGANG, M.; FIGLIO, R.; SELLIN, T. Delinquency in a birth cohort. Chicago: University of Chicago Press, 1972.

(Recebido em maio de 2003. Aceito para publicação em janeiro de 2004)

I am grateful to Shelly Lundberg, Robert Pollak, Raaj Sah, Barbara Schone, Jeffrey Wooldridge , and two anonymous referees for many helpful comments and suggestions.The views expressed in the paper are those of the author.No official endorsement by either the Medical College of Wisconsin or the Health Policy Institute is intended or should be inferred. lpezzin@mcw.edu

  • AMEMYIA, T. The estimation of a simultaneous-equations generalized probit model. Econometrica 46, p. 1193-1205, 1978.
  • BECKER, G. Crime and punishment: an economic approach. In: LANDES, W.; BECKER, G. (eds.), Essays in the economics of crime and punishment. 1968.
  • BECKER, G.; TOMES, N. Child endowments and the quantity and quality of children. Journal of Political Economy, v. 84, n. 4, p. S143-S162, 1976.
  • BECKER, Gary S. A theory of social interactions. Journal of Political Economy, v. 82, n. 6, p. 1063-93, 1974.
  • BEHRMAN, J.; TAUBMAN, P. Intergenerational transmission of income and wealth. American Economic Review 66, p. 436-440, 1976.
  • BEHRMAN, J.; TAUBMAN, P.; WALES, T. Controlling for and measuring the effects of genetics and family environment in equations for schooling and labor market success. In: TAUBMAN, P. (ed.), Kinometrics. New-York: North-Holland, 1977.
  • BEHRMAN, J.; POLLAK, R.; TAUBMAN, P. Parental preferences and provision for progeny. Journal of Political Economy, v. 90, n. 1, p. 52-73, 1986.
  • BLOCK, M.; HEINEKE, J. A labor theoretic analysis of the criminal choice. American Economic Review 65, p. 314-325, 1975.
  • CHAMBERLAIN, G. Panel data. In: GRILICHES, Z.; INTRILIGATOR, M. (eds.), Handbook of econometrics, vol. II, 1984.
  • CHAMBERLAIN, G.; GRILICHES, Z. Unobservables with a variance component structure: ability, schooling, and the economic success of brothers. International Economic Review, v. 16, n. 2, p. 442-449, 1975.
  • _______. More on brothers. In: TAUBMAN, P. (ed.), Kinometrics. 1977.
  • CORCORAN, M.,; JENCKS, C.; OLNECK, M. The effects of family background on earnings. American Economic Review 66, p. 430-435, 1976.
  • EHRLICH, I. Participation in illegitimate activities: a theoretical and empirical investigation. Journal of Political Economy 81, p. 521-567, 1973.
  • FARRINGTON, D. Early precursors of frequent offending. In: WILSON, J.Q.; LOURY, G. (eds.), From children to citizens. Vol. 3. Springer-Verlag, 1987.
  • FREEMAN, R. B. The economis of crime. In: ASHENFELTER; CARD, D. (eds.), Handbook of labor economics. Vol. 3. Amsterdam, Holland: Elsevier Science, 1999.
  • FREEMAN, R. B.; RODGERS, W. M. Area economic conditions and the labor market outcomes of young men in the 1990s expansion. National Bureau of Economic Research Working Paper 7073, Cambridge University Press, 1999.
  • GLAESER, E. L.; SACERDOTE, B.; SCHEINKMAN, J. A. Crime and social interactions. Quaterly Journal of Economics 111, p. 507-548, 1996.
  • GOTTFREDSON, M.; HIRSCHI, T. A general theory of crime. Stanford University Press, 1990.
  • GOULD, E. D.; WEINBERG, B. A.; MUSTARD, D. Crime rates and local labor market opportunities in the United States. Review of Economics and Statistics, v. 84, n. 1, p. 45-61, 2002.
  • GREENE, W. Econometric analysis New York, NY: Macmillan Publishing Company, 1993.
  • GRILICHES, Z. Sibling models and data in economics: beginnings of a survey. Journal of Political Economy, v. 87, n. 5, p. S37-S64, 1979.
  • GROGGER, J. Arrests, persistent youth joblessness and black/white employment differentials. Review of Economics and Statistics, v. 74, n. 1, p. 100-106, 1992.
  • HECKMAN, J. Sample selection as a specification error. Econometrica 47, p. 153-161, 1979.
  • HECKMAN, J.; WILLIS, R. Estimation of a stochastic model of reproduction. In: TERLECKYJ, N. (ed.), Household production and consumption Columbia University Press, 1975.
  • HINDELANG, M.; HIRSCHI, M.; WEIS, J. Measuring delinquency. Beverly Hills: Sage Publications, 1981.
