Housing Prices In China Research Articles

The Current Situation of the Housing Market Bubble in Chinas First-tier Cities

Abstract: With the progression of China's economy and urbanization, the real estate industry experienced rapid growth, accompanied by increasing speculative activities, which led to a continuous rise in housing prices and the formation of a bubble. Therefore, the focus of this study was the current state of China's real estate bubble and potential solutions. Given the issue of excessively high real estate prices, this study specifically examined the price trends and factors contributing to the real estate bubble in four Chinese cities: Beijing, Shanghai, Guangzhou, and Shenzhen. The research methodology was as follows: First, data on the price-to-income ratio was collected to analyze the current state of housing prices in China, revealing that housing prices were still far above their actual value and beyond a reasonable range, thereby indicating the severity of the real estate bubble in China. Second, by analyzing data and reviewing the literature, the factors contributing to China's real estate bubble were identified and categorized into two main groups: policy-related and economic. On the policy side, factors included policy reforms, monetary easing, and reductions in both the benchmark interest rate and the reserve requirement ratio. On the economic side, factors included the growth in per capita disposable income and speculative behavior. Finally, this paper analyzed how a property tax could curb speculative activities by increasing the cost of purchasing properties, thereby reducing demand and speculative behavior. The findings revealed that the real estate bubble in China's first-tier cities remained severe, and that a property tax could help curb speculative activities and slow the pace of bubble expansion.

The Impact of Housing Price Volatility on Household Consumption in Northeast China Across Different Demographic Profiles

Amidst the backdrop of an economic downturn, urban housing prices in China have exhibited substantial volatility, significantly impacting domestic demand and household consumption. Demographic characteristics of households have played a pivotal moderating role in this dynamic. Due to economic stagnation and population outflow, Northeast China has garnered heightened attention. This study employs microdata from households in Liaoning and Heilongjiang provinces, spanning from 1989 to 2015, to conduct an empirical examination. The findings indicate that rising housing prices exert a pronounced positive influence on household consumption, particularly among households with children and those headed by elderly individuals. Conversely, the educational attainment of the household head does not exhibit a statistically significant impact on the real estate wealth effect. The study concludes with policy recommendations aimed at stimulating domestic demand and stabilizing housing prices in Northeast China.

The Impact of Urban Planning on House Prices in China

Urban planning is a major part of urban development and leads the future direction of the city. In different times and social situations, urban planning can change, and this change can have an impact on house prices. This paper analyzes the changes in house prices due to urban planning, with China as the main subject. China's real estate market has changed significantly. Housing prices have changed more dramatically and are more susceptible to external factors. Through the collection of data on house prices in Beijing, Jiangsu, and other regions and the development of urban planning, it summarizes the important factors of urban planning affecting house prices and provides an in-depth analysis of different factors. Through the conclusions obtained from different analyses, this essay summarizes the relationship between urban planning and house prices and provides certain suggestions to the government on plans and improvements to address the issues involved.

Feeling the heat: Extreme temperatures and housing prices in China

AbstractClimate change‐driven extreme heat events pose a major threat to urban expansion globally. This study evaluates the relationship between extreme heat and housing prices utilizing panel data from Chinese cities between 2009 and 2019. Our findings indicate a significant negative correlation between housing prices and extreme temperatures. Specifically, we observe a 0.1% reduction in housing prices for each additional day per year with temperatures surpassing 35°C. This research evaluates two primary mechanisms underpinning this finding. Firstly, our analysis demonstrates a decline in labor inflows to cities experiencing extreme heat, with a particularly significant effect on the influx of high‐skilled workers. In addition, existing residents in these hotter urban environments exhibit reduced home‐buying intentions and reduced proclivity for long‐term residency, coupled with higher living costs. Secondly, our findings indicate that extreme heat acts as a deterrent to firm entry, thereby further suppressing housing demand. This study contributes valuable empirical insights into the capitalization of climate risk in housing markets, with a specific emphasis on the effect of extreme heat. Moreover, it highlights the urgent necessity for the development and implementation of sustainable adaptation strategies to reduce the negative effects of evolving climatic conditions.

Inter-city housing spillovers and monetary policy in China

While a great deal of effort over the past few decades has been devoted to the study of housing spillovers, much of the work has failed to grasp the critical role played by monetary policy. This study aims to investigate the full version of housing spillovers across monetary policy and local housing markets by introducing a hybrid structural vector autoregression (VAR) followed by a “two-sector” spillover account. Using monthly data for national M2 and city-level housing prices in China, we find that monetary policy has since 2019 played a key role in combating housing systemic risk by lowering inter-city ripple effects. At the same time, the pivotal position of Shenzhen in coordinating monetary policy with residential markets deserves explicit emphasis.

