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

Using a sample of 2,789 Swedish residents on working age, this paper analyzes long-term absences from work due to sickness. The database contains all compensated sickness spells in the period January 1986 to December 1991. Earlier studies of work absence due to sickness did not analyze multiple...

The goal of this paper is to analyze short term-absences from work (i.e., periods of seven days or less) in Sweden during a period with two different reforms. As a theoretical model we use a utility-maximization framework with two restrictions (time and budget constraints). Using multiple spell...

Using a longitudinal data for about 1800 persons observed between 1986 and 1991, this study investigates the incentive effects on short-term sickness spells of two important regime changes in the social insurance system in Sweden implemented in 1987 and 1991. The results indicate that the rules...

Welfare persistence is estimated in and compared between Swedish-born and foreignborn households. This is done within the framework of a time-stationary dynamic discrete choice model controlling for the initial condition and unobserved heterogeneity. Three different types of persistence are...

Several studies have examined the effects of training programs on employment. Most of them assume that the effects of training are constant for all potential trainees. We use an econometric framework that allows studying the heterogeneous training effects on discrete outcomes. The treatment...

Long-term absenteeism due to sickness has been increasing in the past two decades. This has raised many questions about causes, financing, and policy measures to prevent further increases. Answering these questions is even more important in a society with an aging population, which is expected...

Matching estimators use observed variables to adjust for differences between groups to eliminate sample selection bias. When minimum relevant information is not available, matching estimates are biased. If access to data on usually unobserved factors that determine the selection process is...