"Relative Price Shocks and Inflation," (revised: May 2026), with A. Wolman. Prepared for the Carnegie-Rochester-NYU Conference Series on Public Policy.
Inflation is determined by interaction between monetary policy and real factors, including shocks to supply and demand for different components of the consumption basket. We construct a 15-sector New Keynesian model with a production network and heterogeneity in price rigidity, in the volatility of sectoral shocks, and in the trend rates of productivity growth across sectors to quantify the contributions to inflation from sectoral supply and demand shocks, monetary policy shocks, and aggregate real shocks. The model is estimated by maximum likelihood on U.S. data from 1995 through 2019, when the policy regime appeared to be stable. We find that relative price shocks were major contributors to the inflation deviations from target and the inflation surge after the pandemic
"Membership Turnover and Policy Disagreement at the FOMC" (revised: July 2026), with A. Riboni. Revise and resubmit requested by AEJ: Macroeconomics.
The implications of turnover for decision-making by the Federal Open Market Committee are examined using a voting model where 1) the chair has agenda-setting powers but must secure the median's approval for her proposal to pass, and 2) the identity of the median changes over time due to voting-right rotation and partisan appointments. Estimation of the model by the simulated method of moments delivers estimates of the chair and median policy preferences along a dovish-hawkish scale and of their disagreement, which is shown to forecast future dissents and policy inertia. Although gender and education help explain the policy preferences of the median FOMC member, political variables, notably presidential appointments to the Board, appear to be more important quantitatively.
"Deliberation and Policy Outcomes: Evidence from the Textual Analysis of FOMC Transcripts" (November 2025), with A. Riboni and L. Tran.
Natural language processing is used to extract information from FOMC transcripts and construct quantitative text-based measures of voiced policy stance, emotions, and collaboration. These measures are inputs in an econometric model of deliberation where members interact with one another across rounds of a meeting and over time across meetings. Evidence shows that members learn from one another during within-meeting deliberation and exert influence across meetings. Although emotional tone has limited effects on policy stances and decisions, it has strong predictive power for dissent behavior.
"How Should a Central Bank Respond to Extreme Events?" (revised: May 2025), with J. Kim.
Extreme value theory is used to examine the effects of exceptionally large shocks on the U.S. economy and the appropriate monetary policy response. We construct and estimate a nonlinear multi-sector model where fluctuations are driven by shocks drawn from asymmetric extreme value distributions. The model is used to evaluate a leaning policy whereby the central bank responds directly to aggregate supply and demand shocks, in addition to inflation and employment. The U.S. data favor a specification where the aggregate shocks are negatively skewed so that extreme negative events occur with positive probability, and the central bank limits their effect by means of looser monetary policy. Compared with the optimal Ramsey policy, the leaning policy attaches a larger weight to output than to inflation stabilization. This result suggests that the large increases in the money supply in response to the COVID pandemic, with its subsequent inflation surge, may have been sub-optimal. This paper was previously circulated under the title "The Macroeconomic Effects of Extreme Shocks."
"The Relationship Between Inflation and the Distribution of Relative Price Changes" (revised: September 2026), with A. Hornstein and A. Wolman.
A central challenge for monetary policy is inferring the extent to which large changes in real-time inflation data reflect unusual relative price changes, as opposed to signaling the behavior of underlying inflation. We present new tools for making this inference: first, we show that during the stable U.S. inflation period from 1995 through February 2020, monthly inflation is well explained by a summary statistic for the distribution of relative price changes, and then we use this relationship to control for relative price changes in the post-COVID period, to analyze the onset of the Great Inflation, and to construct measures of underlying inflation for the entire post-1959 period.