"Information Acquisition and the Finance-Uncertainty Trap" (with Ding Dong, Allen Hu, and Zhaorui Li), ederal Reserve Bank of San Francisco Working Paper 2025-12, July 2025.
"The Rise of AI Pricing: Trends, Driving Forces, and Implications for Firm Performance" (with Jonathan Adams, Min Fang, and Yajie Wang), Federal Reserve Bank of San Francisco Working Paper 2024-33, November 2024. Presented at the 2025 Carnegie-Rochester-NYU Conference on Public Policy, with proceedings to be published in a special issue of the Journal of Monetary Economics.
This paper documents key stylized facts about the time-series trends and cross-sectional distributions of AI pricing and study its implications for firm performance, both on average and conditional on monetary policy shocks.
"The Crowding-In Effects of Local Government Debt in China" (with Yuchao Peng, Xiaoming Li, and Zhiwei Xu), Federal Reserve Bank of San Francisco Working Paper 2024-35, November 2024. Revise and resubmit, Journal of Monetary Economics
We study how changes in the composition of Chinese local government debt influenced bank risk taking, credit allocation, and local productivity. Using confidential loan-level data and a difference-in-difference identification approach, we show that a debt-to-bond swap program for local governments implemented in 2015 significantly increased bank risk taking through a risk-weighting channel under Basel III capital regulations. The debt swap program converted bank holdings of municipal corporate debt to local government bonds, reducing banks’ risk-weighted assets. Banks responded by lowering credit spreads on loans to privately owned firms (POEs) relative to state-owned enterprises (SOEs), with significantly larger reductions in POE credit spreads in provinces with more outstanding government debt. Furthermore, the credit reallocation toward more productive private firms—a crowding in effect of the debt swap—significantly raised local productivity.
"Inflation Disagreement Weakens the Power of Monetary Policy" (with Ding Dong, Pengfei Wang, and Min Wei), Federal Reserve Bank of San Francisco Working Paper 2024-27, August 2024.
Households often disagree about their inflation outlooks. Evidence suggests that inflation disagreement weakens the power of monetary policy. A consumer with higher inflation expectations perceives a lower real interest rate and thus has a high propensity to consume (MPC). High-MPC consumers borrow to finance spending, subject to borrowing constraints. An increase in inflation disagreement means a larger share of consumers would face binding borrowing constraints, lowering the sensitivity of aggregate consumption to changes in interest rates induced by monetary policy shocks.
"Targeted Reserve Requirements for Macroeconomic Stabilization" (with Mark Spiegel and Jingyi Zhang), Federal Reserve Bank of San Francisco Working Paper 2023-13, April 2023. R&R, International Economic Review.
Large and small banks serve different customers and should face different regulations. Targeted reserve requirements such as those used by China's central bank are effective for stabilizing macro fluctuations, especially in deep recessions, because the policy mitigates the resource costs for firms to switch lenders.
"Fiscal Stimulus under Average Inflation Targeting" (with Jianjun Miao and Dongling Su), Federal Reserve Bank of San Francisco Working Paper 2022-22, November 2022.
Average inflation targeting (AIT) under the Federal Reserve's new policy framework can have important implications for fiscal policy in stabilizing business cycles. In particular, the fiscal-policy implications of AIT depend on whether or not the economy is in a liquidity trap.
"Can Pandemic-Induced Job Uncertainty Stimulate Automation?" (with Sylvain Leduc), Federal Reserve Bank of San Francisco Working Paper 2020-19, May 2020. Media mentions: VoxEu
The COVID-19 pandemic led to a surge in job uncertainty, creating an incentive for firms to adopt robots and other labor-substituting automation technologies that might hurt workers.