A competing risks model is a model for multiple durations that start at the same point of time for a given subject, where the subject is observed until the first duration is completed and one also observes which of the durations is completed first. This article gives an overview of the main...

This paper uses data from an Internet-based CV database to investigate how factors which may be used as a basis for discrimination, such as the searchers' ethnicity, gender, age and employment status, affect the number of contacts they receive from firms. Since we have access to essentially the...

Often, a treatment and the outcome of interest are characterized by the moment they occur, and these moments are realizations of stochastic processes with dependent unobserved determinants. We develop a simple and intuitive method for inference on the treatment effect. The method can be...

Regression models for proportions are frequently encountered in applied work. The conditional expectation is bound between 0 and 1 and, therefore, must be non-linear which requires non-standard panel data extensions. The quasi-maximum likelihood estimator of Papke and Wooldridge (1996) suffers...

Regression models for proportions are frequently encountered in applied work. The conditional expectation function is bounded between 0 and 1 and therefore must be non-linear, requiring nonstandard panel data extensions. One possible approach is the binomial panel logit model with fixed effects...

This paper considers nonparametric identification of nonlinear dynamic models for panel data with unobserved voariates. Including such unobserved covariates may control for both the individual-specific unobserved heterogeneity and the endogeneity of the explanatory variables. Without specifying...

This paper analyzes the effects of starting the sick leave on part-time compared to fulltime on the probability to recover (i.e., return to work with full recovery of lost work capacity). Using a discrete choice one-factor model, we estimate mean treatment parameters and distributional treatment...

This paper presents an econometric framework for analyzing part-time sick leave as a treatment method. We exemplify how the discrete choice one-factor model can address the importance of controlling for unobserved heterogeneity in understanding the selection into part-time/full-time sick leave...

This paper analyzes the impact of the definition of part-time sick leave (PTSL) when analyzing the effect of PTSL on employees' probability to fully recover lost work capacity. Using a random sample of 3,607 employees, we estimate an econometric model that aims to answer the hypothetical...

Using a discrete choice one-factor model, we estimate mean treatment parameters and distributional treatment parameters to analyze the effects of degree of sick leave on the probability of full recovery of lost work capacity for employed and unemployed individuals, respectively. Our results...