The Impact of Urban Planning on House Prices in China

The commercial residential industry has high added value and comprehensive economic benefit so the commercial residential industry is naturally a hot-spot issue. The core issue of the commercial housing is the price. This thesis conducts the descriptive statistic analysis of residential real estate prices, urban resident income and other relevant data in China’s 30 provinces (excluding Tibet) from 1998 to 2006. The change trend and the difference feature of both the residential real estate price and the urban resident income in those regions are revealed, which is expected to make a contribution to the macro-control in China’s real estate. In recent years, the real estate market in China is growing rapidly. On the one hand, it plays a vital role in both promoting the national economic growth and improving the living standards of urban residents. On the other hand, some problems in the development of China’s current real estate market have been fully exposed, such as the overheated investment, the unbalance in supply and demand, insufficient financing channels, soaring property prices and so on. In particular, the rapid growth in the housing price has brought challenges to the sound development in both China’s real estate market and the whole national economy and it has also become a hot-spot and difficult issue in the current academia. Such relevant research as whether the rapid growth of China’s housing prices has become disjointed with resident income seriously or not and what the rules of the changes in income and housing prices in China’s different regions are is realistically significant for guiding the micro-control in China’s real estate. I. Index Selection and Disposal of Comparability The samples selected in this thesis are composed of the fluctuating residential real estate prices in China’s 30 provinces (excluding Tibet) from 1998 to 2006, urban resident income and other relevant panel data that are from various years of China Statistical Yearbook. The data of the real estate prices adopts the real estate prices in urban areas. The income indexes adopt the annual per capita disposable income of urban residents. In order to remove the impacts of the price and make indexes of various types had comparability in time series, the disposal of comparability has been conducted in indexes of different types in the thesis and their present value has been turned into the value of the constant price, namely, on the basis of the constant price in 1998, the concrete calculation method is that the housing price is deflated by the housing sales price index and the disposable income is deflated by the consumer price index of urban residents. II. Analysis of Commercial Housing Price Variance among Provinces According to the average housing prices and their growth rates in provinces from 1998 to 2006, thirty provinces, cities and autonomous regions across the country can be divided into three types in accordance with the mean and the growth rate of their average housing prices. It’s found that the provinces, cities and autonomous regions of the three types also have common in geographic areas so they can be divided into such three regions as the eastern region, the central region and the western region on the basis of their geographic areas. For the regional division of the average housing price in China, Figure 1 compares the changes in the average housing prices in the central, western and eastern regions from 1998 to 2006. It’s found that the average housing price in the east is prominently higher than those in the western and International Conference on Education Technology, Management and Humanities Science (ETMHS 2015) © 2015. The authors Published by Atlantis Press 1100 central regions and the trend of its average housing prices is on the rise. In particular, the rising trend of the average housing prices is obvious after 2004. The changes in the average housing prices in eastern and western regions are comparatively similar. However, the average prices in the central region are rising slowly while for the western region, a small decline also appears in its slightly rising process. Besides, the average housing prices in the eastern region surpass those in the western region after 2004. III. Analysis of the Differences in the Income Change among Regions Figure 1: Changes in the housing prices in the central, eastern and western regions Figure 2: Changes in the income in the central, eastern and western regions For the regional division of the average housing price in China, Figure 2 compares the changes in the income in the central, western and eastern regions from 1998 to 2006. It’s found that the per capita income in the east is prominently higher than those in the western and central regions and its trend is uniformly on the rise.

PurposeThis 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.Design/methodology/approachThis 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.FindingsThis 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.Research limitations/implicationsBecause 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.Practical implicationsAs 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.Social implicationsIn 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.Originality/valueThis 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.

This paper aims to explore the relationship between population ageing and housing price in China. We attempt to study the effect of population ageing on China's real estate market using panel data from the National Bureau of Statistics of China from 2002 to 2009 across 31 provinces or municipalities. The result indicates that population ageing has non-linear effect on housing price in China and in some major cities, for example, Beijing, Shanghai, and Tianjin, population ageing is contributing to the rise of housing prices.

