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Measuring the Relationship Between Youth Criminal Participation and Household Economic Resources

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Abstract

Using data from the NLSY97, this paper re-examines the empirical relationship between household economic resources and youth criminal participation. Previous estimates of this relationship have often suggested this relationship to be quite weak or even non-existent. However, this analysis suggests that much of the strength of the relationship between household economic resources and youth criminal participation may be obscured due to non-linearities in this relationship, the fact that this relationship is isolated to crimes of a serious nature only, and especially because of measurement error with respect to measuring household economic resources. I show that adjusting for these issues substantially increases the estimated strength of this relationship. Indeed, the results in this paper show that the differences in serious criminal participation between youth from households in the upper parts of the income distribution and youth from households in the lower parts of the income distribution appear to be greater than the difference in serious criminal participation between genders.

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Notes

  1. It should be emphasized the IV methods used in this paper are used to adjust for measurement error only, and are not meant to shed any light on the existence or magnitude of causal effects of household economic resources on youth criminal participation.

  2. See Steffensmeier and Allan (1996) for a discussion of male/famale differences in criminality.

  3. Technically, this “observation year” will be more than one year, as respondents in the sample used in this analysis were interviewed an average of 19.9 months after completing the first round interview. The length of this “observation year” does not appear to differ substantially across the household income distribution, with the mean length for the youth from the poorest third of the household wealth distribution averaging 20.0 months between the first and second round interviews, youth from the middle third of the household wealth distribution averaging 19.7 months between interviews, and youth from the richest third of the household wealth distribution also averaging 19.8 months between interviews. Therefore, while observation year for youth from the poorest third of the household wealth distribution does cover activity over a slightly longer period of time, the difference works out to only about 3/10 of a month or 9 days.

  4. A few individuals refused to answer a crime question or answered “don’t know.” However, since all of these respondents who refused to answer or answered “don’t know” to a particular crime question answered in the affirmative to a different crime question, it does not matter whether these ambiguous responses are treated as affirmatives or negatives since I will only be looking at whether an individual participated in a crime during the time between the first and second round interviews.

  5. Individuals who were not interviewed in the second round or for which there was no data on household income and/or wealth from 1997 were dropped from the sample used for this analysis. This latter criteria left 5,577 of the 8,386 NLSY97 individuals who had second round interviews. As shown in Appendix Table 4, these individuals who were excluded from the analysis appear to be generally similar to those remaining in the analysis with respect to numerous characteristics. Moreover, all OLS regression results remains essentially unchanged if these individuals are kept in the sample and multiple imputation is used to account for the missing data (results available from the author upon request).

  6. All regression results reported in this paper are weighted using the NLSY97 individual weights, and standard errors clustered at the household level.

  7. The actual cutoffs were $19,000 for the second quintile and $51,000 for the fourth quintile.

  8. This method is discussed in a variety of sources, including Grilches and Hausman (1986), Bound et al. (2001), Wooldridge (2002).

  9. Interestingly, the estimated coefficient is actually significantly positive for Hispanic youth with respect to participation in minor crime.

References

  • Bound J, Brown C, Mathiowetz N (2001) Measurement error in survey data. In: Heckman JJ, Leamer E (eds) Handbook of econometrics, vol 5. North-Holland, Amsterdam

    Google Scholar 

  • Brown S (1984) Social class, child maltreatment, and delinquent behavior. Criminology 22:259–278

    Article  Google Scholar 

  • Brownfield D (1986) Social class and violent behavior. Criminology 24:421–438

    Article  Google Scholar 

  • Clelland D, Carter TJ (1980) The new myth of class and crime. Criminology 18:319–336

    Article  Google Scholar 

  • Duncan G, Brooks-Gunn J, Klebanov P (1994) Economic deprivation and early-childhood development. Child Dev 65:296–318

    Article  Google Scholar 

  • Elliot DS, Ageton S (1980) Reconciling race and class differences in self-reported and official estiamtes of delinquency. Am Sociol Rev 45:95–110

    Google Scholar 

  • Fuller W (1987) Measurement error models. Wiley, New York

    Google Scholar 

  • Griliches Z, Hausman JA (1986) Errors in variables in panel data. J Econ 31:93–118

    Google Scholar 

  • Hagan J (1985) Modern criminology: crime, criminal behavior, and its control. McGraw-Hill, New York

