The wild bootstrap was originally developed for regression models with heteroskedasticity of unknown form. Over the past thirty years, it has been extended to models estimated by instrumental variables and maximum likelihood, and to ones where the error terms are (perhaps multi-way) clustered....

Currently there is little practical advice on which treatment effect estimator to use when trying to adjust for observable differences. A recent suggestion is to compare the performance of estimators in simulations that somehow mimic the empirical context. Two ways to run such "empirical Monte...

This paper develops a procedure for estimating parameters of a cross-sectional stochastic frontier production function when the factors of production suffer from measurement errors. Specifically, we use Fuller's (1987) reliability ratio concept to develop an estimator for the model in Aigner et...

This paper shows that the bootstrap algorithm for average technical efficiency by Atkinson and Wilson (1995) should be applied with great care for the Data Envelopment Analysis (DEA) estimator if the production frontier is stochastic. A stochastic frontier implies that the DEA estimator is...

Cet article illustre l’applicabilité des méthodes de rééchantillonnage dans le cadre des tests multiples (simultanés), pour divers problèmes économétriques. Les hypothèses simultanées sont une conséquence habituelle de la théorie économique, de sorte que le contrôle de la...

The detection of dangerous road sites is usually performed using empirical methods which focus on observed accident frequencies and/or proportions of accidents with a given feature. The most widely used detection tools have an empirical Bayes (EB) background. The EB approaches rely on the...

This paper is concerned with tests of restrictions on the sample path of conditional quantile processes. These tests are tantamount to assessments of lack of fit for models of conditional quantile functions or more generally as tests of how certain covariates affect the distribution of an...

A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are...

The purpose of this article is to analyze if spatial dependence is a synchronic effect in the first-order spatial autoregressive model, SAR(1). Spatial dependence can be not only contemporary but also time-lagged in many socio-economic phenomena. In this paper, we use three Moran-based...

Microaggregation is a set of procedures that distort empirical data in order to guarantee their facutal anonymity. At the same time the information content of data sets should not be reduced too much and should still be useful for scientific research. This paper investigates the effect of...