Estimating systematic continuous‐time trends in recidivism using a non‐Gaussian panel data model

Siem Jan Koopman, Marius Ooms, Andre Lucas, Kees van Montfort and Victor Van Der Geest

Statistica Neerlandica, 2008, vol. 62, issue 1, 104-130

Abstract: 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 and (5) missing observations. We adopt a non‐Gaussian multivariate state‐space model that deals with all 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 behaviour of the juveniles during a period of 13 years, while taking account of significant heterogeneity determined by personality characteristics and initial crime records.

Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9574.2007.00375.x

Related works:
Working Paper: Estimating Systematic Continuous-time Trends in Recidivism using a Non-Gaussian Panel Data Model (2007)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:stanee:v:62:y:2008:i:1:p:104-130

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0039-0402

Access Statistics for this article

Statistica Neerlandica is currently edited by Miroslav Ristic, Marijtje van Duijn and Nan van Geloven

More articles in Statistica Neerlandica from Netherlands Society for Statistics and Operations Research
Bibliographic data for series maintained by Wiley Content Delivery ().