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Koopman, Siem Jan
Lucas, André
Ooms, Marius
van Montfort, Kees
van der Geest, Victor
Year of Publication: 
Series/Report no.: 
Tinbergen Institute Discussion Paper 07-027/4
We model panel data of crime careers of juveniles from a Dutch Judicial Juvenile Institution. The data are decomposed into a systematic and an individual-specific component, of which the systematic component reflects the general time-varying conditions including the criminological climate. Within a model-based analysis, we treat (1) shared effects of each group with the same systematic conditions, (2) strongly non-Gaussian features of the individual time series, (3) unobserved common systematic conditions, (4) changing recidivism probabilities in continuous time, (5) missing observations. We adopt a non-Gaussian multivariate state space model that deals with all of these issues simultaneously. The parameters of the model are estimated by Monte Carlo maximum likelihood methods. This paper illustrates the methods empirically. We compare continuous-time trends and standard discrete-time stochastic trend specifications. We find interesting common time-variation in the recidivism behavior of the juveniles during a period of 13 years, while taking account of significant heterogeneity determined by personality characteristics and initial crime records.
non-Gaussian state space modeling
nonlinear panel data model
binomial time series
recidivism behavior
continuous time modelling
Document Type: 
Working Paper

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