Investors typically measure an asset’s potential to diversify a portfolio by its correlations with the portfolio’s other assets, but correlation is useful only if it provides a good estimate of how an asset’s returns co-occur cumulatively with the other asset returns over the investor’s...

The problem of multicollinearity in the assessments of coefficients is well established. However, it is rarely researched in the estimations of macroeconomic variables and economic performance of developing countries. Predicatively, it has impacts on the estimations of coefficients that should...

The data on JIFs provided by Thomson Scientific can only be considered as a sample since they do not cover the entire universe of those documents that cite an intellectual output (paper, article, etc) or are cited by others. Then, questions arise if the empirical distribution (best fit to the...

In this paper we use Monte Carlo simulation to investigate the impact of effect size heterogeneity on the results of a meta-analysis. Specifically, we address the small sample behaviour of the OLS, the fixed effects regression and the mixed effects meta-estimators under three alternative...

It is well known that several high-breakdown procedures can produce robust estimates of linear-regression coefficients despite substantial contamination in the data. In practice, however, the estimators’ robustness tends to be affected by the value of R2 in the uncontaminated part of the...

Motivated by Manski and Tamer (2002) and especially their partial identification analysis of the regression model where one covariate is only interval-measured, we present two extensions. Manski and Tamer (2002) propose two estimation approaches in this context, focussing on general results. The...

We reconsider the partial identification analysis of the regression model in Manski and Tamer (2002) where one covariate is only interval-measured and present two additional sets of results. Manski and Tamer (2002) propose two estimation approaches in this context, focussing on general results....

In this paper we describe some applications of the Random Recursive Partitioning (RRP) method. This method generates a proximity matrix which can be used in non parametric hot-deck missing data imputation, classification, prediction, average treatment effect estimation and, more generally, in...