Research

Abstract: Eurodollar futures were the bedrock for constructing high-frequency series of monetary policy surprises, so their discontinuation poses a challenge for the continued empirical study of monetary policy. We propose an approach for updating the series of Gürkaynak, Sack, and Swanson (2005) and Nakamura and Steinsson (2018) with SOFR futures in place of Eurodollar futures that is conceptually and materially consistent. We recommend using SOFR futures from January 2022 onward based on regulatory developments and trading volumes. The updated series suggest that surprises over the recent tightening cycle are larger in magnitude than those seen over the decade prior and restrictive on average.

• Article

• Data

Abstract: Different series of high-frequency monetary shocks can have a correlation coefficient as low as 0.5 and the same sign in only two-thirds of observations. Both data and methods drive these differences, which are starkest when the federal funds rate is at its effective lower bound. Methods that exploit the differential responsiveness of short- and long-term asset prices can incorporate additional information. After documenting differences in monetary shocks, we explore their consequence for inference. We find that empirical estimates of monetary policy transmission from local projections and VARs are less affected by shock choice than forecast revision specifications. 

• FEDS working paper

Abstract: We present an indicator of job loss derived from Twitter data, based on a fine-tuned neural network with transfer learning to classify if a tweet is job-loss related or not. We show that our Twitter-based measure of job loss is well-correlated with and predictive of other measures of unemployment available in the official statistics and with the added benefits of real-time availability and daily frequency. These findings are especially strong for the period of the Pandemic Recession, when our Twitter indicator continues to track job loss well but where other real-time measures like unemployment insurance claims provided an imperfect signal of job loss. Additionally, we find that our Twitter job loss indicator provides incremental information in predicting official unemployment flows in a given month beyond what weekly unemployment insurance claims offer.

• FEDS working paper