Abadie and Imbens (2008, Econometrica) showed that classical bootstrap schemes fail to provide correct inference for K-nearest neighbour (KNN) matching estimators of average causal effects. This is an interesting result showing that bootstrap should not be applied without theoretical...

This paper studies the cross-border health and productivity effects of alcohol taxes. We estimate the effect of a large cut in the Finnish alcohol tax on mortality, alcohol related illnesses and work absenteeism in Sweden. This tax cut led to large differences in the prices of alcoholic...

This paper estimates the effects of early interventions in the Swedish sickness insurance system. The aim of the interventions is to screen and, further to, rehabilitate sick listed individuals. We find that the early interventions - in contrast to what is expected - increase the inflow into...

We study the recruitment behavior of Swedish employers using data from a stated choice experiment. In the experiment, the employers are first asked to describe an employee who recently and voluntarily left the firm, and then to choose between two hypothetical applicants to invite to a job...

The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption or on the availability of an instrument. When available, instruments may also be used to test for the unconfoundedness assumption (exogeneity of the...

This paper examines the effect of income inequality on health for a group of particularly disadvantaged individuals: refugees. Our analysis draws on longitudinal hospitalization records coupled with a settlement policy where Swedish authorities assigned newly arrived refugees to their first area...

This paper studies empirically the consequences of retirement on health. We make use of a targeted retirement offer to army employees 55 years of age or older. Before the offer was implemented in the Swedish defense, the normal retirement age was 60 years of age. Estimating the effect of the...

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that the duration framework in discrete time provides a fertile ground for effect evaluations. We suggest easy-to-use nonparametric survival function...

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified....

We show that the main nonparametric identification finding of Abbring and Van den Berg (2003b, Econometrica) for the effect of a timing-chosen treatment on an event duration of interest does not hold. The main problem is that the identification is based on the competing-risks identification...