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Shop Crime and Deterrence: Evidence on Shoplifting among Young People in the Youth Lifestyle Survey (YLS)

  • George Saridakis EMAIL logo
Published/Copyright: September 26, 2013
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Review of Law & Economics
From the journal Review of Law & Economics Volume 9 Issue 2

Abstract

I use data from the 1998 Youth Lifestyle Survey to assess empirically the link between perceived deterrence and criminal involvement. I concentrate on shop theft and two specific deterrents: the perceived probability of detection and the perceived consequences stemming from detection in terms of job loss. The estimation of the deterrence model reveals that perceived deterrents significantly influence criminal activity. I investigate whether perceptions are determined simultaneously with crime, through learning in the light of personal experience. To overcome this simultaneity problem, I use an instrumental variables strategy to estimate the deterrence model. Recent techniques of propensity score matching algorithms developed are also considered. The results are robust and consistent with the deterrence theory.

Keywords: crime; deterrence; shoplifting

Appendix 1: survey questions on shoplifting

  • Q1. Have you ever stolen anything from a shop, supermarket or department store?

    1. Yes

    2. No

  • Q2. How many times have you ever done this?

    1. Once

    2. Twice

    3. 3–5 times

    4. 6–10 times

    5. 11–20 times

    6. More than 20 times

    7. Can’t remember

  • Q3. Have you stolen anything from a shop, supermarket or department store within the last 12 months?

    1. Yes

    2. No

  • Q4. How many times have you done this within the last 12 months?

    1. Once

    2. Twice

    3. 3–5 times

    4. 6–10 times

    5. 11–20 times

    6. More than 20 times

    7. Can’t remember

Appendix 2: survey questions on perceived deterrents

  • Q5. How likely is that someone like you would be caught taking something from a shop worth £20 without paying for it?

    1. Very likely

    2. Quite likely

    3. Not very likely

    4. Not at all likely

    5. It depends

  • Q6. If taken to court and found guilty of taking something from a shop worth £20 without paying for it, how difficult would someone like you find it…to keep your job/a job?

    1. Very difficult

    2. Quite difficult

    3. Not very difficult

    4. Not at all difficult

  • Q7. …to find another/a new job?

    1. Very difficult

    2. Quite difficult

    3. Not very difficult

    4. Not at all difficult

Appendix 3: Description of covariates (n = 1,686, weighted estimates with 95% confidence bands).

VariablesMean or sample (%)ValueVariablesMean or sample (%)Value
Age (at survey date)12–30Educational qualification
Male21.27±0.320–1No qualification (base)34.91±2.69–
Single50.00±2.900–1O levels40.97±2.840–1
Children in household70.81±2.660–1A levels12.61±2.110–1
Religious practice (belongs to church/mosque/etc.)19.67±2.120–1University degree11.51±2.060–1
Race66.93±2.76Family/disadvantage background
White (base)–Father jobless, retired or employee without managerial profession1 (base)
Black (Caribbean/African/other black groups)91.63±1.600–158.81±2.86–
Asian (Indian/Pakistani/Bangladeshi)1.62±0.560–1Absent father (had no-one considered to be father1)5.67±1.290–1
Other ethnic origin5.00±1.370–1Father managerial (father was employee and had managerial profession1)
Non-native born1.75±0.690–119.47±2.34–
Occupation/employment status (at survey date)5.99±1.46Father self-employed (with or without employees1)16.05±2.140–1
Working full-time (base)–Working mother (mother was employed or self-employed1)
School (inc. sixth form at school)42.12±2.890–173.02±2.550–1
Studying full-time (sixth form college/college/university)26.96±2.450–1Living with parents53.94±2.920–1
12.28±2.06Low parental supervision (parents rarely or never know who or where1)
Government youth training scheme0–123.83±2.520–1
Working part-time0.54±0.320–1Hard drug use (cocaine/crack/heroin)8.47±1.840–1
Unemployed5.68±1.170–1Perceptual measures of deterrence
Doing something else5.16±1.530–1Perceived risk of being caught (very/quite likely to be caught)40.30±2.830–1
Gross weekly income (£'00 per week)7.26±1.340–1
Weekly income £1 (base)Perceived current employment consequences (very/quite difficult to keep a job)79.62±2.280–1
No weekly income–
Refused to respond94.63±1.270–1Perceived future employment consequences (very/quite difficult to find a job)82.76±2.220–1
Gross weekly income (£'00 per week)1.24±0.550–1
4.13±1.150–1,500Regions and area characteristics
133.69±8.58Inner city area14.21±1.760–1
East Anglia and London (base)18.27±2.29–
North England (North/North West/York and Humberside)26.84±2.510–1
Midlands (East Midlands/West Midlands)17.80±2.210–1
South England (South East/South West)32.25±2.770–1
Wales4.84±1.090–1

Notes: 1For those aged 16 and over, refers to circumstances at the time the respondent was aged 15; for other, refers to current circumstances.

