Chinese University of Hong Kong
Institutional Affiliation: Chinese University of Hong Kong
NBER Working Papers and Publications
|March 2020||Learning about the Neighborhood|
with Michael Sockin, Wei Xiong: w26907
We develop a model to analyze information aggregation and learning in housing markets. In the presence of pervasive informational frictions, housing prices serve as important signals to households and capital producers about the economic strength of a neighborhood. Our model provides a novel mechanism for amplification through learning in which noise from the housing market can propagate to the local economy, distorting not only migration into the neighborhood, but also the supply of capital and labor. We provide consistent evidence of our model implications for housing price volatility and new construction using data from the recent U.S. housing cycle.
|November 2019||Economic Consequences of Housing Speculation|
with Michael Sockin, Wei Xiong: w26457
By exploiting variation in state capital gains taxation as an instrument, we analyze the economic consequences of housing speculation during the U.S. housing boom in the 2000s. We find that housing speculation, anchored, in part, on extrapolation of past housing price changes, led not only to greater price appreciation, economic expansions, and housing construction during the boom in 2004-2006, but also to more severe economic downturns during the subsequent bust in 2007-2009. Our analysis supports supply overhang and local household demand as two key channels for transmitting these adverse effects.
|November 2017||Daily Price Limits and Destructive Market Behavior|
with Ting Chen, Jibao He, Wenxi Jiang, Wei Xiong: w24014
We use account-level data from the Shenzhen Stock Exchange to show that daily price limits, a widely adopted market stabilization mechanism, may lead to unintended, destructive market behavior: large investors tend to buy on the day when a stock hits the 10% upper price limit and then sell on the next day; and their net buying on the limit-hitting day predicts stronger long-run price reversal. We also analyze a sample of special treatment (ST) stocks, which face tighter 5% daily price limits, and provide a causal validation from comparing market dynamics before and after they are assigned the ST status.
Published: Ting Chen & Zhenyu Gao & Jibao He & Wenxi Jiang & Wei Xiong, 2018. "Daily price limits and destructive market behavior," Journal of Econometrics, .