We construct a daily Chinese Housing Market Sentiment Index by applying GPT-4o to Chinese news articles. Our method outperforms traditional models in several validation tests, including a test based on a suite of machine learning models. Applying this index to household-level data, we find that after monetary easing, an important group of homebuyers (who have a college degree and are aged between 30 and 50) in cities with more optimistic housing sentiment have lower responses in non-housing consumption, whereas for homebuyers in other age-education groups, such a pattern does not exist. This suggests that current monetary easing might be more effective in boosting non-housing consumption than in the past for China due to weaker crowding-out effects from pessimistic housing sentiment. The paper also highlights the need for complementary structural reforms to enhance monetary policy transmission in China, a lesson relevant for other similar countries. Methodologically, it offers a tool for monitoring housing sentiment and lays out some principles for applying generative AI models, adaptable to other studies globally.

In this paper, we use a unique dataset of the List of Dishonest Judgment Debtors to explore the impact on the social credit environment of the increasing housing prices in China. We find that housing price has a negative impact on the local credit environment. Dominance analysis suggests that housing price contributes to the model R-squared (R2) by an overwhelming majority, suppressing any other economic or social factors in explaining the deteriorating credit environment. Heterogeneity analysis shows that the rule of law and moral standards mitigate the negative influence of high housing prices, while income inequality exacerbates the influence.

We study the effects of mortgage debt and informal home loans on stock ownership. Mortgage debt is typically originated with licensed financial institutions while informal home loans are obtained from private lending. Using the China Household Finance Survey data, we show that mortgage debt has a positive relationship, while informal home loans have a negative relationship, with a household’s likelihood and degree of subsequent stock market participation. Instrumental variable estimates identify a causal impact of these effects. Further tests demonstrate cross-sectional variations of these effects across urban development, education, financial literacy, loan interest rate, maturity, and funding sources.

As China’s population ages, more older workers are participating in the labor market, including a significant number of older migrant workers moving to urban areas. However, surprisingly little research has been done on their destination city and employment patterns. This paper addresses this gap by investigating the impact of city-level and industry specialization on the employment prospects of older migrant workers. Using both individual- and city-level data, we find that unlike prime-age migrant workers, older migrant workers have higher employment probabilities in relatively less-developed lower-tier Chinese cities than in better-developed high-tier cities like Shanghai, Beijing, Shenzhen, or Guangzhou. This phenomenon is driven by industry specialization, particularly in the construction sector, which fosters a dense labor market and facilitates higher job-finding rates. Additionally, construction firms and real estate developers in lower-tier cities are more willing to offer better wages than those in high-tier cities, which aligns with older migrant workers’ relatively moderate education profile and wage preferences over housing costs.

This paper investigates the impact of Covid-19 outbreak on households’ preferences for subway proximity, using housing transaction data from eight major cities with the highest metro commuting volumes. Contrary to what we expect from remote working which has been popular since Covid-19 outbreak, we find no evidence of a smaller housing price premium for subway proximity after the outbreak, based on a difference-in-difference empirical strategy.

This paper investigates the causal effects of air pollution on housing prices in China using a dataset of 65 cities from 2014 to 2021. We employ the central environmental protection inspection (CEPI) as a quasi-natural experiment for air pollution index to show a negative causal relationship between air pollution and housing prices. We also find that this causal relationship is more pronounced for less-developed, manufacturing-intensive and tourismrelied cities. Our results reveal the response to central environmental protection inspection on improvement in regional air pollution protection but its by-effects on housing markets, as the impact is limited if the inspection is conducted repeatedly, suggesting its unsustainability as a regulatory tool.

The implementation of prefabricated housing (PH) has become prevalent in China recently because of its advantages in improving production efficiency and saving energy. However, the benefits of adopting PH cannot always be accrued by the stakeholders because of the arising transaction costs (TCs) in the projects’ development process. This study investigates the strategies for developers to make rational choices for minimizing the TCs of the PH project considering their own attributes and external constraints. A Bayesian Belief Network model was applied as the analytical method, based on the surveys in China. The single sensitive analysis indicated that developers influence the TCs of PH through the three most impactful factors: Prefabrication rate, PH experience, and Contract payment method. Furthermore, combined strategies were recommended for developers in various situations based on the multiple sensitivity analysis. Developers facing high prefabrication rate challenges are suggested to reduce the risks by procuring high-qualified general contractors and adopting unit-price contracts type. For developers with limited PH experience, adopting the Engineering-Procurement-Construction procurement method is the most efficient in reducing their TCs in the context of China’s PH market. This study contributes to the current body of knowledge concerning the effect of traders’ attributes and choices on TCs, expanding the application of TCs theory and fulfilling the study on the determinants of TCs in construction management.

This paper is about investigating how different bank liquidity creation activities affect housing markets. Using data of 401 metropolitan statistical areas/metropolitan statistical area divisions (MSAs/MSADs) of the U.S. between 1990 and 2018, we show that not all bank liquidity creation activities boost the housing markets. In particular, unlike asset- side and off-balance sheet liquidity creations, funding-side liquidity creation dampens housing markets. The relationships between liquidity creation activities and housing markets are stronger in regions with inelastic house supply, but flip when banks face external liquidity shocks. We also find that housing markets dominated by large banks are more sensitive to off-balance sheet liquidity creation activities. Finally, as expected, asset-side and off-balance sheet liquidity creations boost housing markets by driving house prices away from fundamental values. Our results offer a more thorough explanation of how bank liquidity creation fuels the momentum of housing markets.

This paper provides the first theory and evidence on the role of presale policies in the residential housing market. We start with constructing a novel dataset of unfinished projects, presale policies, and land auction outcomes across 270 major cities in China. We then identify 2,330 unfinished residential projects from 2010 to 2017 on a citizen complaint website run by the central government. We find that both presale criterion and postsale supervision of construction costs relate to a lower probability of unfinished projects. But only presale criterion relates negatively to the pace of new housing development, measured by developers' multitasking and land auction outcomes. A back-of-the-envelope calculation suggests that the average bundle of presale policies is inferior to the Pareto frontier in our sampled cities. Tightening the regulation on postsale supervision by 2 standard deviations may lead to a 58% reduction in the occurrence of unfinished projects, while keeping the pace of new housing development unchanged. Eliminating unfinished projects would entail a drastic increase in both presale criterion and postsale supervision, with slower housing development.

We document a speculation channel through which house market booms negatively affect entrepreneurship. To address endogeneity concerns, we exploit plausibly exogenous variation in house prices generated by staggered and unintended policy spillovers in China. We find house market speculation triggered by house booms crowds out entrepreneurship. Reduced labor supply, reduced capital supply, and heightened entry costs do not appear to explain our main findings. The negative effect exhibits in the OECD countries as well. Our paper complements the well-documented collateral channel by offering novel evidence on a previously under-explored adverse consequence of house market booms – their hindrance to entrepreneurship.