Guanghua School of Management
Information about this author at RePEc
NBER Working Papers and Publications
|October 2013||Market Thickness and the Impact of Unemployment on Housing Market Outcomes|
with Li Gan: w19564
This paper develops a search-matching model to study the impact of the unemployment rate on the housing market in the presence of the thick market effect. We estimate the structural model using Texas city-level data that covers three years, 1990, 2000 and 2010. Our structural estimation helps identify the channel through which the thick market effect amplifies the impact of the unemployment rate on housing market outcomes. Specifically, we show that an increase in the unemployment generates a thinner market, which leads to poorer matching quality on average. As a consequence, prices and the transaction volume both decline more than in the absence of the thick market effect. Simulations based on our estimates predict that a three percentage-point increase in the unemployment rate lowers ...
|June 2009||China's Land Market Auctions: Evidence of Corruption|
with Hongbin Cai, J. Vernon Henderson: w15067
This paper studies the urban land market in China in 2003--2007. In China, all urban land is owned by the state. Leasehold use rights for land for (re)development are sold by city governments and are a key source of city revenue. Leasehold sales are viewed as a major venue for corruption, prompting a number of reforms over the years. Reforms now require all leasehold rights be sold at public auction. There are two main types of auction: regular English auction and an unusual type which we call a "two stage auction". The latter type of auction seems more subject to corruption, and to side deals between potential bidders and the auctioneer. Absent corruption, theory suggests that two stage auctions would most likely maximize sales revenue for properties which are likely to have relatively fe...
Published: Hongbin Cai & J. Vernon Henderson & Qinghua Zhang, 2013. "China's land market auctions: evidence of corruption?," RAND Journal of Economics, RAND Corporation, vol. 44(3), pages 488-521, 09. citation courtesy of
|April 2006||The Thick Market Effect on Housing Markets Transactions|
with Li Gan: w12134
This paper provides a search model for housing market where the number of buyers and/or sellers plays very important role. The model makes three testable predictions: (1) the unemployment rate has a negative impact on the trading volume and the sale prices of the housing market; (2) a larger housing market has a lower average sale price, shorter time-to-sale and smaller price dispersion, in addition to a lower vacancy rate. (3) In a larger housing market, when the unemployment rate goes up (or down), the sale price decreases (or increases) by a smaller percentage than in a smaller market. All three predictions are supported by a panel dataset of the Texas city-level housing markets.
Published: Gan, Li and Qinghua Zhang. “The Thick Market Effect of Local Unemployment Rate Fluctuations.” Journal of Econometrics 133(2006): 127-152.
|April 2005||The Thick Market Effect on Local Unemployment Rate Fluctuations|
with Li Gan: w11248
This paper studies how the thick market effect influences local unemployment rate fluctuations. The paper presents a model to demonstrate that the average matching quality improves as the number of workers and firms increases. Unemployed workers accumulate in a city until the local labor market reaches a critical minimum size, which leads to cyclical fluctuations in the local unemployment rates. Since larger cities attain the critical market size more frequently, they have shorter unemployment cycles, lower peak unemployment rates, and lower mean unemployment rates. Our empirical tests are consisten with the predictions of the model. In particular, we find that an increase of two standard deviations in city size shortens the unemployment cycles by about 0.72 months, lowers the peak unemplo...
Published: Gan, Li and Qinghua Zhang. "The Thick Market Effect on Local Unemployment Rate Fluctuations." Journal of Econometrics 133, 1 (July 2006): 127-152 citation courtesy of