This survey provides an updated review of the empirical literature on the regional effects of monetary policy in economic activity by means of undertaking a threefold perspective. First, the main methodological dimensions of this literature are examined while pinpointing those modelling or methodological traits that constitute a source of diverging estimates and thereby produce inconclusive evidence. Secondly, the estimates yielded by the literature are summarized by carrying out a crossstudy analysis of the results for each monetary union. By drawing on empirical regularities that are robust across studies, the conclusiveness of the results is assessed, while those monetary unions for which conclusive evidence is still lacking are also identified. Lastly, the sources of regional heterogeneity identified by these studies are reviewed in order to shed some light on the linkage between monetary policy and territorial heterogeneity. As a result of this threefold perspective, this survey delivers overall structured conclusions and updated policy-relevant lessons. Moreover, various research gaps and emerging topics in the literature are also identified.

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In studies on the redistributive, vertical, and horizontal effects of health care financing, the sum of the contributions calculated for each financial instrument does not equal the total effects. As a consequence, the final calculations tend to be overestimated or underestimated. The solution proposed here involves the adaptation of the Shapley value to achieve additive results for all the effects and reveals the relative contributions of different instruments to the change of whole-system equity. An understanding of this change would help policy makers attain equitable health care financing. We test the method with the public finance and private payments of health care systems in Denmark and the Netherlands.

The aim of this work is to solve the problem of nonadditivity revealed by work that calculates the redistributive effects of the budget or public policies made up of different instruments of income or public spending. To do this, the authors use the Shapley value. This technique allows us to consistently, symmetrically, and directly decompose the redistributive effect and the vertical and horizontal effects. This method is consistent because the total effects can be explained by the sum of the individual contributions; it is symmetrical because it does not depend on the aggregation ranking of the instruments; and it is direct because each index can be calculated without the need to calculate the rest. The main result obtained for the case of taxes and social transfers in the United States is that previous calculations undervalued the redistributive effects and their vertical and horizontal components for taxes and transfers. Undervaluation is more important for taxes.

The evolution of the pandemic caused by COVID-19, its high reproductive number and the associated clinical needs, is overwhelming national health systems. We propose a method for predicting the number of deaths, and which will enable the health authorities of the countries involved to plan the resources needed to face the pandemic as many days in advance as possible. We employ OLS to perform the econometric estimation. Using RMSE, MSE, MAPE, and SMAPE forecast performance measures, we select the best lagged predictor of both dependent variables. Our objective is to estimate a leading indicator of clinical needs. Having a forecast model available several days in advance can enable governments to more effectively face the gap between needs and resources triggered by the outbreak and thus reduce the deaths caused by COVID-19.