Sensitivity Analysis Through Mixed Gini and OLS Regressions

Abstract

About thirty years ago Edward Leamer criticized the credibility of empirical research in economics. Since then there were huge improvements in research design, data collection and econometric methodology. On the other hand, the huge increase in computing power has increased the number of instruments available for the use of the over-zealous researcher who wants to prove his point. I suggest developing the mixed Gini and Ordinary Least Squares regression. It enables unraveling, tracing and testing the role of several whimsical assumptions imposed on the data in regression analysis. Among those assumptions are the linearity assumption, the use of monotonic increasing transformations, and the symmetry between distributions that is imposed by the Pearson correlation coefficient. My conjecture is that the new technique will reduce drastically the number of results that are claimed to be supported by empirical proofs.