During the last decade, economists have intensively searched for evidence on the importance of the Balassa-Samuelson (B-S) hypothesis in explaining nominal convergence. One general result is that B-S can at best explain only part of the excess inflation observed in the European catching-up...

Contrary to most existing studies of the literature that assumed that the effects of real exchange rate (RE) misalignment on trade flows are symmetric, this paper considers a more general and realistic framework allowing for possible asymmetric effects. We use monthly time-series data over the...

Researchers in economics and other disciplines are often interested in the causal effect of a binary treatment on outcomes. Econometric methods used to estimate such effects are divided into one of two strands depending on whether they require the conditional independence assumption (i.e.,...

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...

When a treatment unambiguously defines the treatment and control groups at a given time point, its effects are usually found by comparing the two groups' mean responses. But there are many cases where the treatment timing is chosen, for which the conventional approach fails.This paper sets up an...

This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design. The distributional impacts of social programs such as welfare, education, training programs and unemployment insurance are of large interest to economists. QTE are an...

Expansion of the public sector and redistributive policies may reduce income inequality, but formal tests suffer from the problem of endogeneity of government size with respect to the distribution of income. Studying 30 European countries over the period 2004-2015, we apply instrumental variable...

A key assumption in regression discontinuity analysis is that units cannot manipulate the value of their running variable in a way that guarantees or avoids assignment to the treatment. Standard identification arguments break down if this condition is violated. This paper shows that treatment...

This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non-response bias, using two instrumental variables. Making use of a discrete instrument for the treatment and a continuous instrument for...

This paper discusses the nonparametric identification of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the...