A particular robust regression estimator has gained popularity among applied econometricians. We show that this estimator is inconsistent for the parameters of the conditional mean when the errors are skewed and heteroskedastic, and conclude that therefore its use cannot be generally recommended.

The use of robust regression estimators has gained popularity among applied econometricians. The main argument invoked to justify the use of the robust estimators is that they provide efficiency gains in the presence of outliers or non-normal errors. Unfortunately, most practitioners seem to be...

This fascinating and highly relevant book facilitates discussion on the difficult technical, legal and economic issues with respect to innovation, competition and welfare raised, through the span of more than a decade, by the US and EC Microsoft antitrust cases. It assesses their impact on the...

Understanding and quantifying the determinants of the number of sectors or firms exporting in a given country is of relevance for the assessment of trade policies. Estimation of models for the number of exporting sectors, however, poses a challenge because the dependent variable has both a lower...

In this note, we argue that tests of overidentifying restrictions give little information on the validity of the moment conditions implied by the underlying economic model, and therefore are mute about the possibility of identifying the parameters of interest.

We highlight a subtle identification problem that afflicts models for non-negative data in which the conditional expectation is specified as the product of a logit and an exponential function. The results are illustrated with an empirical model for medical expenditures.

This paper develops a count data model for credit scoring which allows the estimation of default probabilities using incomplete contracts data. The main advantage of the proposed approach is that it permits a more efficient use of the data, including that for the most recent clients. Moreover,...

We note that the existence of the maximum likelihood estimates in Poisson regression depends on the data configuration, and propose a strategy to identify the existence of the problem and to single out the regressors causing it.