To what extent can a central bank influence its own balance sheet credit risks during a financial crisis through unconventional monetary policy operations? To study this question we develop a risk measurement framework to infer the time-variation in portfolio credit risks at a high (weekly)...

A simple methodology is presented for modeling time variation in volatilities and other higher-order moments using a recursive updating scheme similar to the familiar RiskMetricsTM approach. We update parameters using the score of the forecasting distribution. This allows the parameter dynamics...

We develop a novel high-dimensional non-Gaussian modeling framework to infer measures of conditional and joint default risk for many financial sector firms. The model is based on a dynamic Generalized Hyperbolic Skewed-t block-equicorrelation copula with time-varying volatility and dependence...

Using a monthly panel dataset of individuals' debt composition including mortgage and nonmortgage consumer credit, we show that house price changes can explain a significant fraction of personal debt composition dynamics. We exploit the variation in local house price growth as shocks to...

We study the impact of trust on the expansion of online lending in the U.S. over the 2008-2016 period. Using data from the largest platform, we demonstrate that a misconduct-driven decline of trust in traditional banking is associated with a statistically and economically significant increase in...

On December 16th of 2015, the Fed initiated "liftoff", a critical step in the monetary normalization process. We use a unique panel dataset of 640,000 loan-hour observations to measure the impact of liftoff on interest rates, demand, and supply in the online primary market for uncollateralized...

We use text analysis and a novel dataset to measure the sentiment component of central bank communications in 23 countries over the 2002-2017 period. Our analysis yields three key results. First, using directed networks, we show that comovement in sentiment across central banks is not reducible...

We propose an empirical framework to assess the likelihood of joint and conditional sovereign default from observed CDS prices. Our model is based on a dynamic skewed-t distribution that captures all salient features of the data, including skewed and heavytailed changes in the price of CDS...

We propose a dynamic semi-parametric framework to study time variation in tail parameters. The framework builds on the Generalized Pareto Distribution (GPD) for modeling peaks over thresholds as in Extreme Value Theory, but casts the model in a conditional framework to allow for time-variation...

Using a novel rich dataset at the regional level, this paper provides new empirical evidence on the fiscal transmission mechanism in the Eurozone. Our baseline estimates reveal a government spending relative output multiplier of 2.9, an employment multiplier of 1.9, and a cost per job created of...