Housing Risk and Its Influence on House Price: An Expected Utility Approach

Wang, Yehui; Liu, Jianxu; Tang, Yuxuan; Sriboonchitta, Songsak

doi:10.1155/2020/3943676

Cited by 5 publications

(22 citation statements)

References 44 publications

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“…Wang et al. (2020) studied the impact of the housing market risk on housing prices from theoretical and empirical aspects.…”

Section: Resultsmentioning

confidence: 99%

“…Next, housing tax is an essential factor that affects housing prices. Wang et al (2020) studied the impact of the housing market risk on housing prices from theoretical and empirical aspects. Taking the Beijing real estate market as an example, Zhang and Wang (2020) analysed the impact of purchase restrictions and monetary policies on the housing prices in Beijing.…”

Section: Administrative Dimensionsmentioning

confidence: 99%

“…This reflects China's economic growth and has become the focus of attention from all walks of life (Ohno and Shimizu, 2015). Exploring the behaviour mechanism and accurately predicting housing prices is critical in making tenure choice decisions (Wang et al. , 2020).…”

Section: Introductionmentioning

confidence: 99%

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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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“…Wang et al. (2020) studied the impact of the housing market risk on housing prices from theoretical and empirical aspects.…”

Section: Resultsmentioning

confidence: 99%

Section: Administrative Dimensionsmentioning

confidence: 99%

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

Jotikasthira

2022

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“…The lowest correlation between the new C R and the S P M is -0.45 at Period 6. Since (i) house prices are usually affected by many economic factors [e.g., Wang et al (2020)], but our S P M was only derived from the linkage network; and (ii) C R are capital returns, but S P M are simulated probabilities, corre- is sharply increased, and risk-defusing capability is much weaker; if housing-market linkage is approximately doubled, risk-defusing capability almost disappears; on the other hand, if overall housing-market linkage decreases by 50%, the probability of housing-market collapse is significantly reduced, but risk-defusing capability (slope) is not significantly changed compared with the solid line. The probability of housing-market collapse is very sensitive to housingmarket linkage.…”

Section: Spatial Housing-market Consequencesmentioning

confidence: 99%

Linkage structure of China’s housing market and its risk-defusing capability

et al. 2021

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There have been many recent fears of severe house-price decreases in some provinces in China causing a nationwide collapse of the housing market. Therefore, this paper aims to clarify the linkage structure of China's housing market and its risk contagion routes. Given monthly data of provincial housing and stock-market capital returns from 2001M01 to 2019M12, on the basis of graph theory, this paper first explores the linkage structure of provincial housing markets. Relying on the linkage structure, this paper then simulates the effect of unexpected negative shocks from the stock market on the probabilities of a housing-market collapse based on the epidemic model. The results show that (i) consistently with practical evidence, the probability of housing-market collapse is relatively high in the southwest of China and (ii) reducing housing-market linkage, such as through a blocking mechanism, to prevent collapse is helpful. IntroductionIn recent decades, house prices in most developing and developed countries have been sharply increasing. For example, the average house prices in China were 2409.61 and 9208.56 CNY/m 2 in 2001Q1 and 2019Q4, respectively (CNY 1 ≈ USD 0.15). This is a 282.16% nominal inflation during the last 19 years or 14.85% annual growth on average. However, after 2018, the growth rate of house prices in Communicated by Vladik Kreinovich.

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“…(Semenenko & Yoo, 2019) Y. Wang, J. Liu and others assume that House price is affected by households' expectations of future house price trend and volatility, where the expected volatility of housing capital return, indicated by variance, is defined as the housing market risk. (Wang et al, 2020) N. K. Kishor and H. A. Marfatia study the dynamic relationship among house prices, income and interest rates in 15 OECD countries. They find that any disequilibrium in the long-run cointegrating relationship among these variables is corrected by the subsequent movement in house prices in most of these countries.…”

Section: Literature Reviewmentioning

confidence: 99%

Financial and Strategic Pricing Analysis in the Development Market Using an Econometric Model

Akhmetzianov¹,

Sokolov²

2020

IJFR

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This article demonstrates the use of a financial and econometric model with dummy variables to calculate the average price in the real estate market. The average price is used in the model for calculating project effectiveness and allows you to evaluate the profitability of the project at the construction planning stage. The number of rooms, the presence of a balcony, the number of sides of the windows and the number of floors were used as independent variables. A model with these factors showed qualitative estimates and can be applied for the purpose of forecasting prices in standard projects in the Russian real estate market.

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Housing Risk and Its Influence on House Price: An Expected Utility Approach

Cited by 5 publications

References 44 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

Linkage structure of China’s housing market and its risk-defusing capability

Financial and Strategic Pricing Analysis in the Development Market Using an Econometric Model

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