Acknowledgments

I appreciate the comments of Tonja Jacobi and Stephen Pudney on an earlier version of this paper.

References

Akers, R. 2000. Criminological Theories: Introduction, Evaluation and Application. Los Angeles: Roxbury Publishing Company.Search in Google Scholar

Anderson, L., T.Chiricos, and G.Waldo. 1977. “Formal and Informal Sanctions: A Comparison of Deterrent Effects,” 25Social Problems103–112.Search in Google Scholar

Bar-Gill, O., and A.Harel. 2001. “Crime Rates and Expected Sanctions: The Economics of Deterrence Revisited,” XXXJournal of Legal Studies485–501.10.1086/322055Search in Google Scholar

Becker, G. S. 1968. “Crime and Punishment: An Economic Approach,” 76Journal of Political Economy169–217.10.1007/978-1-349-62853-7_2Search in Google Scholar

Becker, S. O., and A.Ichino. 2002. “Estimation of Average Treatment Effects Based on Propensity Scores,” 2The Stata Journal358–377.10.1177/1536867X0200200403Search in Google Scholar

Brooks, C., and C.Cross. 1996. Retail Crime Costs: 1994/5 Survey. London: British Retail Consortium.Search in Google Scholar

Buckle, A., D. P.Farrington, J.Burrows, M.Speed, and T.Burns-Howell. 1992. “Measuring Shoplifting by Repeated Systematic Counting,” 3Security Journal137–146.Search in Google Scholar

Budd, T., C.Sharp, and P.Mayhew. 2005. “Offending in England and Wales: First Results from the 2003 Crime and Justice Survey”, Home Office Research Study 275.Search in Google Scholar

Burrows, J., and A.Lewis. 1987. “Stereotyping Shoplifters,” 3Policing226–232.Search in Google Scholar

Caliendo, M., and S.Kopeinig. 2005. “Some Practical Guidance for the Implementation of Propensity Score Matching,” Discussion Paper 1588.10.2139/ssrn.721907Search in Google Scholar

Cameron, C., and P.Trivedi. 2005. Microeconometrics: Methods and Applications. Cambridge: Cambridge University Press.10.1017/CBO9780511811241Search in Google Scholar

Cornwell, C., and W.Trumbull. 1994. “Estimating the Economic Model of Crime with Panel Data,” 76/2The Review of Economic and Statistics360–366.10.2307/2109893Search in Google Scholar

Deadman, D., and Z.MacDonald. 2004. “Offenders as Victims of Crime?: An Investigation into the Relationship between Criminal Behaviour and Victimization,” 167/1 Journal of Royal Statistical Society (Series A)53–67.10.1111/j.1467-985X.2004.00291.xSearch in Google Scholar

Ehrlich, I. 1973. “Participation in Illegitimate Activities: A Theoretical and Empirical Investigation,” 81/3The Journal of Political Economy521–565.10.1086/260058Search in Google Scholar

Entorf, H., and H.Spengler. 2000. “Socioeconomic and Demographic Factors of Crime in Germany: Evidence from Panel Data of the German States,” 20International Review of Law and Economics75–106.Search in Google Scholar

Fajnzylber, P., D.Lederman, and N.Loayza. 2002. “What Causes Violent Crime?” 46European Economic Review1323–1357.10.1016/S0014-2921(01)00096-4Search in Google Scholar

Farrington, D. P. 1999. “Measuring, Explaining and Prevailing Shoplifting: A Review of British Research,” 12Security Journal9–27.Search in Google Scholar

Farrington, D. P., and J. N.Burrows. 1992. “Criminal Career Research in the United Kingdom,” 32/4British Journal of Criminology521–536.10.1093/oxfordjournals.bjc.a048255Search in Google Scholar

Farrington, D. P. 1993. “Did Shoplifting Really Decrease?” 33British Journal of Criminology57–69.10.1093/oxfordjournals.bjc.a048290Search in Google Scholar

