Market sentiment, housing prices, consumption structure upgrading and cities' innovation capacity in China - Ding, Yemin (2022)
In recent years, the media has portrayed China’s housing market with terms like “Riguangpan” and “panic-buying housing”, which has fueled irrational sentiment among potential home buyers, leading to noise trading and the herding effect. This has caused a dramatic rise in China’s housing demand and housing prices. While existing literature has explained this phenomenon from multiple perspectives, there is a lack of empirical research on it through the lens of behavioral economics. Therefore, the first objective of this study was to explore the impact of market sentiment on China’s housing prices from the behavioral economics perspective. The results of a fixed effect model analysis of 45 sample cities from 2011 to 2017 showed that market sentiment plays a significant role in driving up China's housing prices; this relationship was confirmed through robustness checks. Additionally, the sample cities were divided into two sub-samples (first-tier cities and second-tier cities) for heterogeneity analysis, revealing that market sentiment has a stronger positive impact on housing prices in China’s first-tier cities. These findings suggest that local governments in China should pay attention to housing market sentiment and consider regularly quantifying and publishing it to help improve market participants’ understanding of the current housing market and encourage rational decisions. Although consumption structure upgrading reflects the improvement of Chinese residents’ living standards and stimulates economic growth, the dramatic rise of housing prices makes such upgrading difficult. Therefore, the second objective of this study was to examine the impact of housing prices on the upgrading of Chinese residents’ consumption structure. The estimation results showed that housing prices have an inverted U-shaped impact on the upgrading of urban residents’ consumption structure, but an inhibitory effect on the upgrading of rural residents’ consumption structure. There was also heterogeneity in the relationship between housing prices and consumption structure upgrading across different cities. Based on these findings, it is recommended that local governments in China, with the exception of a few cities where housing prices have not yet passed the extreme point of this inverted U-shaped relationship, should focus on house price regulation. The Chinese government should also prioritize promoting rural revitalization to mitigate the negative impact of rising commercial housing prices on the upgrading of Chinese rural residents’ consumption structure. Innovation is a decisive factor in China’s sustained economic growth, but the effect of rising house prices on cities’ innovation capacity is unclear. The third objective of the study was thus to investigate the impact of housing prices on cities’ innovation capacity in China. The results of static, dynamic, and Poisson estimation demonstrated a positive relationship between the two. Further exploration revealed that high housing prices achieve innovation through talent attraction and fiscal growth but can restrain innovation by lowering fund availability and residents’ consumption ability. Additionally, the tight bank credit scale prevents rising house prices from promoting cities’ innovation capacity. Based on these findings, it is recommended that local governments restrain real estate investments and expand the scale of bank credit, to increase the availability of loans for innovation.