The law enforcement administrative data for analyses based on statistical time series models: example of drug policies

Criminologists try to understand the nature of various changes, such as what leads to changes in crime. One of the shortcomings of criminology, especially in a Czech context, is the underdeveloped field of statistical modeling based on time-specific information. The aim of this article is to discuss the possibilities and limits of administrative data in the field of law enforcement while applying statistical models using time-specific information. Selected methods based on the use of data containing time-specific information, through the application of time series analysis, are presented: ARIMA models and structural change models. Furthermore, examples of such analyses are provided and a theoretical framework which facilitates the use of time series models is outlined. In addition, the availability of the data needed for such analyses is assessed.

law enforcement; time series; ARIMA; structural change; longitudinal analysis; administrative data; drug policy; crime

Benjamin Petruželka



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