The term multi-valued treatment effects refers to a collection of population parameters capturing the impact of a treatment variable on an outcome variable when the treatment takes multiple values. For example, in labour training programmes participants receive different hours of training or in...

Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modeling of complex structural relationships. However, they are not commonly used in practice due to the need for exogenous variables with large support for...

Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modeling of complex structural relationships. However, they are not commonly used in practice due to the need for exogenous variables with large support for...

This paper studies three interrelated health care decisions: insurance, utilization, and expenditures. The model treats insurance as an endogenous variable with respect to both utilization and expenditures, addresses potential selection issues, and takes into account that the decisions to use...

En años recientes los métodos de evaluación de impacto se han difundido ampliamente en la investigación microeconómica aplicada. Sin embargo, la variedad de métodos responde a problemas particulares y específicos los cuales están determinados normalmente por los datos disponibles y el...

The aim of this book is to contribute to the debate on the continuity/fracture of regional patterns of development and employment in old and new European Union (EU) regions. Several contributions in this book suggest that a factor common to all backward regions, often neglected in the...

This paper discusses the solution of nonlinear integral equations with noisy integral kernels as they appear in nonparametric instrumental regression. We propose a regularized Newton-type iteration and establish convergence and convergence rate results. A particular emphasis is on instrumental...

I propose a nonparametric iid bootstrap that achieves asymptotic refinements for t tests and confidence intervals based on GMM estimators even when the model is misspecified. In addition, my bootstrap does not require recentering the moment function, which has been considered as critical for...

While estimates of models with spatial interaction are very sensitive to the choice of spatial weights, considerable uncertainty surrounds the definition of spatial weights in most studies with cross-section dependence. We show that, in the spatial error model, the spatial weights matrix is only...

In this paper bootstrap confidence bands are constructed for nonparametric quantile estimates of regression functions, where resampling is done from a suitably estimated empirical distribution function (edf) for residuals. It is known that the approximation error for the confidence band by the...