This study employs a Triple-Difference (Triple-DID) model, utilizing balanced panel data at the district level from Beijing, Shanghai, Shenzhen, and Hangzhou between 2018 and 2024, to critically evaluate the effectiveness of the Multi-School Zoning Policy (MSZP) in suppressing the capitalization of educational resources into housing prices and promoting educational equity. The research explicitly accounts for spatial and institutional heterogeneity as well as household strategic behavior.The results indicate that: (1) MSZP significantly reduced the average housing price premium associated with elite school districts by 15.2%, with the strongest effect observed in Beijing and the weakest in Hangzhou; (2) The policy's effectiveness diminishes as the spatial concentration of high-quality educational resources increases, highlighting persistent structural inequalities; (3) In areas characterized by resource monopolization and strong institutional inertia, the policy's suppressive effect on educational capitalization and its gains in educational equity are both constrained.The findings suggest that MSZP alone cannot fully overcome the "spatial lock-in" effect of high-quality educational resources. Achieving lasting equity requires complementary deeper institutional innovations, such as robust cross-district teacher rotation, transparent resource allocation mechanisms, and adaptive zoning algorithms. This research offers quantitative evidence for optimizing policy and institutional tools in the pursuit of comprehensive urban education reform.

We construct a Housing Purchase Intention Index (HPII) using the Baidu Search Index, which captures online search behavior directly reflecting households’ housing purchase intentions. We assess the predictive power of the HPII for the growth rate of housing transaction volume and further examine factors influencing housing purchase intention. The results show that the HPII has significant predictive ability and enhances real-time forecasting accuracy, highlighting the role of search behavior as a behavioral signal in the housing market. We also find that housing purchase intention is shaped by policy, economic, demographic, and supply factors. Specifically, purchase restriction policies exhibit an inverted U-shaped effect; moderate mortgage-rate hikes dampen purchase intention, while persistent increases may induce anticipatory buying. In addition, rising wages, increasing population concentration, and expanded residential land supply consistently strengthen housing purchase intention. These findings provide new behavioral evidence on the drivers of housing demand and underscore the value of search-based indicators for understanding household decision-making in the real estate market.

Shill bidding, the use of non-genuine bids to inflate prices, undermines auction market integrity. Exploiting China’s online judicial housing auctions as a laboratory, we identify 2% of participants as suspected shill bidders, affecting 8% of auctions. They raise price premium by 14.3%, causing an annual deadweight loss of ¥570 million for homebuyers. Mechanism analysis reveals they create bidding momentum and intensify competition. We establish causality using a difference-in-differences analysis leveraging a 2017 regulatory intervention and an instrumental variable approach using dishonest judgment debtors. These findings offer actionable insights for policymakers and auction platforms to combat fraud in online high-stake auctions.

This study examines how housing purchase restrictions (HPRs) affect firms' robotics adoption through labor cost increases. Exploiting policy-driven housing price shocks across Chinese cities, we find firms significantly accelerate robot adoption in response to higher labor costs. Effects are pronounced among financially unconstrained firms, state-owned enterprises, and firms with skilled or educated workforces. Automation investments subsequently improve firm productivity, profitability, and market positions. Our findings highlight unintended spillovers from housing regulations to firm-level technological decisions and suggest policymakers consider these indirect effects when designing local market interventions.

This study examines the economic consequences of China’s Three-Red-Lines policy—introduced in 2021 to cap real estate developers’ leverage by imposing strict thresholds on debt ratios and liquidity. Developers breaching these thresholds experienced sharp declines in financing, land acquisitions, and financial performance, with privately-owned developers disproportionately affected relative to state-owned firms. Using granular project-level data, we document significant drops in sales and a demand shift from private to state-owned developers. The policy also reduced local governments’ land sale revenues, prompting greater reliance on hidden local government financing vehicles for land purchases. The policy induced broad structural changes in China’s housing and land markets.

The aging population is intensifying, and solving the problem of elderly care is urgent. This article is based on CHFS (2019) survey data, and empirical research has found that commercial pension insurance significantly promotes households' allocation of risky financial assets. The mechanism is tested using household risk perception and investment risk preference as mediating variables. In addition, through heterogeneity testing, it was found that the positive effect of commercial pension insurance on the allocation of risky financial assets is more significant in rural households with household registration, two sets of housing, and households in the northeast.

The aging population is expanding globally, and addressing the challenges of elderly care is urgent. Using the 2019 China Household Finance Survey data, this study finds that commercial pension insurance significantly promotes households’ allocation of risky financial assets. We test the mechanisms using household risk perception and investment risk preference as mediating variables. Heterogeneity analysis reveals that the positive effect of commercial pension insurance on risky financial asset allocation is more significant in rural households with household registration, those with two sets of housing, and households in the northeast. The research findings of this article aim to promote the continuous improvement of China’s elderly care system and provide important empirical evidence for the formulation of relevant policies.

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.