Handbook of Quantitative Criminology

pp 353-374


Measurement Error in Criminal Justice Data

  • John PepperAffiliated withDepartment of Economics, University of Virginia
  • , Carol PetrieAffiliated withCommittee on Law and Justice, National Research Council
  • , Sean SullivanAffiliated withDepartment of Economics, University of Virginia

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While accurate data are critical in understanding crime and assessing criminal justice policy, data on crime and illicit activities are invariably measured with error. In this chapter, we illustrate and evaluate several examples of measurement error in criminal justice data. Errors are evidently pervasive, systematic, frequently related to behaviors and policies of interest, and unlikely to conform to convenient textbook assumptions. Using both convolution and mixing models of the measurement error generating process, we demonstrate the effects of data error on identification and statistical inference. Even small amounts of data error can have considerable consequences. Throughout this chapter, we emphasize the value of auxiliary data and reasonable assumptions in achieving informative inferences, but caution against reliance on strong and untenable assumptions about the error generating process.