Parents invest in their children's human capital in several ways. We investigate the extent to which the levels and composition of parent-child time varies across countries with different welfare regimes: Finland, Germany and the United States. We test the hypothesis of parentchild time as a...

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,...

In the practice of program evaluation, choosing the covariates and the functional form of the propensity score is an important choice for estimating treatment effects. This paper proposes data-driven model selection and model averaging procedures that address this issue for the propensity score...

This paper studies (nonparametric) partial identification of treatment response with social interactions. It imposes conditions motivated by economic theory on the primitives of the model, that is, the structural equations, and shows that they imply shape restrictions on the distribution of...

We analyse all the major sources of direct and indirect R&D subsidies in Norway in the period 2002- 2013 and compare their effects on individual firms’ performance. Firms that received support are matched with a control group of firms that did not receive support using a combination of...

Previous studies on the value of terroir, or more generally geographical indications (GI), used hedonic techniques. We use historical data and exploit temporal and geographical variations in the introduction of wine GIs in early twentieth century France to study the impact on the price of...

Average treatment effects estimands can present significant bias under the presence of outliers. Moreover, outliers can be particularly hard to detect, creating bias and inconsistency in the semi-parametric ATE estimads. In this paper, we use Monte Carlo simulations to demonstrate that...

The assumption that the assignment to treatments is ignorable conditional on attributes plays an important role in the applied statistic and econometric evaluation literature. Another term for it is conditional independence assumption. This paper discusses identification when there are more than...

Traditional instrumental variable estimators do not generally estimate effects for the treated population but for the unobserved population of compliers. They do identify effects for the treated when there is one-sided perfect non-compliance. However, this property is lost when covariates are...

We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using...