After more than two decades of rapid growth, China's real estate market has gradually contracted in recent years amid economic weakness, with property prices beginning to fall sharply. Since new home sales in China primarily operate under a pre-sale system, where developers secure government land through auctions, mortgage that land to banks for development funding, and rely on bank capital alongside buyers' down payments and mortgages, the price decline not only adversely impacts banks' real estate loan risks but also leads to buyers defaulting due to insufficient collateral value, thereby amplifying systemic financial risks. Against this backdrop, our study examines the mediating role of educational attainment, measuring whether regional housing price fluctuations influence the non-performing loan ratio of commercial banks' real estate loans through educational levels. Using a bank-level panel matched to provincial socio-economic indicators, we estimate fixed effects models and implement a three-step mediation design with bootstrap inference. The evidence reveals a clear mechanism: changes in housing prices are associated with higher regional educational attainment; in turn, education is linked to greater credit expansion and higher non-performing loan ratios. Once this channel is taken into account, the direct link between housing prices and bank risk markedly attenuates, with the bulk of the overall effect operating indirectly through education. These patterns are economically meaningful, robust to alternative education proxies, and extensive resampling. The findings highlight a macroprudential paradox: while better-educated borrowers are typically safer at the micro level, improvements in human capital can, at scale, amplify risk-taking and balance-sheet exposure. Supervisors should therefore monitor human capital trends alongside collateral dynamics and incorporate them into early warning systems and the calibration of borrower and capital-based tools, so that bank risk assessments remain informative even in a housing market downturn.

Based on the least squares model, this study conducted an empirical analysis of price fluctuations in China's real estate market and explored the impact of macroeconomic variables and policy factors on real estate prices. Through the analysis of factors such as GDP, residents' disposable income, inflation rate, unemployment rate, interest rate and land supply, the results show that economic growth and the increase in residents' income level have significantly promoted the rise in housing prices, while the increase in inflation rate, unemployment rate and land supply has suppressed the rising trend of housing prices to a certain extent. The model test results show that the constructed model has good robustness, conforms to the structural characteristics of real estate market data, and the analysis results are reliable. Studies have shown that economic growth and the increase in residents' income are important driving forces for house price increases, while reasonable policy regulation and land supply management have a positive effect on controlling house price fluctuations. This study provides a quantitative basis for understanding the causes of price fluctuations in China's real estate market and provides a scientific theoretical reference for the formulation of relevant policies.

Since the beginning of 1998, China has begun its gradual and but incremental implementation of housing reform nationwide. Over the last decade, residential housing is leading the growth and expansion of China's real estate market. There is a need to understand how housing prices are spatially structured and differentiated in metropolitan areas in order to provide relevant information for policy makers who aim to regulate overheated urban housing prices in China. In this paper, we attempt to use a geographically weighted regression model. According to the study, we find that the geographically weighted regression model is far better than the traditional ordinary least square model revealing structural determinants of housing price.

This article predicts potential future trends in Chinas housing market by analyzing past housing price fluctuations and the bubble economy in Japan during the 1980s. The study focuses on the price of second-hand homes rather than new houses. Through a detailed analysis of various data and drawing lessons from Japans experience, the paper concludes that housing prices in China are likely to continue declining in the future. Furthermore, there is a significant possibility of a bubble economy bursting, similar to what occurred in Japan. The paper warns of this impending crisis, urging stakeholders to prepare in advance. Given the escalating regulatory interventions and economic challenges confronting China's real estate sector, the likelihood of a housing bubble rupture poses significant risks to the broader economy. Consequently, it is imperative to implement preemptive strategies at this juncture to alleviate the prospective economic repercussions that may ensue from such a crisis.

Over these years, China's real estate industry has achieved a rapid development.However, high house prices have become a hidden danger for the economy.Based on previous studies, this article selects three representative variables to build the vector error correction model (VECM) to test the impact of monetary policy on house price fluctuations Empirically.The result shows that there is a long-term stable relationship between monetary policy and house prices, and the monetary policy has a significant impact on house prices.To achieve the objectives of lowering house prices, central bank could combine administrative measures with the appropriate monetary policies.

This paper investigates the convergence and ripple effects of regional house prices in China over 1998 to 2010 by using 35 main capital cities’ house price indexes, by developing some innovative econometrical approaches—the pairwise Granger causality tests and the panel regression models. One of this paper’s originalities is the first attempt to apply above approaches into the study of regional house prices in China; and the other originality is to add the distance factors into the house price convergence study. Generally, the empirical results suggest that there is some evidence of ripple effects but not convergence between regional house prices in China; and house price shocks in some core cities ‘ripple out’ to other cities, wherein Beijing, Hangzhou, Guangzhou and Shenzhen are original regions of nationwide house price swings. Keywords Convergence, Ripple Effects, Pairwise Granger Causality test, Panel Regression Model, Regional House Prices

Foreign direct investment in China's real estate market

Different intergenerational fertility levels affected by the family planning policy under such altruistic behavior will inevitably affect real estate prices. This paper studies the effect of different intergenerational fertility levels on real estate prices under the parental altruistic behavior model with Chinese characteristics by constructing an Overlapping Generation Model (OLG) with intergenerational wealth transfer. The empirical results show that the lower the intergenerational fertility level of the middle-aged generation, the higher the average wealth level transferred to the youth generation, and the higher the real estate price. This result shows that, unlike the high fertility rate of popular cognition, the low fertility rate of the middle-aged generation under the influence of the family planning policy and the altruistic behavior of the Chinese parents are the important reasons for the current high housing prices. This paper reveals the relationship between China's population policy and real estate price, and can guide the judgment of China's real estate market in the future.

