Housing Price and Population Growth across China: The Role of Housing Supply

Wang, Hongbo; Rickman, Dan S.

doi:10.1177/0160017619835885

Cited by 5 publications

(2 citation statements)

References 53 publications

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“…Researchers generally believed that housing prices were affected by the market supply and consumer demand. Wang and Rickman (2019) conducted an empirical test using a spatial equilibrium growth model in China from 2002 to 2015 to determine the role of housing supply growth in provinces, autonomous regions, municipalities and major cities' housing prices and population growth. The eastern part, especially in Shanghai, Ningbo, Qingdao and Xiamen, had the smallest growth in housing supply.…”

Section: Resultsmentioning

confidence: 99%

Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database

Jotikasthira

2022

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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.

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Section: Resultsmentioning

confidence: 99%

Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database

Jotikasthira

2022

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“…These results are consistent with many existing studies. For instance, Meng et al [ 53 ] discovered that the disparate distribution of income, welfare, and infrastructure across various urban regions has led to cross-regional population migration, subsequently elevating housing prices in China’s first-tier cities. Han and Lu [ 5 ], along with Wang and Richman [ 53 ] highlighted that constrained land supply in first-tier cities, paired with robust residential demand, has fostered a persistent divergence in housing prices between China’s first-tier cities and smaller, medium-sized cities.…”

Section: Housing Price Bubble Measurementmentioning

confidence: 99%

Do high house prices promote the development of China’s real economy? Empirical evidence based on the decomposition of real estate price

Fan,

He,

Hao

et al. 2024

PLoS ONE

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Moderate rising of house prices are beneficial to the economic development. However, over high house prices worsen the economic distortions and thus hinder the development of the real economy. We use the stochastic frontier models to calculate the fundamental value in the housing in Chinese large and medium cities, and then obtain indexes which could measure the house prices’ deviations from the fundamental value. With the macroeconomic data in the city-level, this paper empirically investigates the effects of the house prices’ deviations on macro-economic variables like consumption, investment and output. The study reveals that the housing bubble exists in most Chinese cities, and first-tier cities fare the worst. House prices over the fundamental value, which could increase the scale of real estate investment, bring adverse impacts on GDP, as it causes declining civilian consumption and discourages real economy’s investment and production. The encouragement and the discouragement on macroeconomy caused by house prices’ deviation from its basic value take turns to play a key role in the process of China’ eco-nomic growth. In the early stage of China’s economic growth, the encouragement effect predominates. As urbanization and industrialization gradually upgrade to a higher level, the discouragement effect takes charge.

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Community formation in talent worker housing: the case of Silicon Valley Talent Apartments, Shenzhen

MacLachlan

Gong

2022

Urban Geography

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Housing Price and Population Growth across China: The Role of Housing Supply

Cited by 5 publications

References 53 publications

Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database

Factors affect the housing prices in China: a systematic review of papers indexed in Chinese Science Citation Database

Do high house prices promote the development of China’s real economy? Empirical evidence based on the decomposition of real estate price

Community formation in talent worker housing: the case of Silicon Valley Talent Apartments, Shenzhen

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