The Impact of Government Macro-Control on Commodity Housing Prices in China: An Analytical Study

The Chinese government has implemented macro-control measures to stabilize soaring housing prices, yet the effectiveness of these interventions remains largely unexamined. This study evaluates the impact of macroeconomic policies on commodity housing prices by considering both supply and demand factors and aims to construct a concise, robust simulation model. This model will serve as a reference for the government in establishing a systematic, strategic, and enduring macro-control mechanism for the real estate sector. Our model integrates four key variables: development/consumption stage tax rates, lending rates, and land prices, to simulate their collective influence on commercial housing prices. The findings indicate that: (1) the development stage tax rate and loan interest rates significantly enhance prices, demonstrating a strong positive feedback, whereas the consumption stage tax rate exerts a minimal negative impact; (2) land price exhibits the most substantial positive feedback effect on housing prices, primarily from the supply side; (3) adjusting land prices through land policy and modulating the development stage tax rate through tax policy are crucial for managing real estate development effectively; (4) a combined approach of adjusting land and development stage tax rates, supported by monetary policy, can significantly enhance the effectiveness of China’s real estate macro-policy regulation.

Rise and Fall: The Heterogeneous Impacts of School Federations on Housing Prices in China

School federations may promote the flow of education resources between headquarter and branch schools, yet there have been few studies on the heterogeneous effect of school federations on housing prices of headquarter and branch school attendance zones. This article uses a difference in difference in differences (DDD) model to examine this effect with house transaction data of Hefei, China. It found that school federations make housing prices in headquarter school attendance zones rise, while prices in branch school attendance zones fall. Results imply school-choice families prefer headquarter schools to branch schools of federations. Potential explanations imply that the federation makes headquarter schools capture more senior teachers, and may disclose the better education quality information about headquarter schools to school-choice families.

Financial shock transmission in China's banking and housing sectors: A network analysis

Rising housing prices in China present a significant risk to financial and economic stability. Our study investigates this "gray rhino" risk by analyzing the financial shock transmission network, using a novel high-dimensional network approach applied to data from 45 real estate firms and 15 banks from 2011 to 2023. We discover that the network's connectedness is predominantly short-term and internal to each sector, with weaker inter-sectoral links. Key macroeconomic indicators, notably monetary policy uncertainty, and inflation, significantly drive this connectedness. Our results indicate that, despite concerns, China's real estate risk remains within manageable bounds, offering critical insights for market stakeholders.

Unleashing the real estate market: assessing the impact of relaxed housing purchase restriction policy on house prices in China

ABSTRACT This study examines the effects of the relaxed housing purchase restriction (RHPR) policy on house prices in China, using panel data from 41 cities between January 2021 and June 2022. The study finds that the RHPR policy has a positive effect on the existing housing market, contributing to its stabilization. However, the impact on new house prices is unclear. Mechanism analysis indicates that the policy effectively boosts house demand and fosters positive market expectations. The study also finds that the policy has a greater impact on second-tier and northern cities. Additionally, the research indicates that the policy has stimulated house demand among non-registered populations and in non-restricted purchase zones. These results emphasize the importance of timely adjustment and optimization of real estate policies to maintain a stable and sustainable market.

Study on the influence of housing price on fertility intention in the new development stage

In recent years, in order to adapt to the economic and social development and constantly adjust the fertility policy, the improvement of residents' fertility willingness has not reached the ideal level. The reason is that housing is necessary for life. The housing price, as the cost of living and the cost of raising children, has a very significant impact on the current residents' willingness to have children. According to the relevant literature, it can be seen that the influence of housing price on fertility intention is mostly analyzed from two aspects: crowding out effect and wealth effect. Therefore, this study relies on the micro-data of families in recent years to study the influence mechanism of housing prices on the fertility willingness of urban and rural residents. The results show that the housing price has a crowding out effect on the fertility willingness of urban and rural residents, that is, the higher the housing price, the lower the residents' fertility willingness, and other variables also have an impact on the fertility intention, such as gender, annual family income, etc. The housing price also has a wealth effect on the fertility willingness, that is, the higher the housing price, the higher the residents' willingness to reproduce. However, the wealth effect is less than the crowding out effect, so in general, in the new stage of development, the higher the housing price in China, the lower the residents' willingness to have children.

How Housing Stress Affect Health Care Costs: A Panel Data Study.

