Using a unique Chinese data set capturing the trading behavior of particularly aggressive investors, we provide new evidence that is consistent with the presence of informational advantages. Critically, an advantage of our data is that we can also directly identify several plausible channels through which such an informational advantage could arise. Specifically, return predictability around key value-relevant events is most pronounced in the presence of aggressive traders who share the same geographic location as the firms in which they trade.
China has witnessed persistent increases in economic inequality since the early 1990s when the urban labor market began its transformation — from centrally-controlled to market-driven. Using the Urban Household Survey data, this paper (Feng and Tang, 2018) documents the trends...
Using data from the China Employer-Employee Survey (CEES), a recent survey of Chinese manufacturing firms, we analyze the extent to which employees of differing levels are able to assess their firms’ management practices. Our study finds that of CEOs, managers, and workers, CEOs tend to have the most accurate appraisals of their firms. Additionally, we find that firms with higher levels of disagreement...
Residential investment has been a key growth engine for China in the last two decades. Total housing investment grew from about 4 percent of GDP in 1997 to a peak of 15 percent of GDP in 2014, with residential investment accounting for more than two-thirds of it. Our analysis indicates that structural changes in the Chinese economy that led to rebalancing toward consumption...
Gift expenditures grow swiftly in rural China and may adversely affect people's welfare. While gift-giving helps to maintain social status and connections, gift competition may create a predicament: people must spend more and more to "keep up with the Joneses." As a result, the escalating gift expenses crowd out spending on other important consumption and become increasingly burdensome to people in rural areas, particularly to the poor.