The aim of this study is to analyze and compare the results from Propensity Score Matching (PSM) and Spatial Hedonic Prices (SHP) methodologies estimating value fluctuations on residential proprieties in Bogotá (Colombia). Specifically, this study examines value fluctuations on residential...

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...

This research analyses the performance of Portuguese metros in the European context. By means of two non-parametric benchmarking techniques, respectively performance indicators and data envelopment analysis, we compute the efficiency of 37 European metros. In order to provide statistical...

We search for evidence against the hypothesis of a non-linear relationship between inflation and growth rates for 1993-2012 Peruvian data. A family of dichotomous models provide the way to model the relationship between the those two variables' cycles. Given the acceleration/de-acceleration...

The rank-ordered logit model's coefficients often vary significantly with the depth of rankings used in the estimation process. The common interpretation of the unstable coefficients across ranks is that survey respondents state their more and less preferred alternatives in an incoherent manner....

Most existing semi-parametric estimation procedures for binary choice models are based on the maximum score, maximum likelihood, or nonlinear least squares principles. These methods have two problems. They are difficult to compute and they may result in multiple local optima because they require...

In recent years, major advances have taken place in three areas of random utility modeling: (1) semiparametric estimation, (2) computational methods for multinomial probit models, and (3) computational methods for Bayesian stimation. This paper summarizes these developments and discusses their...

We propose a method to generate flexible mixture distributions that are useful for estimating models such as the mixed logit model using simulation. The method is easy to implement, yet it can approximate essentially any mixture distribution. We test it with good results in a simulation study...

The choice of a specific distribution for random parameters of discrete choice models is a critical issue in transportation analysis. Indeed, various pieces of research have demonstrated that an inappropriate choice of the distribution may lead to serious bias in model forecast and in the...

The aim of this paper is to analyse the role of unobserved heterogeneity in structural discrete choice models of labour supply for the evaluation of tax-reforms. Within this framework, unobserved heterogeneity has been estimated either parametrically or nonparametrically through random co-...