Geography of housing bubbles in Shanghai: a study of price-to-rent ratios at the community level

Abstract

Scholars are divided over the existence of a housing bubble in China and the effectiveness of the price-to-rent [(P/R)] ratio in detecting it. This disagreement may stem from the absence of region-specific (P/R) ratios and the unique socioeconomic, cultural, and institutional characteristics of Chinese cities, which challenge the application of international standards in measuring housing bubbles. This study contributes to the debate by examining the distribution and spatial dynamics of community-level (P/R) ratios in Shanghai from a spatial and geographical perspective. We found that in 2018, over 90% of communities in Shanghai had a (P/R) ratio ranging from 50 to 80, a range considered high by international standards. Furthermore, our comparison of 2018 (P/R) ratios with foreclosure cases in 2021 reveals that while (P/R) ratios are not directly comparable across different cities, they can indicate the relative severity of housing bubbles at an intra-urban level. Our regression and machine learning models indicate that (P/R) ratios are collectively influenced by fundamental and non-fundamental determinants. However, fundamental determinants like GDP per capita and public schools have only a marginal positive impact compared to speculative elements like proximity to the Central Business District (CBD) and parks. Other key fundamentals like job opportunities and average salary are insignificant. This suggests that Shanghai’s housing market was likely experiencing a bubble in 2018.

KEYWORDS: :

• Price-to-rent ratio
• housing bubble
• Shanghai
• non-linear relationship

Disclosure statement

No potential conflict of interest was reported by the author.