Exploring determinants of housing prices: A case study of Chinese experience in 1999–2010

Zhang, Yanbing; Hua, Xiuping; Liang, Zhao

doi:10.1016/j.econmod.2012.06.025

Cited by 105 publications

(60 citation statements)

References 41 publications

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“…The central government deemed the free market as the avenue for housing allocation in 1998. Since then, Chinese housing prices grew explosively and became the major investment focus [69]. Our research echoed this trend by revealing that all three real-estate businesses had been spatially clustered in the last two decades.…”

Section: Discussionsupporting

confidence: 58%

“…Our research echoed this trend by revealing that all three real-estate businesses had been spatially clustered in the last two decades. Although the central government recently made intervention policies including higher mortgage down payment, pilot property tax, prohibitions on purchasing multiple houses by the same household, and the suspension of non-local purchasing [70], local governments have strong incentive and capability to generate significant revenue from the sale of land-use rights [69]. Thus, developing land (especially agricultural use) into dwellings in markets is still favored locally, and will continue under supportive local government's urban development plan.…”

Section: Discussionmentioning

confidence: 99%

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Spatiotemporal Agglomeration of Real-Estate Industry in Guangzhou, China

2017

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Abstract:Real estate development is critical to healthy economic growth and regional development. Using real-estate data in Guangzhou, China from the 1970s to 2015, we examined the spatiotemporal agglomeration and evolution of Guangzhou's real estate industry with spatial and spatiotemporal techniques. This study shows that real estate businesses were initially agglomerated in the city center with socioeconomic advantages, and later spread into suburbs as new growth foundations. We also found that different business types, depending on their functions, evolved and agglomerated in different time periods. The findings provide valuable support to the formulation of effective government policy and the management of real estate enterprises in China.

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Section: Discussionsupporting

confidence: 58%

Section: Discussionmentioning

confidence: 99%

Spatiotemporal Agglomeration of Real-Estate Industry in Guangzhou, China

2017

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“…For instance, Ren et al (2012) found that the economic theory of demand and supply could explain the relative price of urban housing in China satisfactorily. Shen (2012), Zhang et al (2012) and Zhang (2013) also found that housing price was relatively reasonable because the affordability in China was high due to higher growth rate and low interest rates and disposable incomes of urban residents was vital.…”

Section: The Predicted Results Of Impulse Response Functionmentioning

confidence: 98%

“…This conclusion agrees well with previous studies, although there are presently a few reports of commercial housing price fluctuations relevant to the present work in China. Some academic literatures studied the determination of nominal housing price and found that disposable incomes or monetary factors were really at work (Shen, 2012;Ren et al, 2012;Zhang et al, 2012;Zhang, 2013). For instance, Ren et al (2012) found that the economic theory of demand and supply could explain the relative price of urban housing in China satisfactorily.…”

Section: The Predicted Results Of Impulse Response Functionmentioning

confidence: 99%

Numerical Computation of the Fluctuations of Commercial Housing Prices and Disposable Incomes of Urban Residents Based on the VAR and LSE Models

Zhang¹,

Liu²

2015

J. of Software Engineering

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To ensure the healthy development of the national real estate industry and explore the determinant of commercial housing prices in China, the correlation between fluctuations of commercial housing prices and disposable incomes of urban residents was analyzed and predicted with annual time series data based on Vector autoregressive (VAR) model. The study dealt with the bifactorial data and found positive correlations in both the empirical VAR model and the Least Squares Estimation (LSE) model. The Granger causality test and Cointegration tests were next carried out to verify the rationality of the empirical VAR model and its settings. The present study revealed that the urban resident disposable income was one of the crucial impact factors influencing the rising commercial housing prices. There exists a positive correlation or convergence relationship between the development trends of the commercial housing prices and the disposable incomes of urban residents on the basis of a fifteen years prediction by impulse response function. Finally, some comments and suggestions were put forward relevant to the corresponding policy adjustment and decision making of commercial housing market in view of the present empirical study.

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“…Liang and Cao (2007) investigate the relationship between property prices and bank lending for the case of China over the period 1999-2006, and find that there is unidirectional causality running from bank lending to property prices. Zhang et al (2012) show that Chinese house prices can also be linked to changes in the macroeconomic variables using a nonlinear autoregressive moving average with exogenous inputs approach combined with the vector error correction model over the period 1999-2010. Their estimations show that the mortgage rate, money supply growth rate, producer prices and the real exchange rate are key drivers of Chinese house prices while surprisingly they do not detect a significant role for personal disposable income, international trade or real incomes.…”

Section: Literature Reviewmentioning

confidence: 99%

Estimation of bubble dynamics in the Chinese real estate market: a State space model

Gabrieli

Pılbeam

Wang

2017

Int Econ Econ Policy

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This paper analyses the existence of a bubble in the Chinese real estate market and examines its driving factors with a state-space model. The model considers macroeconomic and real estate time series variables as inputs and employs a Kalman filter to obtain an estimated fundamental price using demand and supply for Chinese real estate. We then measure the deviation between actual and estimated fundamental real estate prices to test for the existence of a bubble. We find evidence for the existence of a bubble especially post 2010, when the deviation ratio is found to be significantly higher with a peak of 80% in 2012. Our estimation of overvaluation is generally much higher than in other studies.

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Exploring determinants of housing prices: A case study of Chinese experience in 1999–2010

Cited by 105 publications

References 41 publications

Spatiotemporal Agglomeration of Real-Estate Industry in Guangzhou, China

Spatiotemporal Agglomeration of Real-Estate Industry in Guangzhou, China

Numerical Computation of the Fluctuations of Commercial Housing Prices and Disposable Incomes of Urban Residents Based on the VAR and LSE Models

Estimation of bubble dynamics in the Chinese real estate market: a State space model

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