We measure the economic risk of epidemics at a geo-spatially detailed resolution. In addition to data about the …’s resilience (its ability of the recover rapidly from the shock). We find that the economic risk of epidemics is particularly high …

significantly from normality. Even though the Shannon entropy is more inclusive of different facets of a forecast density, we find …

the period 1972:1-2014:12 to forecasts our tail risk indicators with each model in pseudo-real time. Our key finding is …

The measurement of health inequalities usually involves either estimating the concentration of health outcomes using an …

We examine how the tail risk of currency returns over the past 20 years were impacted by central bank (monetary and … effects last for up to 1 month, and are proportionally higher for joint QE actions. This cross-border source of tail risk is …

market outcomes, we apply a regression-adjusted matched difference-in-differences approach with entropy balancing to account … risk of unemployment two years after the treatment. However, the effects are heterogeneous as to gender, age, education …

face lower relocation costs than NEs, which enhances their bargaining position. Using French firm-level data and entropy …

We measure the economic risk of COVID-19 at a geo-spatially detailed resolution. In addition to data about the current … prevalence of confirmed cases, we use data from 2014-2018 and a conceptual disaster risk model to compute measures for exposure ….e., its ability of the recover rapidly from the shock). We find that the economic risk of this pandemic is particularly high …

We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high … EV models, especially in the developed markets. -- value at risk ; expected shortfall ; hybrid historical simulation … ; extreme value theory ; bootstrapping …