As housing prices in China continue to escalate and the limitations of the "personal unlimited liability system" for housing loans become more evident, the financial stress on families has significantly increased. This stress not only impacts the physical and mental health of family members but also results in rising health care costs. This paper presents empirical research examining how housing stress influences changes in household health care costs through a panel data analysis. The study is based on the China Family Panel Study (CFPS) database and employs a panel two-way fixed effect model alongside a mediating effect model to examine the impact of housing stress, family income, and health status on health care costs. The findings reveal a significant positive correlation between housing stress and health care costs; specifically, for every 1% point increase in housing stress, health care costs rise by 0.141. Robustness tests and propensity score matching (PSM) further validate these findings, even after addressing endogeneity issues. Mediation effect analysis indicates that for every 1% point increase in housing stress, household disposable income decreases by 1.749, and health status declines by 0.468, thereby increasing household health care costs. Heterogeneity analysis demonstrates that housing stress has a more pronounced impact on health care costs among western, eastern, urban, and rental households. The government should implement various measures, such as promoting a "personal limited liability system" mortgage policy, reducing housing prices, and ensuring equal rights to rent and purchase, to alleviate housing stress, enhance family income, and improve residents' health status. These actions would contribute to the promotion of both the housing market and medical care, supporting the sustainable development of the health care sector and ultimately improving long-term social welfare.

A neglected climate risk: The price effect of urban waterlogging

With global warming, cities are vulnerable to extreme weather, increasing the climate risk to cities worldwide. Although existing literature has examined the ex-post impacts of extreme weather, it is less clear how climate risk affects cites before extreme weather occur. To lower the risk of urban waterlogging, which is caused by extreme weather, and improve the ability of cities to adapt to extreme weather, China launched the Sponge City Project (SCP) in 2013 to manage the urban stormwater and waterlogging. Adopting the SCP pilot in China as a quasi-natural experiment, we examine the impact of the climate risk caused by urban stormwater and waterlogging on the house price with the difference-in-differences (DID) method. We find that after implementing the SCP pilot program, the house price in pilot cities increased significantly because of the improvement in cities’ resilience to climate risk. Additionally, this effect was only demonstrated in cities with a high waterlogging risk. For SCP pilot cities with lower waterlogging risk, the house price is not significantly affected by SCP implementation. This indicates that the house price in China is sensitive to the climate risk caused by the urban stormwater and waterlogging. Our findings also contribute to the understanding of the significance of the climate risk management, and provided theoretical evidence for urban governance.

Testing for stationary of housing prices in China: An examination using efficient unit root tests

Changes in housing prices affect all aspects of production and life, and have always been a hot spot of social concern. This paper uses the sequence panel selection method (SPSM) to study the time series properties of housing prices in 100 cities in China from June 2010 to December 2022. It is found that there are large differences in the stationary of housing prices in first/second/third-tier cities. Using the SPSM test method, it is found that housing prices in first-tier cities are all non-stationary series, the samples of second- and third-tier cities can be significantly divided into stable housing prices and non-stable housing prices. After further using the Fourier function to approximate the structural mutation of the data, more second-tier cities show stable housing prices, while less third-tier cities show stable housing prices. These findings provide an important decision-making basis for the government to implement regulatory policies according to local conditions based on the differential characteristics of changes in housing prices.

Analysis of Regional Differences and Influencing Factors of Real Estate Prices: An Empirical Study Based on 31 Provinces in China

Currently, the continuous rise in housing prices in China has brought about social issues regarding housing fairness. Therefore, it is of practical significance to study the influencing factors of China's real estate prices and the effects of these factors. This article first identifies ten variables that have a significant impact on housing prices through analysis, and then conducts empirical analysis separately for the eastern and central-western regions. Based on the correlation and model multicollinearity tests, two corresponding models are established. Subsequently, this article uses a multiple linear regression model for regression and uses a test set to verify the model's effectiveness, conducting quantitative analysis. Combining the analysis results, the factors that have a significant impact on housing prices in the eastern region of China are identified as the sales area of commercial housing, rental prices, and unemployment rates. In the central-western region, the factors with a significant impact on housing prices are disposable income and real estate development costs. Based on these conclusions, this article proposes relevant policy suggestions, which are expected to provide a basis for differentiated macro-control policies by the government.

Land finance, infrastructure investment and housing prices in China.

