RESEARCH
Working Papers
Abstract: This paper shows that the wording of Federal Reserve communication affects expectations and other economic variables over and above the effects of setting the federal funds rate. Adapting neural network methods for text analysis from the computer science literature, I analyze how the wording in statements of the Federal Open Market Committee (FOMC) impacts fed funds futures (FFF) prices when these statements are announced. Using text analysis on FOMC statements and internal meeting materials, I create a new monetary policy “text shock” series for 2005-2014 that isolates the variation of FFF prices induced by the FOMC’s forward guidance, not their current assessment of the economy. I find that the wording of FOMC statements accounts for four times more variation in FFF prices than direct announcements of changes in the target federal funds rate. I also find that the impact of forward guidance on real interest rates is twice as large when using text shocks over other measures, like changes in FFF prices. Furthermore, the text shock produces responses in output and inflation that are qualitatively consistent with workhorse macroeconomic models, whereas changes in FFF prices do not.
Abstract: The Federal Open Market Committee (FOMC) claims that their post-meeting statements shift market expectations of future monetary policy. In this paper, I provide evidence supporting this claim. I apply a methodology from computational text analysis to produce a pairwise-statement similarity measure that compares wording between two FOMC statements. This similarity measure documents that FOMC statements have become more similar over time. With an event-study approach, I find that a decrease in the similarity of sequential FOMC statements is correlated with an increase the variation of federal funds rate expectations, calculated from high-frequency fed funds futures prices. This relationship persists even after controlling for changes in the target federal funds rate and Federal Reserve Chair. Standard monetary regressions omit any measure of policy statement texts and are thus biased. Adding the sequential statement similarity measure to a regression of federal funds rate expectations on the target rate accounts for 1.5 times the variation in market expectations. This paper suggests that more detailed text analysis on FOMC statements will improve modeling of monetary policy expectations.
NBER Monetary Economics Fall 2023 Workshop <YouTube Live Stream>
Abstract: Does the Federal Reserve follow a communication rule? We propose a simple framework to estimate communication rules, which we conceptualize as a systematic mapping between the Fed’s expectations of macroeconomic variables and the words they use to talk about the economy. Using text analysis and regularized regressions, we find strong evidence for systematic communication rules that vary over time, with changes in the rule often being associated with changes in the economic environment. We also find that shifts in communication rules increase disagreement among professional forecasters and correlate with monetary policy surprise measures. Our method is general and can be applied to investigate systematic communication in a wide variety of settings.
"Gender and Tone in Recorded Economics Presentations: Audio Analysis with Machine Learning," with Haoyu Sheng [Draft]
Abstract: This paper develops a replicable and scalable method for analyzing tone in economics seminars to study the relationship between speaker gender, age, and tone in both static and dynamic settings. We train a deep convolutional neural network on public audio data from the computer science literature to impute labels for gender, age, and multiple tones, like happy, neutral, angry, and fearful. We apply our trained algorithm to a topically representative sample of presentations from the 2022 NBER Summer Institute. Overall, our results highlight systematic differences in presentation dynamics by gender, field, and format. We find that female economists are more likely to speak in a positive tone and are less likely to be spoken to in a positive tone, even by other women. We find that male economists are significantly more likely to sound angry or stern compared to female economists. Despite finding that female and male presenters receive a similar number of interruptions and questions, we find slightly longer interruptions for female presenters. Our trained algorithm can be applied to other economics presentation recordings for continued analysis of seminar dynamics.
Work in Progress
"Reputation for Competence," with Laura Gáti
"Joint Taxation and Labor Supply," with Ross Batzer
"Labor Market Demand and Monetary Information Shocks," with Ross Batzer
"Historical Measures of Market Concentration," with Enrico Berkes, Carola Frydman, Jane Olmstead-Rumsey, and Dimitris Papanikolaou
Discussions
"ECB Communication and its Impact on Financial Markets," by Istrefi, Odendahl, & Sestieri - Central Bank Communications: Theory and Practice Conference 2024 (FRB Cleveland, OH)
"Estimating the Effects of Political Pressure on the Fed: A Narrative Approach with New Data," by Drechsel - NBER Monetary Economics Spring Workshop 2024 (Chicago, IL)
"Policymakers' Uncertainty," by Cieslak, Hansen, McMahon & Xiao - Western Finance Association 2023 (San Francisco, CA)