This paper proposes a novel instrumental variable method for program evaluation that only requires a single cross-section of data on the spatial intensity of programs and outcomes. The instruments are derived from a simple theoretical model of government decision-making in which governments are...

We consider taxation by a utilitarian government in the presence of heterogeneous locations within a country. We show that a utilitarian government never equalizes after-tax incomes, even when it can impose group-specific lump-sum taxes. If migration is impossible, a utilitarian government may...

This paper analyses the impact of European Union (EU) funds on the performance of private firms. In particular, we examine a quasi-natural experiment consisting of a redrawing of administrative areas that expanded regional eligibility and led to a sudden increase in accessibility to EU grants...

This paper proposes a new approach to identify the wage effects of training. The idea is to narrow down the comparison group by only taking into consideration the workers who wanted to participate in training but did not do so because of some random event. The point estimate of the return to...

A large part of the recent literature on program evaluation has focused on estimation of the average effect of the treatment under assumptions of unconfoundedness or ignorability following the seminal work by Rubin (1974) and Rosenbaum and Rubin (1983). In many cases however, researchers are...

This paper develops a partial equilibrium model to account for stylized facts about the behavior of oligarchs, politically and economically strong conglomerates in transition and developing countries. The model predicts that oligarchs are more likely than other owners to invest in productivity...

Currently available asymptotic results in the literature suggest that matching estimators have higher variance than reweighting estimators. The extant literature comparing the finite sample properties of matching to specific reweighting estimators, however, has concluded that reweighting...

I demonstrate that Ai and Norton's (2003) point about cross differences is not relevant for the estimation of the treatment effect in nonlinear difference-in-differences models such as probit, logit or tobit, because the cross difference is not equal to the treatment effect, which is the...

An important goal when analyzing the causal effect of a treatment on an outcome is to understand the mechanisms through which the treatment causally works. We define a causal mechanism effect of a treatment and the causal effect net of that mechanism using the potential outcomes framework. These...