Erik HeitfieldThis paper examines how model uncertainty affects the price of catastrophe risk insurance. We use unique data on expected loss rate projections from seven hurricane risk models approved by regulators for use in Florida property insurance rate setting to quantify model uncertainty.
Dario Caldara, Haroon Mumtaz, and Molin ZhongWe characterize asymmetric tail risk across over one hundred U.S. macroeconomic and financial variables using a dynamic factor model with stochastic volatility. The model unifies growth-at-risk, inflation-at-risk, and sectoral heterogeneity through common factors whose volatility responds endogenously to shocks, combined with heterogeneous factor loadings.
Ece Fisgin, Johannes Fleck, Keith RichardsWe show that the EU’s 2018 retaliation against US steel and aluminum tariffs targeted goods with low US import dependence and high substitutability. For the majority of tariffed goods, the US share of EU imports declined notably and remained below pre-2018 levels even after the retaliatory tariffs were lifted, reflecting asymmetric effects of tariffs on trade diversion.
Nils Gornemann, Eugenio Rojas, Felipe SaffieDoes global financial risk affect long-run growth? Using a panel state-space model for emerging and advanced small open economies, we measure the effects of U.S. monetary policy uncertainty shocks. A one-standard-deviation shock lowers the level of the stochastic trend in emerging markets by at least 25 basis points after three years, with little effect in advanced economies.
David Splinter and Jeff LarrimoreCirculation into and out of the top one percent is pronounced in the U.S. One third exit after a year and two-thirds exit after a decade. This mobility lowers top income shares when shifting from annual to multi-year income measures. Intragenerational mobility over two decades lowers recent top one percent fiscal income shares by over 10 percent. Two-decade mobility reduces top 0.1% shares by over 20 percent, top 0.01% shares by 30 percent, and top 0.001% shares by 40 percent.
Using regional data for 11 euro area countries from 1999 to 2023, instead of country-level data, we find that inflation still responds to economic slack, but this relationship is more modest and largely shaped by inflation expectations. This implies that traditional demand-side central bank policies may have limited direct effects on inflation, highlighting that anchoring expectations is essential for effective monetary policy transmission.
The post-pandemic inflation surge is often attributed to pent-up demand andopportunistic price hikes. In fact, it is better explained by the effects of theeconomy’s production network and “state-dependent” pricing, where firmschange prices optimally when the reward justifies the effort. Firms are tightlylinked through supply chains so a surge in prices upstream can triggersimultaneous repricing by many layers of firms downstream, fuelling broad-based inflation.
This paper examines the relevance of banks’ exposure to climate transition risk in the interbank lending market. Using transaction-level data on repo agreements, we first establish that banks with higher exposure to transition risk face significantly higher borrowing costs. This premium is a combination of a risk premium, compensating lenders for increased credit risk, and an inconvenience premium, reflecting the sustainability preferences of key dealer banks.
We use a novel data set containing all corporate loans throughout the Eurozone to document a series of novel stylized facts on the relationship between collateral and the probability of default. First, we show that the pervasive empirical finding that riskier borrowers pledge collateral is driven by economists’ informational disadvantage relative to banks. Accounting for time-varying bank- and firm-specific risk factors produces negative correlations consistent with theory. Second, the relationship between pledging collateral and the probability of default is non-linear.
We propose a robust semi-parametric framework for persistent time-varying extreme tail behavior, including extreme Value-at-Risk (VaR) and Expected Shortfall (ES). The framework builds on Extreme Value Theory and uses a conditional version of the Generalized Pareto Distribution (GPD) for peaks-over-threshold (POT) dynamics.
