Yeji Sung

I'm an economist at the Federal Reserve Bank of San Francisco.

I've been building computational models to understand how people, given their limited attention and memory, process information and form expectations. I'm interested in how these cognitive constraints shape outcomes on a larger scale—like in the broader economy—and what this means for designing effective policies and communication strategies.

Here is my CV.

You can contact me at yeji.sung@sf.frb.org.

SF Fed Workshop on Expectations and Behavioral Macroeconomics

Date: October 27, 2025
Here is our program

Working Papers

Macroeconomic Expectations and Cognitive Noise

Revise & Resubmit, American Economic Review

Standard models of information frictions explain sluggish forecasts but struggle to account for cases of excessive sensitivity. I argue that this limitation arises because these models define information frictions too narrowly—emphasizing constraints on processing new information while assuming past information remains fully accessible. I propose a broader framework that integrates both attention and memory frictions, which reflects constraints on processing new and past information, respectively. This unified model better matches observed forecast biases, enables joint identification of the two frictions from survey data, and provides novel insights for optimal monetary policy responses to cost-push shocks.

Publications

Optimally Imprecise Memory and Biased Forecasts (with Rava Azeredo da Silveira and Michael Woodford)

American Economic Review, 114 (10): 3075–3118, October 2024

We propose a model of optimal decision-making subject to a memory constraint in the spirit of models of rational inattention. Our theory differs from that of Sims (2003) in not assuming costless memory of past cognitive states. The model implies that both forecasts and actions will exhibit idiosyncratic random variation; that average beliefs will exhibit a bias that fluctuates forever; and that more recent news will be given disproportionate weight in forecasts. The model provides a simple explanation for the overreaction to news observed in the laboratory by Afrouzi et al. (2023).

Teaching

At Columbia University, I was a teaching assistant for

Money and Banking (2019)
The Psychology and Economics of Consumer Finance (MBA; 2018,2019)
International Trade (2017)

At Seoul National University, I was a teaching assistant for

Advanced Macroeconomics (PhD)
Applied Macroeconomics (PhD)
Macroeconomics
Microeconomics
Principles of Economics
Introductory Statistics for Economists

Policy Pieces

The impact of TLTOR2 on the Italian credit market: some econometric evidence, Feb. 2020

with Lucia Esposito and Davide Fantino

Bank of Italy Temi di discussione No. 1264

This work evaluates the impact of the second series of Targeted Longer-Term Refinancing Operations (TLTRO2) on credit market conditions for Italian firms. The estimates use a difference-in-differences approach on quarterly data, including term loans, interest rates, and bank and firm characteristics, between the start of 2015 and the end of 2017. The TLTRO2 had a positive impact on credit, encouraging lending to firms and reducing interest rates. The impact on the amount of credit was stronger for less risky firms, while that on interest rates was stronger for riskier ones. Smaller firms benefited more in terms of both loan amounts and interest rates.