In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an...

I study the predictability of the EC’s merger decision procedure before and after the 2004 merger policy reform based on a dataset covering all affected markets of mergers with an official decision documented by DG Comp between 1990 and 2014. Using the highly flexible, non-parametric random...

Scholars and enforcement officials debate the merits and implications of “behavioral antitrust” — the application of empirical evidence showing how human behavior departs systematically and predictably from strict rationality (“bounded rationality”) to antitrust law. Notwithstanding...

In this note we develop principles for forecasting economies viewed as evolving networks formed by individuals acting on the basis of their psychology and social position following Markey-Towler (2016). We review the basic formal apparatus required to understand economies as such before using...