Classical regression analysis uses partial coefficients to measure the influences of some variables (regressors) on another variable (regressand). However, a descriptive point of view shows that these coefficients are very bad measures of influence. Their interpretation as an average change of...

Explained variance (R^2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models we consider in this paper are characterized by hierarchical data structures in which individuals are grouped into...

The least-absolute-deviations (LAD) estimator for a median- regression model does not satisfy the standard conditions for obtaining asymptotic refinements through use of the bootstrap because the LAD objective function is not smooth. This paper overcomes this problem by smoothing the objective...

This working paper aims to stress the role of the institutional capital and its components, as primary factors, in economic results at the national level, using adequate measurement indicators and econometric models. For this purpose, we analysed the following aspects: the definition of...

This working paper aims to stress the role of the institutional capital and its components, as primary factors, in economic results at the national level, using adequate measurement indicators and econometric models. For this purpose, we analysed the following aspects: the definition of...

Multiple regression is frequently used across the various social sciences to analyze cross-sectional data. However, it can often times be challenging to justify the assumption of common regression coefficients across all respondents. This manuscript presents a heterogeneous Bayesian regression...

In this paper we propose a method for estimating and conducting inference on categorical effects of random variables that are characterize by more that two categories. We focus on a class of parametric asymptotically normal estimators in deriving the the properties which allows for inference on...

In this paper we consider the problem of interpreting the signs of the estimated coefficients in multivariate time series regressions where the regressors are correlated. Using a continuous time model, we argue that focusing on the signs of individual coefficients in such regressions could be...

In this supplemental article, we introduce some useful results in spectral theory and perturbation theory. Some of the results are well-established. We briefly review them for the purpose of easy reference. We derive a novel bound for the perturbation of eigenprojections, which plays a key role...