Michele Modugno and Dino PalazzoThe equity market’s reaction to macroeconomic news is consistent with the propagation of news into the real economy. We embody all the macro news in an activity news index and a price news index that together explain 34% of the quarterly stock price returns variation.
Benjamin N. Dennis, Gurubala Kotta, and Caroline Conley NorrisThe correlation of the spatial distribution of banking exposures with changes in spatial patterns of economic activity (e.g., internal migration, changes in agglomeration patterns, climate change, etc.) may have financial stability implications. We therefore study the spatial distribution of large U.S. banks' commercial and industrial (C&I) lending portfolios.
Zach Modig, Hulusi Inanoglu, and David LynchUsing a novel data collection, we examine the impact of the Volcker Rule on trading revenue of the 21 largest U.S. trading firms during the 100 day stress period centered on the COVID-19 financial crisis.
Robin Braun, George Kapetanios, Massimiliano MarcellinoThis paper studies the estimation and inference of time-varying impulse response functions in structural vector autoregressions (SVARs) identified with external instruments. Building on kernel estimators that allow for nonparametric time variation, we derive the asymptotic distributions of the relevant quantities. Our estimators are simple and computationally trivial and allow for potentially weak instruments.
Robert Kelchen, Dubravka Ritter, and Douglas WebberIn this paper, we assemble the most comprehensive dataset to date on the characteristics of colleges and universities, including dates of operation, institutional setting, student body, staff, and finance data from 2002 to 2023. We provide an extensive description of what is known and unknown about closed colleges compared with institutions that did not close.
Diego Bonelli, Berardino Palazzo, Ram S. YamarthyUsing inflation swap prices, we study how changes in expected inflation affect firm-level credit spreads and equity returns, and uncover evidence of a time-varying inflation sensitivity.
Dobrislav Dobrev and Paweł J. SzerszeńReplacing faulty measurements with missing values can suppress outlier-induced distortions in state-space inference. We therefore put forward two complementary methods for enhanced outlier-robust filtering and forecasting: supervised missing data substitution (MD) upon exceeding a Huber threshold, and unsupervised missing data substitution via exogenous randomization (RMDX).
Mohammad R. Jahan-Parvar, Charles Knipp, and Paweł J. SzerszeńWe propose a generalized multivariate unobserved components model to decompose macroeconomic data into trend and cyclical components. We then forecast the series using Bayesian methods.
Matteo Barigozzi, Claudio Lissona, and Matteo LucianiWe measure the Euro Area (EA) output gap and potential output using a non-stationary dynamic factor model estimated on a large dataset of macroeconomic and financial variables. From 2012 to 2023, we estimate that the EA economy was tighter than the European Commission and the International Monetary Fund estimate, suggesting that the slow EA growth is the result of a potential output issue, not a business cycle issue.
Daniel Barth, Phillip J. Monin, Emil Siriwardane, and Adi SunderamSince 2013, large U.S. hedge fund advisers have been required to report risk exposures in their regulatory filings. Using these data, we first establish that managers’ perceptions of risk contain useful information that is not embedded in fund returns.