Flood-Page, C., S.Cambell, V.Harrington, and J.Miller. 2000. Youth Crime: Findings from the 1998/99 Youth Lifestyle Survey. London: Home Office Research Study, No. 209.Search in Google Scholar

Freeman, R. 1999. “The Economics of Crime,” in O. Ashenfelter and D. Card, eds. Handbook of Labour Economics, Amsterdam: North Holland, 3c. 3529–3571.Search in Google Scholar

Graham, J., and B.Bowling. 1995. Young People and Crime. London: Home Office.10.1037/e450582008-001Search in Google Scholar

Grasmick, H., and R.Bursik. 1990. “Conscience, Significant Others, and Rational Choice: Extending the Deterrence Model,” 24/3Law and Society Review887–861.10.2307/3053861Search in Google Scholar

Grasmick, H., R.Bursik., and D.Green. 1980. “Legal Punishment, Social Disapproval and Internalization as Inhibitors of Illegal Behavior,” 71Journal of Criminal Law & Criminology325–335.10.2307/1142704Search in Google Scholar

Greenberg, D. 1981. “Methodological Issues in Survey Research on Inhibition of Crime,” 72/3The Journal of Criminal Law and Criminology1094–1101.10.2307/1143277Search in Google Scholar

Hirschi, T., and M.Gottfredson. 1995. “Control-Theory and the Life-Course Perspective,” 4Studies on Crime Prevention131–142.Search in Google Scholar

Hirschi, T., and M.Gottfredson. 1983. “Age and the Explanation of Crime,” 89American Journal of Sociology552–584.10.1086/227905Search in Google Scholar

Inciadi, J. A. 1979. “Heroin Use and Street Crime,” 25Crime and Delinquency335–346.Search in Google Scholar

Inciadi, J. A. 1969. “Crime Doesn’t Pay: Correlates of Shared Misunderstanding,” 17Social Problems189–2001.Search in Google Scholar

Jensen, G., M.Erickson, and J.Gibbs. 1978. “Perceived Risk of Punishment and Self-Reported Delinquency,” 57/1Social Forces57–78.10.2307/2577626Search in Google Scholar

Kallis, M. J., and D. J.Vanier. 1985. “Consumer Shoplifting: Orientations and Deterrents,” 13Journal of Criminal Justice459–473.10.1016/0047-2352(85)90045-5Search in Google Scholar

Klemke, L. W. 1992. The Sociology of Shoplifting: Boosters and Snitches Today. Westport, CT: Praeger.Search in Google Scholar

Levitt, S. 1998a. “Juvenile Crime and Punishment,” 106/6The Journal of Political Economy1156–1185.10.1086/250043Search in Google Scholar

Levitt, S. 1998b. “Why Do Arrest Rates to Reduce Crime: Deterrence, Incapacitation, or Measurement Error?” 38Economic Inquiry353–372.Search in Google Scholar

Levitt, S. 1996. “The Effects of Prison Population Size on Crime Rates: Evidence from Prison Overcrowding Litigation,” 111/2 The Quarterly Journal of Economics320–351.10.2307/2946681Search in Google Scholar

Levitt, S. 2003. “Individual Perceptions of the Criminal Justice System”, NBER Working Paper 9474.Search in Google Scholar

Lochner, L. 2004. “Education, Work, and Crime: A Human Capital Approach,” NBER Working Paper 10478.10.3386/w10478Search in Google Scholar

Maddala, G. S. 1983. Limited-Dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press.10.1017/CBO9780511810176Search in Google Scholar

Maguire, M. 1994. “Crime Statistics, Patterns and Trends: Changing Perceptions and their Implications,” in M.Maguire, R.Morgan, and R.Reiner, eds. The Oxford Handbook of Criminology. Oxford: Clarendon Press, 233–291.Search in Google Scholar

McCarthy, B., and J.Hagan. 1991. “Homelessness: A Criminogenic Situation?” 31British Journal of Criminology393–410.10.1093/oxfordjournals.bjc.a048137Search in Google Scholar

McNeely, C. 1995. “Perceptions of the Criminal Justice System: Television Imagery and Public Knowledge in the United States,” 3/1Journal of Criminal Justice and Popular Culture1–20.Search in Google Scholar

