Monetary Policy & Anchored Expectations - An Endogenous Gain Learning Model
This paper analyzes monetary policy in a model with a potential unanchoring of inflation expectations. The degree of unanchoring is given by how sensitively the public's long-run inflation expectations respond to inflation surprises. I find that optimal policy moves the interest rate aggressively when expectations unanchor, allowing the central bank to accommodate inflation fluctuations when expectations are well-anchored. Furthermore, I estimate the model-implied relationship that determines the extent of unanchoring. The data suggest that the expectations process is nonlinear and asymmetric: expectations respond more sensitively to large or downside surprises than to smaller or upside ones.
VMACS 2021 talk (10 minutes)
NBER Inflation Expectations 2022 talk (with discussion by Karthik Sastry, available until June 2022)
NBER Summer Institute 2022, Behavioral Macro Workshop talk (30 minutes, starting at 6:00:30, with discussion by Bruce Preston, available until August 2022)
Monetary Communication Rules
(with Amy Handlan)
Is there a systematic mapping between the Federal Reserve's expectations of macro variables and the words it uses to talk about the economy? We propose a simple framework that allows us to estimate communication rules in the United States based on text analysis with 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 or with the introduction of a new Fed chair. In the case of the fed funds rate, we also estimate the market's perception of the Fed's communication rule and use it to investigate how much of the disagreement between the market and the Fed come from disagreement about the communication rule.
Investment and Communication Technologies and Medium-Run Fluctuations
(with Marco Brianti)
Talking Over Time - Dynamic Central Bank Communication
Journal of Money, Credit & Banking
Work in Progress
Reputation for Competence
(with Amy Handlan)
The Feeling of the Age: A Quantitative Analysis of the Correlation between Novelistic and Economic Sentiment
(with literature scholar Daniella Gáti)
What predictive information do works of fiction contain for long-run economic fluctuations? We investigate this question in a two-step procedure. First, we conduct a sentiment analysis of prize-winning novels of the Pulitzer, National Book Award, PEN Faulkner, PEN Hemingway and Book Critics Circle awards from the years 1948-2018. We assign the novels quantitative sentiment scores. Second, we explore the correlation between the sentiment scores and macroeconomic aggregates such as GDP, total factor productivity, R&D expenditures, and so on. Once we have identified the frequencies where most of the comovement occurs via frequency domain methods, we analyze the cointegration relationships and the effects of innovations to literary sentiment using a structural Vector Error Correction model (VECM).
Do Long-Horizon Expectations Matter for New Keynesian Models?
In the literature on New Keynesian (NK) models with statistical learning, common practice is to write down the log-linearized first order conditions of the NK model and replace the objective with a subjective expectations operator ("Euler-equation approach"). An alternative approach following Preston (2005) involves obtaining model equations in which long-horizon expectations are explicitly spelled out ("long-horizon approach"). I investigate numerically what implications the two approaches have for model dynamics. While both lead to oscillatory impulse responses, the long-horizon approach results in much more volatility because the term structure of interest rate expectations, absent in Euler-equation learning, responds very sensitively to shocks.