Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The article by Zellner and Ando proposes methods for coping with the excess kurtosis that is often observed in disturbances in applications of the seemingly unrelated regressions (SUR) model. This is an important topic which is of particular relevance in forecasting. However, the proposed methods do not address the problem: the direct Monte Carlo (DMC) algorithm is incorrect and the proposed variant of the Student-t distribution cannot account for thick tails in the distribution of disturbances in the SUR model.