Abstract
As both a vibrant industry and necessity for people's lives, housing has attracted much attention in recent years. This article examines the efficacy of both loosening and tightening policies on mortgage lending in different priced housing markets in Shanghai, China, from 2014 to 2018 using daily average sale prices across 1,824 neighborhoods, with price-classified cluster analysis and policy-informed hedonic regressions. The results show that (1) the effects of mortgage lending policy interventions varied significantly and the overall spatial distribution gravitated toward subway networks and varied throughout the years; (2) the effects of interventions were time lagged but varied by different priced neighborhoods; and (3) although the accumulated number of both loosening and tightening policies were both significant, only the effects of tightening policies were significant overall. This article contributes to the existing literature by combining the spatial-temporal component in policy studies, providing detailed mortgage lending policy intervention variables, and expanding the scope of study from housing prices to housing transaction frequencies. ©2022 by American Association of Geographers.
| Original language | English |
|---|---|
| Pages (from-to) | 495-511 |
| Number of pages | 17 |
| Journal | The Professional Geographer |
| Volume | 75 |
| Issue number | 3 |
| Online published | 2 Feb 2023 |
| DOIs | |
| Publication status | Published - May 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Research Keywords
- loosening and tightening policies
- low-priced neighborhoods
- mortgage lending
- residential property market
- spatial temporal variation
- HOUSING-MARKET EVIDENCE
- GOVERNMENT INTERVENTION
- CHINA
- DENSITY
- POLICY
- DYNAMICS
- PATTERN
- IMPACT
- CITIES
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