The impact of a home purchase restrictions (HPR) policy on the distressed property market in Beijing

Shi, S; Zhang, J; Zhang, H

The impact of a home purchase restrictions (HPR) policy on the distressed property market in Beijing

Shi, S

Zhang, J Zhang, H

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: Journal of Housing Economics, 2021, 58, pp. 101877
Issue Date:: 2021

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Field	Value	Language
dc.contributor.author	Shi, S https://orcid.org/0000-0003-4188-5151
dc.contributor.author	Zhang, J
dc.contributor.author	Zhang, H
dc.date.accessioned	2023-01-11T09:18:28Z
dc.date.available	2023-01-11T09:18:28Z
dc.date.issued	2021
dc.identifier.citation	Journal of Housing Economics, 2021, 58, pp. 101877
dc.identifier.issn	1051-1377
dc.identifier.issn	1096-0791
dc.identifier.uri	http://hdl.handle.net/10453/164866
dc.description.abstract	Distressed property sales, which are carried out under court order by online auction, have increased rapidly in China in recent years. We examine how the implementation of home purchase restrictions (HPR) by the Chinese government in 2017 has affected the market for distressed properties in Beijing. We first use a stylized second-price auction model to derive theoretical predictions for how HPR should impact the number of auction entrants, auction prices/premia, and auction bidders’ average willingness to pay. We then test those predictions using data on court sales from the Taobao online auction platform from 2015 to 2018. By comparing legal auctions of housing before and after April 2017, we obtain empirical results consistent with the model's predictions. Specifically, our analysis documents that auction entrants fell by approximately 70% and auction premia by 16%–27% after the HPR policy was implemented. Furthermore, the average bidder's willingness to pay relative to the seller's valuation fell from 80% to 40%, which suggests that bidders who were affected by HPR had higher valuations, on average, than bidders who weren't.
dc.language	en
dc.publisher	Elsevier BV
dc.relation.ispartof	Journal of Housing Economics
dc.relation.isbasedon	10.1016/j.jhe.2022.101877
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	1205 Urban and Regional Planning, 1402 Applied Economics
dc.subject.classification	Economics
dc.title	The impact of a home purchase restrictions (HPR) policy on the distressed property market in Beijing
dc.type	Journal Article
utslib.citation.volume	58
utslib.for	1205 Urban and Regional Planning
utslib.for	1402 Applied Economics
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building/School of Built Environment
utslib.copyright.status	embargoed	*
utslib.copyright.embargo	2024-12-01T00:00:00+1000Z
dc.date.updated	2023-01-11T09:18:25Z
pubs.publication-status	Published
pubs.volume	58

Abstract:

Distressed property sales, which are carried out under court order by online auction, have increased rapidly in China in recent years. We examine how the implementation of home purchase restrictions (HPR) by the Chinese government in 2017 has affected the market for distressed properties in Beijing. We first use a stylized second-price auction model to derive theoretical predictions for how HPR should impact the number of auction entrants, auction prices/premia, and auction bidders’ average willingness to pay. We then test those predictions using data on court sales from the Taobao online auction platform from 2015 to 2018. By comparing legal auctions of housing before and after April 2017, we obtain empirical results consistent with the model's predictions. Specifically, our analysis documents that auction entrants fell by approximately 70% and auction premia by 16%–27% after the HPR policy was implemented. Furthermore, the average bidder's willingness to pay relative to the seller's valuation fell from 80% to 40%, which suggests that bidders who were affected by HPR had higher valuations, on average, than bidders who weren't.

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http://hdl.handle.net/10453/164866