This paper discusses a tool for optimization of econometric models based on genetic algorithms. First, we briefly describe the concept of this optimization technique. Then, we explain the design of a specifically developed algorithm and apply it to a difficult econometric problem, the...

We consider inference in regression discontinuity designs when the running variable only takes a moderate number of distinct values. In particular, we study the common practice of using confidence intervals (CIs) based on standard errors that are clustered by the running variable. We derive...

The paper analyses how context and time dependent factors determine the impulse of R&D subsidies on firm behavior with respect to private R&D expenditures. Based on data from the German R&D survey, we combine propensity-score matching with a difference-in-difference-estimator in order to measure...

Recent advances in the econometric modelling of count data have often been based on the generalized method of moments (GMM). However, the two-step GMM procedure may perform poorly in small samples, and several empirical likelihood-based estimators have been suggested alternatively. In this paper...

El objetivo principal de este estudio consiste en analizar y comparar los resultados obtenidos mediantes Propensity Score Matching y un modelo de precios hedónico espaciales para estimar el cambio en el valor de la propiedad en Bogotá, cuando un predio se encuentra ubicado cerca a una...

We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed at high frequencies, such as cumulated trading volumes. We introduce a flexible point-mass...

This paper considers the identification and estimation of an extension of Roy's model (1951) of sectoral choice, which includes a non-pecuniary component in the selection equation and allows for uncertainty on potential earnings. We focus on the identification of the non-pecuniary component,...

We introduce an approach for semiparametric inference in dynamic binary choice models that does not impose distributional assumptions on the state variables unobserved by the econometrician. The proposed framework combines Bayesian inference with partial identification results. The method is...

This article is an empirical study of residential land values in the vicinity of the TransMilenio system (Bus Rapid Transit, BRT) in Bogota' (Colombia). The results have been established through impact evaluation by means of nonparameteric approaches (Propensity Score Matching, PSM) and...

The estimation of dynamic games is known to be a numerically challenging task. In this paper we propose an alternative class of asymptotic least squares estimators to Pesendorfer and Schmidt-Dengler's (2008), which includes several well known estimators in the literature as special cases. Our...