McNess, M. P., D. S.Egli, R. S.Marshall, J. F.Schnelle, and T.Risley. 1976. “Shoplifting Prevention: Providing Information Through Signs,” 9Journal of Applied Behaviour Analysis399–405.10.1901/jaba.1976.9-399Search in Google Scholar

Osgood, W. D., P. M.O’Malley, G. G.Bechman, and L. D.Johnston. 1989. “Time Trends and Age Trends in Arrests and Self-Reported Illegal Behaviour,” 27/3Criminology380–415.Search in Google Scholar

Paternoster, R., L.Saltzman, and T.Chiricos. 1983. “Perceived Risk and Social Control: Do Sanctions Really Deter?” 17/3Law and Society Review457–479.10.2307/3053589Search in Google Scholar

Pogarsky, G., A.Piquero, and R.Paternoster. 2004. “Modelling Change in Perceptions about Sanctions Threats: The Neglected Linkage in Deterrence Theory,” 20/4Journal of Quantitative Criminology343–369.Search in Google Scholar

Pudney, S. 2003. “The Road to Ruin? Sequences of Initiation to Drug Use and Offending by Young People in Britain,” 113/486The Economic Journalc182-c198.Search in Google Scholar

Pudney, S. 2004. “Keeping Off the Grass? An Econometric Model of Cannabis Consumption in Britain,” 19Journal of Applied Econometrics435–453.10.1002/jae.746Search in Google Scholar

Pudney, S, and D.Deadman, and D.Pyle. 2000. “The Relationship between Crime, Punishment and Economic Conditions: Is Reliable Inference Possible When Crimes Are Under-Recorded?” 163/1Journal of the Royal Statistic Society Series A (Statistics in Society)81–97.Search in Google Scholar

Rosenbaum, P., and D.Rubin. 1983. “The Central Role of the Propensity Score in Observational Studies for Causal Effects,” 70Biometrica41–50.10.1093/biomet/70.1.41Search in Google Scholar

Sah, R. 1991. “Social Osmosis and Patterns of Crime,” 99/6The Journal of Political Economy1272–1295.10.1086/261800Search in Google Scholar

Sah, R. 2004. “Violent Crime in the United States of America: A Time-Series Analysis between 1960–2000,” 18European Journal of Law and Economics203–221.Search in Google Scholar

Sah, R. 2011. “Violent Crime and Incentives in the Long-Run: Evidence from England and Wales,” 38Journal of Applied Statistics647–660.Search in Google Scholar

Saridakis, G., and H.Spengler. 2012. “Crime, Deterrence and Unemployment in Greece: A Panel Data Approach,” 49The Social Science Journal167–174.10.1016/j.soscij.2011.08.005Search in Google Scholar

Speed, M., J.Burrows, and J.Bamfield. 1995. Retail Crime Costs 1993/94 Survey: The Impact of Crime and the Retail Response. London: British Retail Consortium.Search in Google Scholar

Stockwell, T., S.Donath, M.Cooper-Stanbury, T.Chikritzhs, P.Catelado, and C.Mateo. 2004. “Under-Reporting of Alcohol Consumption in Household Surveys: A Comparison of Quantity-Frequency, Graduated-Frequency and Recent Call,” 99Addiction1024–1033.10.1111/j.1360-0443.2004.00815.xSearch in Google Scholar

Stratford, N., and W.Roth. 1999. The 1998 Youth Lifestyle Survey Technical Report. London: National Centre for Social Research.Search in Google Scholar

Sutherland, E. H. 1942/1973. Revised edition “Development of the Theory,” in K.Schuessler, eds. Edwin Sutherland on Analysing Crime. Chicago, IL: Chicago University Press, 30–41.Search in Google Scholar

Tauchen, H., A.Witte, and H.Griesinger. 1994. “Criminal Deterrence: Revisiting the Issue with a Birth Cohort,” LXXVI/3The Review of Economic and Statistics399–412.10.2307/2109966Search in Google Scholar

Teevan, J.1975. “Perceptions of Punishment: Current Research,” in R.Henshel and A.Silverman, eds. Perception in Criminology. New York: Columbia University Press, 146–154.Search in Google Scholar

Teevan, J. 1976. “Subjective Perceptions of Deterrence,” 13Journal of Research in Crime and Delinquency155–164.Search in Google Scholar

Tittle, C. 1977. “Sanction Fear and the Maintenance of Social Order,” 55/3Social Forces579–596.10.2307/2577457Search in Google Scholar

