On December 16th of 2015, the Fed initiated "liftoff," raising the federal funds rate range by 25 basis points and ending a 7-year regime of near-zero rates. We use a unique dataset of 640,000 loan-hour observations to measure the impact of liftoff on interest rates in the peer-to-peer lending...

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...

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...

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 assess the impact of large-scale asset purchases, commonly known as quantitative easing (QE), conducted by Sveriges Riksbank and the European Central Bank (ECB) on bond risk premia in the Swedish government bond market. Using a novel arbitrage-free dynamic term structure model of nominal and...

This paper introduces a novel database of text features extracted from the speeches of 53 central banks from 1996 to 2023 using state-of-the-art NLP methods. We establish four facts: (1) central banks with floating and pegged exchange rates communicate differently, and these differences are...

Central banks have been considering the introduction of central bank digital currencies (CBDCs). The theoretical literature indicates that this may influence private banks' lending activity and their profitability with implications for financial stability. To provide empirical evidence on this...

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...

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...