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This paper aims to examine the evolution of house prices in China and especially the effects of different financing channels on China’s house prices.

The author use the own theoretical framework and proceed to test the testable hypotheses by using the autoregressive distributed lag bounds test approach for cointegration analysis and the unrestricted error correction model. Quarterly time series data from Q1 2002 to Q2 2016 are used.

The results suggest that in the short run, bank loans to real estate development and scale of shadow banking have significant positive effects on house prices. In the long run, the scale of shadow banking and disposable income affects house prices positively and significantly.

This study provides more insights into how and to the extent different financing channels affect China’s house prices, particularly the impact of shadow banking on the house prices.

This paper aims to explore the sources of China's property boom from 2000 to 2009. The basic research hypothesis is that the property boom is largely associated with Chinese local governments’ incentive structure which prioritizes GDP growth for evaluating their performance.

Based on the fixed effects panel data regression model of 35 major Chinese cities, the determinants of property investment, property price and land sale price are identified. In particular, the roles of local governments in boosting the property boom are discussed.

Property investment is driven by accelerating urbanization process, easier availability of bank loans and more housing sales. Meanwhile, higher disposable income, more housing sales and increasing property investment are identified to mainly account for the property price escalation. It is further demonstrated that increasing property price has positive effect on land sale price. Local governments have quickened the urbanization process, released more bank loans and sold more land through public auction to support property development, sustain property price and increase land sale revenue. Such behaviour is closely related to Chinese local governments’ incentive structure.

Previous studies have not empirically tested the relationships between local governments’ pursuits for higher revenue in the urban land market and China's magnified and sustained property boom over the past decade. A prosperous property market is conducive to economic development and hence local officials’ chances of political promotion.

The purpose of this study is to estimate different data models on house prices using statistical models and the variables which are controlled by real estate policy.

This study used several statistical techniques, such as Vector auto-regression (VAR), Johansen co-integration and variance decomposition, which aim to assess the significant effect of macroeconomic factors on Chinese house prices.

The results show that land supply and other variables have negative effects on house prices. The results also indicate that financial mortgages for real estate have positive effects on house prices and the area of vacant houses as well as the area of housing sold.

This study only covers three cities in China because of limitations of data for other cities.

This study proposes policy suggestions according to the empirical results obtained.

China's real estate market is rampantly expanding. The purpose of this paper is to examine the factors underpinning China's real estate price escalation from 1998 to 2009.

Cointegration approach, vector error correction model and Granger causality test are adopted to analyze whether stable and long‐run equilibrium interactions exist between housing prices and key macroeconomic variables, such as CPI, land sale and GDP.

Cointegration analysis shows long‐term equilibrium between real estate price (HP) and CPI or GDP, but not land sale. A bilateral Granger causality is observed between CPI and HP. However, GDP does not Granger cause HP, indicating personal gain (disposable income) does not catch up with national gain (GDP) in China, or “Guojinmintui” (national gain outpaces personal gain). Neither is there a feedback effect from HP to GDP, indicating housing price appreciation does not result in immediate capital gain or speculations in housing purchase. Besides, lack of cointegration relationships between HP and land sale is probably caused by restrictive polices on land supply.

This paper represents the first attempt to adopt cointegration approach and Granger causality tests to examine the real estate price escalation in China using national monthly data. Econometric analysis and subsequent policy discussion suggest that real estate price is driven by both economic and institutional factors. In particular, “Guojinmintui” is a fiscal issue while capital gain is a monetary issue. Together with land market policies, these institutional factors significantly contribute to the price escalation.

This paper aims to explore the factors that affect housing prices as per Chinese articles indexed in the Chinese Science Citation Database (CSCD). There were different foci regarding what drove housing prices in China in Chinese articles, and international journal articles in English. As most previous English articles only threw light on international research, it motivated the researchers to systematically review Chinese literature’s factors that affected housing prices in China.

This paper reviewed housing price research articles indexed in the two largest Chinese academic research databases: the CSCD and China Knowledge Infrastructure Engineering Database (CNKI.NET). It systematically collected the data and adopted descriptive analysis techniques and synthesis.

This research reviewed the literature published from 2015 to 2020 and revealed some unique factors affecting China's housing prices. For example, research focused on administrative aspects such as macroeconomic regulation and control (often known as macro control). Authors of Chinese articles suggested that the two-child policy affected housing prices, which differed from that in the English journal articles. The research results implied that researchers should read top Chinese journals on top of good international journals when they study China's real estate market in the future.

Because the domestic real estate market started late, domestic real estate transaction data and real estate-related statistics are more difficult to obtain. The research is mostly based on the relationship between supply and demand, government policy and individual consumer factors, and the sample has a short time span.

