Publications
“Endogenous Participation, Risk, and Learning in the Stock Market”, Macroeconomic Dynamics, 2020, 1-33.
Abstract: A simple asset pricing model with both endogenous stock market participation and subjective risk can explain the negative cross-country correlation between participation rates and the volatility of excess returns, along with the time-varying participation rates in the data. Belief-driven learning dynamics can explain the interplay between participation, subjective risk, and price volatility. When agents adaptively learn about the risk and return, the model can generate 25% of the excess volatility in stock prices observed in U.S. data while matching key moments. With learning about risk, excess volatility of prices is driven by fluctuations in the participation rate that arise because agents' risk estimates vary with prices. I find that learning about risk is quantitatively more important than learning about returns.
“Subjective Expectations, Experiences, and Stock Market Participation: Evidence From the Lab”, Journal of Economic Behavior & Organization, 2021, 186: 672-689.
Abstract: Recent evidence suggests that stock market experiences, i.e. realized returns, impact subjective expected returns. I bring a model into the laboratory and find that experience-based subjective expected returns can help explain limited stock market participation. In the experiment, the probability of subjects participating in the stock market is increasing in both their subjective expected returns and past realized returns. I find that “learning from experience" generates heterogeneity in subjective expected returns, where subjects who “experience" low returns have lower subjective expected returns than subjects who only observe low returns. This experience effect is asymmetric, where subjects who experience high returns have no statistically significant difference in their subjective expected returns than subjects who only observe high returns. Finally, after a series of low returns, a fraction of subjects leave the stock market indefinitely.
Working Papers
“Heterogeneous Experience and Constant-Gain Learning” (with John Duffy) (Revise and resubmit at the Journal of Economic Dynamics and Control)
Abstract: Recent evidence suggests that agents may base their forecasts for macroeconomic variables mainly on their personal life experiences. We connect this behavior to the concept of constant-gain learning (CGL) in macroeconomics. Our approach incorporates both heterogeneity in the life cycle via the perpetual youth model and learning from experience (LfE) into a linear expectations model where agents are born and die with some probability every period. For LfE, agents employ a decreasing-gain learning (DGL) model using data only from their own lifetimes. While agents are using DGL individually, we show that in the aggregate, expectations follow an approach related to CGL, where the gain is now tied to the probabilities of birth and death. We provide a precise characterization of the relationship between CGL and our model of perpetual youth learning (PYL) and show that PYL can well approximate CGL while pinning down the gain parameter with demographic data. Calibrating the model to U.S. demographics leads to gain parameters similar to those found in the literature. Further, variation in birth and death rates across countries and time periods can help explain the empirical time-variation in gains. Finally, we show that our approach is robust to alternative ways of modeling individual agent learning.
Works in Progress
CEO Inflation Experience, Attention, and Corporate Decisions (with Diego Garcia, Chanik Jo, and Siyuan Wu) in progress
Endogenous Stock Market Participation and Time-Varying Volatility (with Guanglian Hu) in progress
Learning, Hypothesis Testing, and Restricted Perceptions Equilibria in progress