News, Sentiment, and Inflation Expectations: Insights from Social Media Data and Experiments
Job Market Paper / Dissertation Chapter
This project studies how households use news media when forming inflation
expectations. It combines household survey data, social-media news data,
machine-learning methods, and an information-provision experiment.
Presented at: ASSA 2026, Indiana University Macroeconomic Seminar (2025), Midwest Macroeconomics Meeting (Spring 2025), Ostrom-Smith Conference in Behavioral and Experimental Economics (2023), Hoosier Economic Conference (2023), Department of Economics Macro Brownbag (2023)
Incentivizing Inflation Expectations
with Daniela Puzzello, Ryan Rholes, and Alena Wabitsch
We study whether performance-based marginal incentives improve the measurement
of household inflation expectations. Incentives reduce upward bias and
disagreement, close the gender gap in reported beliefs, and strengthen learning
from information.
Presented at: SED (2026), the BSE Summer Forum Workshops on Advancing Methods in Behavioral and Experimental Economics and Theoretical and Experimental Macroeconomic (2026), Vienna University of Technology, Midwest Macroeconomics (2026), New York Fed, ETH Zurich (KOF), University of Vienna, University of Southern California, NTU Behavioral Macroeconomics Workshop (2026), Heidelberg University, the 9th SAFE Household Finance Workshop, the Summer School on Experimetrics and Behavioral Economics (2025), the Ostrom-Smith Conference in Behavioral and Experimental Economics, the BSE Summer Forum Workshop on Theoretical and Experimental Macroeconomics (2025), and the 3rd Paris Conference on the Macroeconomics of Expectations
Forecasting the Future Through a Partisan Lens: Electoral Outcomes and Household Expectations
with Nayeon Kang
We study how the 2024 U.S. presidential election shaped household expectations. Republicans revised inflation and unemployment expectations downward, while Democrats revised both upward, although subjective uncertainty declined for both groups. We also find that AI-generated personas capture some directional partisan responses but perform poorly quantitatively, highlighting their limitations as substitutes for human survey data.
Presented at: 10th European Workshop on Political Macroeconomics (2026), Midwest Macroeconomics (2026), Ostrom-Smith Conference in Behavioral and Experimental Economics (2026)