As China is a planned economy country, administrative factors are one main factor that affects the housing price. There were a significant number of articles in Chinese that considered this factor to be the main driver of the real estate price. It included government investment and macro-control, i.e. direct government intervention to cool down the overheated economy. Yet, there are few English articles that threw light on this factor including the commodity housing supply and government behaviour that affect housing price. The second-child policy, which is unique in China, also played an important role in the determination of the housing price. In the articles indexed in CNKI, the second-child rate, willingness to have a second child or having a second child were mentioned in the Chinese articles but not the English ones.

In this paper, the economic, social, administrative and environmental factors were summarised, which basically covered all the factors affecting housing prices. The administrative factors were a special group of factors that affect the housing price because of the country's planned economic system. Secondly, it provided useful information to real estate development enterprises in China. To make a correct investment and management decision, real estate development enterprises must understand the actual situation and possible problems of the industry. In this study, we analysed the research literature on the real estate industry in China for the period from 2015 to 2020 one by one and determined the influencing factors of the housing price, which provided references for effective cost control. Thirdly, it allows the public to understand and grasp the real estate industry. As the housing price has been continuously increasing, the public pays increasing attention to the real estate industry. Through the literature analysis of the impact of real estate prices, this paper revealed the elements of house price expenses, which makes it convenient for ordinary people to understand the real estate industry.

This study allows foreigners who do not know Chinese to know more about factors that drove housing prices from the Chinese perspective. It also provides insights to overseas developers who wish to enter the property market in China. The results can be generalised to other non-English-speaking real estate research.

To explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a combination of conditional Granger causality and network analysis.

Although housing market networks have been well discussed for different countries, the question of housing market networks in China's major cities based on the conditional causality perspective has yet to be answered.

We discover that second-tier cities are more influential than first-tier cities. Although the connectivity of the primary housing market is more complex than the diversified connectivity observed in the secondary housing market, both markets are scale-free networks that exhibit high stability. Moreover, we reveal that geographic conditions and economic development jointly determine the housing market's modular hierarchical structure. Our results provide meaningful information for both Chinese policymakers and investors.

By excluding the influence of other cities, our conditional Granger causality identifies the true casual relation between cities' housing markets. Moreover, it is the first paper to consider the primary housing market and secondary housing market separately. Specifically, Chinese prefer new house rather than second-hand house from both speculative and self-housing. Generally speaking, the new house price is lower than the second-hand house price since the new house is off-plan property. Therefore, understanding the difference between primary and secondary housing markets will provide useful information for both policymakers and speculators.

This study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.

This study uses a novel bootstrap autoregressive distributed lag (ARDL) testing to empirically analyze the short and long links among the tested variables.

The ARDL estimations demonstrate a positive impact of oil price shocks and real income on housing market prices in both the phrases of the short and long run. Furthermore, the results reveal that gold price shocks negatively affect housing prices both in the short and long run. The result can be attributed to China’s housing market and advanced infrastructure, resulting in a drop in housing prices as gold prices increase. Additionally, the prediction of housing market prices will provide a base and direction for housing market investors to forecast housing prices and avoid losses.

To the best of the authors’ knowledge, this is the first attempt to analyze the effect of gold price shocks on housing market prices in China.

Due to greater returns to high skill and desirable amenities, high-skilled workers are increasingly agglomerating in metropolitan areas and form path dependence. This chapter explores whether the land supply policy of China constraining big cities' urban construction land quota strengthens the spatial divergence of human capital. Using city-level land supply data, population census data, and land transaction micro data, we find that the higher the degree of a city's land supply lagging behind land demand, the greater the enlargement effect of the initial share of population with college degrees on the increase in share of population with college degrees. Further research reveals that the main mechanism causing this phenomenon is the rapidly rising housing prices hindering low-skill labor flows to big cities.

In 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.

This 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.

The 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.

Few 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.

This study aims to merge the world’s proven ways of housing finance, including musharakah mutanaqisah, housing cooperatives and real estate crowdfunding, to present an alternative housing unaffordability solution based on the Islamic finance principle. It is intended to reduce the burden of funding for both sides (consumers and developers) and create win–win chances for all stakeholders, including intermediaries. By moving away from debt financing and merging the features of crowdfunding and cooperative, it is hopeful that the burden of home ownership will no longer be the case.

This paper presents the opinions of potential Chinese homebuyers (minority Muslims and most non-Muslims) and a few industry experts toward the proposed model via a mixed research method.

According to the findings, the majority of respondents agreed with the proposed paradigm. Just concerned that China’s lack of community culture and trust could pose a major threat to implementation. However, this paper argues that Chinese local governments may perform pilot testing in places where Islamic culture is prevalent. Their unique community culture and fundamental understanding of Shariah law may affect the viability of the proposed model.

The proposed model would increase the applicability of Islamic finance as a way of protecting the social order of communities in the spirit of upholding justice and fairness. A new type of housing loan based on musharakah mutanaqisah may squeeze out the real estate bubble and provide stakeholders with a multidimensional investment channel. In particular, the study identifies the impact of Chinese Islamic financing on government and cultural needs. It presents possible challenges for implementing the proposed model in reality and helps bridge the gap between theory and practice.