    Google Scholar 

  • Hindelang M, Hirschi T, Weis J (1981) Measuring delinquency. Sage Publications, Beverly Hills

    Google Scholar 

  • Johnson R (1980) Social class and delinquent behavior. Criminology 18:86–93

    Article  Google Scholar 

  • Johnstone JWC (1978) Social class, social areas, and delinquency. Sociol Social Res 63:49–72

    Google Scholar 

  • Kleck G (1982) On the use of self-report data to determine the class distribution of criminal and delinquent behavior. Am Sociol Rev 47:427–433

    Article  Google Scholar 

  • Krohn M, Akers R, Radosevich M, Lanza-Kaduce L (1980) Social status and deviance: social context of school, social forces, and delinqent behavior. Criminology 18:303–318

    Google Scholar 

  • Mayer S (1997) What money can’t buy: family income and children’s life chances. Harvard University Press, Cambridge, MA

    Google Scholar 

  • Merton RK (1957) Social structure and social theory. Free Press, Glencoe, IL

    Google Scholar 

  • Nettler G (1978) Social status and self-reported criminality. Social Forces 57:304–305

    Article  Google Scholar 

  • Reckless W (1967) The crime problem, 4th edn. Appleton-Century-Crofts, New York

    Google Scholar 

  • Smith J, Brooks-Gunn J, Klebanov P (1997) Consequences of growing up poor for young children. In: Duncan G, Brooks-Gunn J (eds) Consequences of growing up poor. Russell Sage, New York

    Google Scholar 

  • Snyder H, Sickmund M (1999) Juvenile offenders and victims: 1999 national report. Office of Juvenile Justice and Delinquency Prevention, Washington, DC

    Google Scholar 

  • Solon G (1992) Intergenerational income mobility in the United States. Am Econ Rev 82:393–408

    Google Scholar 

  • Steffensmeier D, Allan E (1996) Gender and crime: toward a gendered theory of female offending. Annu Rev Sociol 22:459–487

    Article  Google Scholar 

  • Thornberry TP, Farnworth M (1982) Social correlates of criminal involvement: further evidence on the relationship between social status and criminal behavior. Am Sociol Rev 47:505–518

    Google Scholar 

  • Tittle C, Villemez WJ, Smith D (1978) The myth of social class and criminality: an empirical assessment of the empirical evidence. Am Sociol Rev 43:643–656

    Google Scholar 

  • Tittle C, Meier R (1990) Specifying the SES/delinquency relationship. Criminology 28:271–299

    Article  Google Scholar 

  • Turner CF, Kim L, Rogers SM, Lindberg LD, Pleck JH, Sonenstein FL (1998) Adolescent sexual behavior, drug use, and violence: increased reporting with computer survey technology. Science 280:867–873

    Article  Google Scholar 

  • Weiss J (1987) Social class and crime. In: Gottfredson MR, Hirschi T (eds) Positive criminology. Sage, Newbury Park, CA

    Google Scholar 

  • Wiatrowski M, Griswold D, Roberts M (1981) Social control theory and delinquency. Am Sociol Rev 4:525–541

    Article  Google Scholar 

  • Wolfgang M, Ferracuti F (1967) The subculture of violence: towards and integrated theory in criminology. Tavistock Press, London

    Google Scholar 

  • Wooldridge J (2002) Econometric analysis of cross section and panel data. The MIT Press, Cambridge, MA

    Google Scholar 

  • Wright BR, Caspi EA, Miech R, Silva P (1999) Reconsidering the relationship between ses and delinquency: causation but not correlation. Criminology 37:175–194

    Article  Google Scholar 

  • Zimmerman DJ (1992) Regression toward mediocrity in economics stature. Am Econ Rev 82:409–429

    Google Scholar 

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  1. McMaster University and RAND Corporation, 1776 Main Street, P.O. Box 2138, Santa Monica, CA, 90407, USA

    David Bjerk

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  1. David Bjerk
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Correspondence to David Bjerk.

Appendix

Appendix

Table 4 Differences between sample and those excluded from sample due to missing income data
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Bjerk, D. Measuring the Relationship Between Youth Criminal Participation and Household Economic Resources. J Quant Criminol 23, 23–39 (2007). https://doi.org/10.1007/s10940-006-9017-8

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