In recent years, agent-based modeling and simulation (ABMS) methods have attracted the people's attention in the field of management science and is becoming a important tool for solving complex problems. In this paper, the Bayesian network is introduced to ABMS methods, and a multi-agent system of China's real estate market is proposed based on the Bayesian network with uncertain information, which has the abilities of online learning and effect describing for group behavior. China's real estate market ecology is simulated by the system. Simulation results can accurately reproduce the operation of China's real estate market, so to prove the effectiveness of the model. Through simulating for related parameters, some valuable findings on operation rule of estate market are obtained. The model and method developed in the paper provide reference for studying China's real estate market rules.

Since the reform and opening up, China's real estate industry has prospered rapidly and has become an important force driving rapid economic growth and promoting urbanization. In recent years, China's real estate industry has entered an inflection point of development, and real estate bubbles and cyclical sharp fluctuations in the real estate market have occurred from time to time. Behavioral finance has provided a new research direction for how to explain this fluctuation. Based on this, this essay uses the classic anchoring effect theory in behavioral finance theory to study the existence and characteristics of anchoring effect in China's real estate market from the micro level, and explains the entire mechanism through three applications. The first application empirically tested the existence of the anchoring effect in China's real estate market, and analyzed the difference between the anchoring effect in the eastern and western regions of China. It verified that the decision of housing prices in the central region was affected by the anchoring effect of the micro subject, while the anchoring effect in the eastern and western regions was not significant. The second application analyzed Hong Kong's secondary residential market, and a statistical model including anchoring effects was also presented in order to study the dynamics of house prices. The third application provides an improved Hedonic model, which combines various literature data to study the influence of age, growth area and other characteristics of home buyers on real estate prices under the anchoring effect.

China's real estate market involves many main parties, different interests, and complicated relationship. The regulations on real estate market should not only consider the main interests of the parties involving, but also consider the economic trend as whole, so it's evitable that the regulation encountered the dilemma. In this article, by including the central government, local government, real estate developer, bank, and assessment agencies in the analysis framework and building the five parties game model, we explore a balanced solution through taking the different interest groups into the consideration. The result shows that fluctuation in the house price relates to factors like interest rate, construction of affordable housing, and the activity of assessment agencies, etc., therefore, regulating the housing price have great impact on the economy as whole. Finally, we interpret the current regulation dilemma and provide policy recommendation for the government.

At this stage, broadening the consumer market, upgrading the consumption system and gradually establishing a consumption-led development concept are key factors in promoting high-quality economic development. At the same time, China's macro economy is also experiencing another test. The rapid development of China's real estate market in recent years has attracted a large number of investors, and real estate prices have produced irrational and substantial increases. Behind the boom of the real estate market is a social system crisis driven by profiteering and the growing seriousness of real estate financial bubble. So exploring the mechanism of the influence of real estate prices on the upgrading of residents' consumption is important for the current stage of China. Therefore, it is important to investigate the mechanism of real estate price impact on consumer upgrading for the coordinated development of real estate industry and national economy. In this paper, we analyze and examine the theory on the consumption improvement by the literature survey method. We also summarize the present research on the correlation and the influence mechanism of the real estate price and the consumption improvement and choose the index which reflects the present state of the real estate industry and the consumption of the inhabitant. Besides the input indicators that qualitatively manage the impact of housing prices on the improvement of residents' consumption, we first use the descriptive statistics method to understand the level of the Chinese real estate market and improve consumer spending. Based on this, the descriptive statistical method is applied to define the current state of China's real estate market and the level of improvement in consumption, and to define the standard for improving consumption in China. On the other hand, based on the spatial and spatial spillover points of view, we use spatial analysis framework combined with exploratory spatial data analysis and GIS to investigate spatial correlation between consumption structure and housing price, and accurately reflect the spatial clustering status of the index by drawing. Moran dispersion plot and Lisa cluster plot, then the spatial Darwinian model, are used to investigate the impact of real estate prices on the increase in occupant consumption from a macro perspective.