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.

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.