Liquidity in the Housing Market: Credit Standards, Volatility Clustering and Asymmetric Price Adjustment
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Authors
Zhou, Chenggang
Date
2015-02-17
Type
thesis
Language
eng
Keyword
Mortgages , Economics , Search Frictions , Volatility Clustering , Macroeconomics , Housing
Alternative Title
Abstract
This dissertation studies various economic issues related to the housing market. First, I investigate how trading frictions in a housing market affect lenders' decisions. In Chapter 2, by employing a dynamic house search model with long-term mortgage debt, I find that a more liquid housing market reduces not only the possibility of a borrower to default but also the lender's cost upon default. These benefits induce lenders to require lower credit requirements and issue larger loans.
Second, Chapter 3 is an empirical study of volatility clustering (ARCH/GARCH effects) in home price of Canadian cities. I find that most Canadian major cities exhibit ARCH/GARCH effects in house price return and several cities also show TGARCH effects, i.e. price volatility is asymmetric in response to positive and negative shocks. Furthermore, I analyze the determinants of house price volatility and document asymmetric price adjustment in Canada.
Finally, in Chapter 4, I develop a static house search model with indebted sellers to study the asymmetric adjustment of house prices. The analysis shows that positive changes of the average house price are larger and more likely to reflect the underlying shocks than negative changes due to the equity effect, i.e. sellers with less house equity tend to post higher asking prices. This result is consistent with empirical findings that the house price exhibits downward rigidity.
Description
Thesis (Ph.D, Economics) -- Queen's University, 2015-02-13 17:36:52.898
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This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.