Tonglet, M. 1998. “Consumers Perceptions of Shoplifting and Shoplifting Behaviour,” in M.Gill, ed. Crime at Work: Increasing the Risk for Offenders, Vol. II. Leicester: Perpetuity Press.Search in Google Scholar

Waldo, G., and T.Chiricos. 1972. “Perceived Penal Sanction and Self-Reported Criminality: A Neglected Approach to Deterrence Research,” Social Problems522–539.Search in Google Scholar

Weaver, F. M., and J. S.Carroll. 1985. “Crime Perceptions in a Natural Setting by Expert and Novice Shoplifters,” 48Social Psychology Quarterly349–359.10.2307/2786696Search in Google Scholar

Wilson, J. Q., and G. L.Kelling. 1982. “The Police and Neighbourhood Safety: Broken Windows,” 3 The Atlantic29–38.Search in Google Scholar

Witte, A. 1980. “Estimating the Economic Model of Crime and Individual Data,” 94Quarterly Journal of Economics59–87.10.2307/1884604Search in Google Scholar

  1. 1

    Empirical research in criminology suggests that shoplifters may be influenced by rational or utilitarian considerations (e.g. Kallis and Vanier, 1985; Weaver and Carroll, 1985; Farrington et al., 1993; McCarthy and Hagan, 1991; Tonglet, 1998; Farrington, 1999). However, these studies do not provide a detailed econometric analysis which allows for the estimation of the deterrence model, this is the key objective of this article.

  2. 2

    However, those who commit several undetected crimes may expect to receive more severe punishment, if they are caught for a crime and the previous events come to light. Therefore, the experiential effect may be more important for perceptions of punishment than severity (Greenberg, 1981).

  3. 3

    See the “broken windows” theory of Wilson and Kelling (1982).

  4. 4

    If the individual has a prior distribution of values for π, then π0 represents its mean. These prior beliefs come from a range of sources including news and entertainment media (see McNeely, 1995) and the views and experience of acquaintances.

  5. 5

    For sample omissions, see Flood-Page et al. (2000).

  6. 6

    I could have made use of the Offending, Crime and Justice Survey (OC&JS), but this does not include questions which make use of measures of the risk of legal penalties as perceived by individuals if shoplifting were committed. That said, it is clear that both the 2003 OC&JS and the 1998 YLS are broadly comparable. For instance, focusing on the offence of shoplifting I obtained admission rates for shoplifting between the ages 12 and 30 of 20.83% (std. err. 0.75) and 17.54% (std. err. 0.72) for the YLS and OC&JS, respectively (weighted estimates). Equally, the mean age for shoplifting was found to be 21.78 (std. err. 0.23) and 21.72 (std. err. 0.24) for the two surveys. Finally, 59.45% (std. err. 2.08) of the offenders were found to be males with mean age 21.94 (std. err. 0.29) in the YLS, whilst a comparable number of males (59.57% (std. err. 2.18)) were shoplifters (mean age 22.19 (std. err. 0.33)) in OC&JS. The OC&JS is obviously a valuable source of information on crime, but given that it does not explicitly allow for the investigation of the deterrence hypothesis.

  7. 7

    Strategies adopted to ensure confidentiality among respondents with reading difficulties are reported in Stratford and Roth (1999).

  8. 8

    I have also examined the association of perceptions and age. About 50% of individuals aged below 21 with a little offending experience (naïve or non-offenders) reported that it was “very” or “quite” likely to be caught. However, only 25% of experienced offenders reported high probability of arrest. For those aged above 21, perceptions remain almost unaffected by additional offending experience. The analysis is repeated for perceived cost. A high perceived cost of offending was reported across all age groups.

  9. 9

    In attempting to give some quantitative meaning to the YLS qualitative responses ranging from “very likely” to “not at all likely” to questions about the risk of being caught, I used the OC&JS. Although the OC&JS does not include questions about the perceived risk of being caught for shoplifting, it does include questions which call for a quantitative answer to the chance of being arrested for burglary and motor vehicle theft. By using the corresponding quintile points from the distribution of responses to OC&JS questions on the risk of being arrested, I found that “very likely”, “quite likely”, “not very likely” and “not at all likely” responses given for category (A) of Table 2 represent approximately a subjective risk of “0.45 and over”, “0.30–0.45”, “0.20–0.30” and “below 0.20”, respectively.

