This paper uses a Bayesian Structural Vector Autoregressive (BSVAR) framework to estimate the pass-through of unexpected gas price supply shocks on HICP inflation in the euro area and its four largest economies. In comparison to oil price shocks, gas price shocks have approximately one-third...

Abstract Operating on electricity markets requires accurately identifying, quantifying, and measuring risk coupled with their corresponding return: this appears as a crucial point, particularly during and after the COVID-19 pandemic. The aim of the present paper is twofold. First, we propose a...

Different types of natural events hit the United States every year. The data of natural hazards from 1900 to 2016 in the US shows that there is an increasing trend in annul natural disaster losses after 1980. Climate change is recognized as one of the factors causing this trend, and predictive...

A Bayesian dynamic compositional model is introduced that can deal with combining a large set of predictive densities. It extends the mixture of experts and the smoothly mixing regression models by allowing for combination weight dependence across models and time. A compositional model with...