  • HIRSCHI, T. Crime and the family. In: WILSON, J. Q. (ed.), Crime and public policy Institute for Contemporary Studies, 1983.
  • KEARL; POPE. Unobservable family and individual contributions to the distributions of income and wealth. Journal of Labor Economics, v. 4, n. 3, p. S48-S79, 1986.
  • LAM, D.; SCHOENI, R. Effects of family background on earnings and returns to schooling: evidence from Brazil. Journal of Political Economy, v. 101, n. 41, p. 710-740, 1993.
  • LAUB, J.; SAMPSON, R. Unraveling families and delinquency. Criminology 26, p. 355-380, 1988.
  • LEVITT, S. D. Why do increased arrest rates appear to reduce crime: dterrence, incapacitation, or measurement error? Economic Inquiry, v. 36, n. 3, p. 353-72, 1998a.
  • _______. Juvenile crime and punishment. Journal of Political Economy, v. 106, n. 6, p. 1156-85, 1998b.
  • LOEBER, R.; STOUTHAMER-LOEBER, M. Family factors as correlates and predictors of juvenile conduct problems and delinquency. In: TONRY, M.; MORRIS, N. (eds.), Crime and justice Chicago: University of Chicago Press, 1986.
  • MENDONÇA, M. J. C.; LOUREIRO, P. R. A.; SACHSIDA, A. Interaçăo social e crimes violentos: uma análise empírica a partir dos dados do Presídio de Papuda. Estudos Econômicos, v. 32, n. 4, p. 621-41, out./dez. 2002.
  • MUSTARD, David B. Re-examining criminal behavior: the importance of omitted variable bias. Review of Economics and Statistics v. 85, n. 1, p. 205-211, 2003.
  • OLNECK. On the use of sibling data to estimate the effects of family background, cognitive skills and schooling. In: TAUBMAN, P. (ed.), Kinometrics. New York: North-Holland, 1977.
  • PEZZIN, L. E. Incentivos de mercado e comportamento criminoso: uma análise econômica dinâmica. Estudos Econômicos, v. 24, n. 3, p. 373-404, jul./set. 1994.
  • _______. Estimating panel selection models. Working Paper, Agency for Healthcare Research and Quality. Rockville, MD, 2003.
  • SAH, R. Social osmosis and patterns of crime. Journal of Political Economy 99, p. 1272-1295, 1991.
  • SCHEINKMAN, J. A.; WOODFORD, M. Self-organized criticality and economic fluctuations. American Economic Review LXXXIV, p. 417-421, 1994.
  • SCHMIDT, P.; WITTE, A. D. Predicting criminal recidivism using split population models. Journal of Econometrics 40, p. 141-159, 1989.
  • SJOQUIST, D. Property crime and economic behavior: some empirical evidence. American Economic Review 63, p. 439-446, 1973.
  • SOLON, G.; CORCORAN, M.; GORDON, R.; LAREN, D. A longitudinal analysis of sibling correlations in economic status. Journal of Human Resources, v. 26, n. 3, p. 509-534, 1991.
  • TAUBMAN, P. The determinants of earnings: genetics, family and other environments: a study of white male twins. American Economic Review, v. 66, n. 5, p. 858-870, 1976.
  • VERBEEK, M.; NIJMAN, T. Testing for selectivity bias in panel data models. International Economic Review, v. 33, n. 2, p. 681-703, 1992.
  • VISCUSI, K. Market incentives for criminal behavior. In: FREEMAN, R. (ed.), Inner city black youth employment NBER Series. Chicago: University of Chicago Press, 1986.
  • WILSON, W. J. The truly disadvantaged. Chicago: University of Chicago Press, 1987.
  • WITTE, A. D. Estimating the economic model of crime with individual data. Quarterly Journal of Economics 94, p. 57-84, 1980.
  • WOOLDRIDGE, J. Selection corrections for panel data models under conditional independence assumptions. 1992. Unpublished manuscript.
  • WOLFGANG, M.; FIGLIO, R.; SELLIN, T. Delinquency in a birth cohort Chicago: University of Chicago Press, 1972.

Publication Dates

  • Publication in this collection
    28 Sept 2009
  • Date of issue
    Sept 2004

History

  • Received
    May 2003
  • Accepted
    Jan 2004
Departamento de Economia; Faculdade de Economia, Administração, Contabilidade e Atuária da Universidade de São Paulo (FEA-USP) Av. Prof. Luciano Gualberto, 908 - FEA 01 - Cid. Universitária, CEP: 05508-010 - São Paulo/SP - Brasil, Tel.: (55 11) 3091-5803/5947 - São Paulo - SP - Brazil
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