  10. 10

    Some economists have explained the nature of this relationship using a human capital approach (Lochner, 2004). Of course, this is not the only explanation. Others stress biological development, changes in social status and networks through which age may affect decision making process (e.g. Hirschi and Gottfredson, 1983, 1995).

  11. 11

    The Wald test suggests a decisive rejection of the joint hypothesis that the coefficients of the deterrence in male (χ2(2) = 8.56) and female (χ2(2) = 7.93) equations are zero.

  12. 12

    A joint test of zero restrictions on the coefficients of deterrence variables suggests that the null hypothesis of zero coefficients cannot be rejected (χ2(2) = 2.46).

  13. 13

    2 Ordered probit analysis for males and females also provides similar findings to those reported using simple probit. For the male equation, the coefficient of perceived risk of arrest was –0.295 (std. err. 0.108), and the coefficient of employment consequences was –0.151 (std. err. 0.108). For the female equation, the coefficient of perceived risk of arrest and the coefficient of employment consequences were –0.076 (std. err. 0.105) and –0.377 (std. err. 0.117). In both models, the deterrence coefficients found to be jointly statistically significant (for the male and female equations, the joint test for zero restrictions had the values χ2(2) = 10.82 and χ2(2) = 11.25, respectively).

  14. 14

    When the Wald test was performed for the exclusion of the deterrence variables, only the coefficients of the perceived risk of arrest were found to be jointly statistically significant in both Models 2 and 3 for males (χ2(3) = 9.50 and χ2(3) = 9.94, respectively).

  15. 15

    Probit analysis gives similar results. One of the major drawback of the data, however, is that the indicators of perceptions are ordinal and not in a numerical scale.

  16. 16

    Ordered probit models of the risk and anticipated employment consequences of being caught for shoplifting have been also estimated for different sub-samples. Some main differences from the estimates of the whole sample were: in the ordered probit model of the perceived risk of arrest the coefficient of police performance found to be positive and statistically significant for those who are currently at school. When the sample split according to gender, I found that among males, those who have shoplifted more than three times are less likely to report a high probability of arrest. Order probit estimates of the reported current perception of the anticipated employment consequences of being arrested show that the crime variables were only statistically significant for the sub-samples of females and those who are still at school. Being arrested or taken to court in the last 12 months was found to have a significant effect on the reported perception of future employment consequences.

  17. 17

    Social learning theory (Sutherland, 1942/1973), for example, stresses the use of peer and family variables in the crime equation. Interestingly, in a recent study by Pogarsky et al. (2004), it was suggested that arrest and peer offending are more consistently correlated with the change in individuals’ perceptions than with the decision to commit crime.

  18. 18

    The probit model provides very similar results.

  19. 19

    The sample was split into six blocks of propensity scores. This number of blocks ensures that the mean propensity score is not different from treated and controls in each block.

  20. 20

    It should be mentioned that the propensity score matching has been restricted to the common support region implying that the test of the balancing property is performed only to observations whose propensity score belongs to the intersection of the supports of the propensity score of treated and controls. This may improve the quality of the matches used to estimate the ATT (see Becker and Ichino, 2002). The region of common support region is [0.148, 0.623]. The restriction does not reduce the original sample significantly. The size of the control group drops from 988 to 985.

Received: 2012-12-26
Accepted: 2013-8-18
Published Online: 2013-9-26

©2013 by Walter de Gruyter Berlin / Boston

Articles in the same Issue

  1. Frontmatter
  3. The Problem with the Holdout Problem
  4. Do Warrants Matter?
  5. Shop Crime and Deterrence: Evidence on Shoplifting among Young People in the Youth Lifestyle Survey (YLS)
  6. Environmental Regulation and Civil Liability Under Causal Uncertainty: An Empirical Study of the French Legal System
  7. Equilibrium and Welfare in a Model of Torts with Industry Reputation Effects
https://doi.org/10.1515/rle-2012-0018
Keywords for this article
crime; deterrence; shoplifting

Articles in the same Issue

  1. Frontmatter
  3. The Problem with the Holdout Problem
  4. Do Warrants Matter?
  5. Shop Crime and Deterrence: Evidence on Shoplifting among Young People in the Youth Lifestyle Survey (YLS)
  6. Environmental Regulation and Civil Liability Under Causal Uncertainty: An Empirical Study of the French Legal System
  7. Equilibrium and Welfare in a Model of Torts with Industry Reputation Effects
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