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...

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....

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that, without additional assumptions, it is not possible to estimate the average treatment effect and treatment on the treated. It is, however,...

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...

We test if social work norms are important for work absence due to self-perceived sick-ness. To this end, we use a randomized social experiment designed to estimate the effect of monitoring on work absence. The treated were exposed to less monitoring of their eligibility to use sickness...

The treatment effect of a Swedish employment subsidy is estimated using exact covariate-matching and instrumental variables methods. Our estimates suggest that the programme had a positive treatment effect for the participants. We also show how non-parametric methods can be used to estimate the...

Using both register and survey data, two types of labour market training programs are compared. One program is part of the regular Swedish labour market training and the other, Swit, was initiated as an experiment during a two-year period, in an attempt to solve a bottleneck problem with people...

We propose a general test for exogeneity that is robust against distributional misspecification. The test can also be used to identify other types of misspecifications, such as the presence of a random coefficient. The idea is to sort the data with respect to a variable (a sorting score) and...

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that, without additional assumptions, it is not possible to estimate the average treatment effect and treatment on the treated. It is, however,...