Housing prices in China have experienced rapid growth in recent decades, and land finance has long been discussed as an important factor in this growth. In this paper, we explore the interactions among housing prices, land transfer revenue and infrastructure investment from the perspective of government revenue and expenditure. Based on the panel data of 35 large and medium-sized cities in China from 2000 to 2017, the empirical results show that land transfer revenue, infrastructure investment and housing prices are causally related and result in positive feedback. The grouped regression results show that infrastructure investment has greater impacts on housing prices in eastern region cities than in the other cities. In contrast, in the central and western regions, land sales revenue has a greater impact on housing prices, indicating that cities in less-developed areas are more dependent on land finance than are those in more developed regions. Finally, we use the vector error correction model (VECM) to add control variables for robustness testing. The results show that land transfer income and infrastructure investment have a positive impact on housing prices. Our results provide some references for the stable development of housing markets in China.

Tourism development and house prices in China’s megacities – a multivariate quantile-on-quantile test

ABSTRACT The purpose of this study is to examine the relationship between tourism and house prices (HPs) in China’s megacities, namely Beijing, Chongqing, Shanghai and Tianjin using the quantile-on-quantile method. This strategy offers the best foundation for capturing the overall structure of reliance between tourism activities and HPs. With significant variances between cities and within quantiles of each China’s megacity, the data largely demonstrate a positive link between tourism and HPs for megacities. These results may particularly have significant policy ramifications for megacities.

The relationship between social media sentiment and house prices in China: Evidence from text mining and wavelet analysis

This study explores the dynamic relationship between house prices and social media sentiment in China, a housing sentiment index is constructed from social media reviews based on natural language processing techniques, and wavelet analysis is used to investigate the causal correlations from a new time-frequency perspective. We find that the sentiment index is negatively correlated with the fluctuation of house prices during the whole period, house prices and sentiment have bidirectional causality at the long-term timescale, and house prices causally affect sentiment at the short-term timescale. Furthermore, the sentiment significantly affects house prices in third-tier cities and the western regions.

From welfarism to entrepreneurialism: Impacts of the “shanty-area renovation” scheme on housing prices in China

Urban renewal is emerging around the world as a tool for spurring economic growth and social regeneration. Over the past decade, the Chinese government has rolled out a nationwide “Shanty-area Renovation” (SAR) scheme which has been characterized as strong central state intervention and local state entrepreneurism. In order to facilitate the process of SAR, the central state has adopted financial and political tools to encourage local governments to be committed to the SAR scheme. With a change in state strategy, the goal of SAR transferred from a welfare-oriented redevelopment program in the beginning to a property-led oriented redevelopment program for the purpose of de-inventorizing the real estate market, resulting in rocketing housing prices. This study adopts a fixed-effect panel regression model to explain the influencing mechanism of SAR on housing price fluctuations across the country. This research concludes that the policy design of SAR could be directed towards urban regeneration beyond property-led development, and the social, economic and environmental objectives should be integrated into the SAR process.

An Empirical Study on the Interconnections between Money Supply and Housing Price

In recent years, the COVID-19 epidemic has caused varying degrees of impact on the M2 money supply. Though the money supply side, a rise in the money supply will cause superfluous funds to access the real estate sector through various channels, which will have an impact on the real estate sector. In this paper, the VAR model is adopted to explore the mutual dynamic influence between M2 and real estate prices through variable stability test, lag selection of VAR model, convergence, impulse response and variance decomposition, etc. The analysis shows that the money supply of M2 positively influences the housing prices in China, however, the housing price has little effect on M2. In other word, the connection is unidirectional, from M2 to housing prices. Based on the consequences of concrete analysis, this paper provides some reference approaches for the progress of our real estate industry in the future.

Diversified urban housing markets and decentralized market regulation in China

PurposeIn 2016, the Chinese central government decentralized the responsibilities of housing market regulation to the municipal level. This paper aims to assess whether the decentralized market regulation is effective.Design/methodology/approachThis study first investigates the fundamental drivers of urban housing prices in China. Taking into consideration the factors driving housing prices, the authors further investigate the effectiveness of decentralized housing market regulation by a pre- and post-policy comparison test using a panel data set of 35 major cities for the years from 2014 to 2019.FindingsThe results reveal heterogenous policy effects on housing price growth among cities with a one-year lag in effectiveness. With the decentralized housing market regulation, cities with fast price growth are incentivized to implement tightening measures, while cities with relatively low housing prices and slow price growth are more likely to do nothing or deregulate the markets. The findings indicate that the shift from a centralized housing market regulation to a decentralized one is more appropriate and effective for the individual cities.Originality/valueFew policy evaluation studies have been done to examine the effects of decentralized housing market regulation on the performance of urban housing markets in China. The authors devise a methodology to conduct a policy evaluation that is important to inform public policy and decisions. This study helps enhance the understanding of the fundamental factors in China’s urban housing markets and the effectiveness of municipal government interventions.