• Graduate Programs
  • Research
  • Browse our Courses
  • Events
    • Events Calendar
    • Events Archive
    • Summer School
      • Applied Public Policy Evaluation
      • Deep Learning
      • Development Economics
      • Economics of Blockchain and Digital Currencies
      • Economics of Climate Change
      • The Economics of Crime
      • Foundations of Machine Learning with Applications in Python
      • From Preference to Choice: The Economic Theory of Decision-Making
      • Inequalities in Health and Healthcare
      • Marketing Research with Purpose
      • Markets with Frictions
      • Modern Toolbox for Spatial and Functional Data
      • Sustainable Finance
      • Tuition Fees and Payment
      • Business Data Science Summer School Program
    • Tinbergen Institute Lectures
    • 2026 Tinbergen Institute Opening Conference
    • Annual Tinbergen Institute Conference
  • News
  • Summer School
    • Applied Public Policy Evaluation
    • Deep Learning
    • Development Economics
    • Economics of Blockchain and Digital Currencies
    • Economics of Climate Change
    • The Economics of Crime
    • Foundations of Machine Learning with Applications in Python
    • From Preference to Choice: The Economic Theory of Decision-Making
    • Inequalities in Health and Healthcare
    • Marketing Research with Purpose
    • Markets with Frictions
    • Modern Toolbox for Spatial and Functional Data
    • Sustainable Finance
    • Tuition Fees and Payment
  • Alumni

Bernasco, W., de Graaff, T., Rouwendal, J. and Steenbeek, W. (2017). Social Interactions and Crime Revisited: An Investigation Using Individual Offender Data in Dutch Neighborhoods Review of Economics and Statistics, 99(4):622--636.


  • Journal
    Review of Economics and Statistics

Using data on the age, sex, ethnicity, and criminal involvement of more than 14 million residents of all ages residing in approximately 4,000 Dutch neighborhoods, we test if an individual's criminal involvement is affected by the proportion of criminals living in his or her residential neighborhood. We develop a binomial discrete choice model for criminal involvement and estimate it on individual data. We control for both the endogeneity that may be related to unobserved neighborhood characteristics and for sorting behavior. We find significant social interaction effects, but our findings do not imply multiple equilibria or large multiplier effects.