<Para ID="Par1">We provide a comprehensive overview of latent Markov (LM) models for the analysis of longitudinal categorical data. We illustrate the general version of the LM model which includes individual covariates, and several constrained versions. Constraints make the model more parsimonious and allow us...</para>

In the context of multilevel longitudinal data, where sample units are collected in clusters, an important aspect that should be accounted for is the unobserved heterogeneity between sample units and between clusters. For this aim we propose an approach based on nested hidden (latent) Markov...

(Spatial) panel data are routinely modelled in discrete time (DT). However, there are compelling arguments for continuous time (CT) modelling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an...

This paper analyzes patterns of regional labour market development in Germany over the period 2000-2003 by means of a spatial-dependence continuous-time model. (Spatial) panel data are routinely modelled in discrete time. However, there are compelling arguments for continuous time modelling of...

A behavioural model of crime is developed and applied to panel data on the number of crimes and clear-ups for the 53 police districts in Norway for the period 1970-78. Data on both total crime and on 12 different types of crime is employed. The model consists of behavioural relations of the...

(Spatial) panel data are routinely modelled in discrete time (DT). However, there are compelling arguments for continuous time (CT) modelling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an...

This discussion paper led to an article in <I>Geographical Analysis</I> (2012). Volume 44, issue 1, pages 29-46.<P> (Spatial) panel data are routinely modelled in discrete time (DT). However, there are compelling arguments for continuous time (CT) modelling of (spatial) panel data. Particularly, most...</p></i>

We develop a generalized dynamic factor model for panel data with the goal of estimating an unobserved index. While similar models have been developed in the literature of dynamic factor analysis, our contribution is threefold. First, contrary to simple dynamic factor analysis where multiple...

In this paper I develop an intertemporal discrete choice model of labor supply. The framework incorporates the nonlinearities in the household budget set and accounts for state dependence in labor supply. Based on panel data for Germany (SOEP), I estimate this model using a dynamic conditional...

In this paper I develop an intertemporal discrete choice model of female labor supply that allows to analyze state dependence and labor supply along the extensive and the intensive margin. Drawing on microsimulation the nonlinearities in the household budget set are captured and thus work...