中国各地区人口特征和房价波动的动态关系
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摘要
本文分析了人口特征、金融市场和房地产市场三者的相互影响机制,基于2002-2015年我国大陆31个省、自治区、直辖市的年度数据,建立了面板平滑转换模型,将人口密度作为异质变量构建计量模型,研究房地产市场的非线性影响因素,及各地区人口特征对房价波动的影响机制。实证结果表明:人均GDP对房价的影响随人口密度增加呈现非线性提升效应;人口密度小的地区,M2存量对房地产价格有正向影响;当人口密度较小时,地区中老年人口占比越大,房价下降的可能越大,反映了房地产"年轻人推动房价上涨"的现象,但是极少人口密度比较大城市例外。
This paper builds up a panel smoothing transition model based on the study of interactive mechanism among the demographic characteristics, financial market and real estate market and the 2002-2015 annual data from 31 provinces, autonomous regions and municipalities in mainland China. Furthermore, taking the population density as a heterogeneous variable, an econometric model is constructed to study the non-linear factors affecting the real estate market, and the impacts of the Chinese provincial demographic characteristics on the housing price volatility. The results show that as the population density increases, the impact of per capita GDP on housing prices exposes an escalating effect in a non-linear way. In a sparsely populated city, a real estate price increase looks more like money-driven than that in a densely populated city. In a sparsely populated area, the more the aged and middle aged people, the more the housing price is inclined to edge down, reflecting the factual tendency of real estate prices driven by the young generation, but being an exception for a few most populated metropolitan cities.
This paper builds up a panel smoothing transition model based on the study of interactive mechanism among the demographic characteristics, financial market and real estate market and the 2002-2015 annual data from 31 provinces, autonomous regions and municipalities in mainland China. Furthermore, taking the population density as a heterogeneous variable, an econometric model is constructed to study the non-linear factors affecting the real estate market, and the impacts of the Chinese provincial demographic characteristics on the housing price volatility. The results show that as the population density increases, the impact of per capita GDP on housing prices exposes an escalating effect in a non-linear way. In a sparsely populated city, a real estate price increase looks more like money-driven than that in a densely populated city. In a sparsely populated area, the more the aged and middle aged people, the more the housing price is inclined to edge down, reflecting the factual tendency of real estate prices driven by the young generation, but being an exception for a few most populated metropolitan cities.
引文
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[14]Bernanke B., Gertle r M. and Gilchris t S..The Financial Accelerator and the Flight to Quality[J].Review of Economics and Statistics,1996,(78):1-15.
[15]Kiyotaki N. and Moore J..Credit Cycles[J].Journal of Political Economy,1997,(105):211-248.
[16]Iacoviello M. and Pavan M..Housing and Debt over the Life Cycle and over the Business Cycle[J].Journal of Monetary Economics,2013,(60):221-238.
[17]Luukkonen R., Saikkonen P. and Ter?evirta T.Testing linearity against smooth transition autoregression models[J].Biometrika,1988,75(3):491-499.
[18]Colletaz G. and Hurlin C..Threshold effects of the public capital productivity: an international panel smooth transition approach[M].Document de recherche du LEO,2006,01.
[2]Mankiw N. G. and Weil D. N..The baby boom, the baby bust, and the housing market A reply to our critics. NBER Working Papers,1989,19(2):235-258.
[3]闫磊.房地产价格影响因素分析:基于1997-2008年面板数据的实证研究[J].商业文化,2011,(1):138-138.
[4]Pages J. and Maza L.Analysis of House Prices in Spain. Banco de Espana Working Papers,2003:No.0307.
[5]McQuinn K. and OReilly G..Assessing the Role of Income and Interest Rates in Determining House Prices[J].Economic modelling,2008,(25):377-390.
[6]Abelson P., Joyeux R., Milunovich G., and Chung D..Explaining House Prices in Australia:1970-2003[J].Economic Record,2005,(81):96-103.
[7]Posedel P. and Vizek M..House Price Determinants in Transition and EU-15 Countries[J].Post-Communist Economies,2009,(21):327-343.
[8]Meen G..The Time-series Behaviour of House Prices: A Transatlantic Divide[J].Journal of Housing Economics,2002,(11):1-23.
[9]Gallin J..The Long-run Relationship between House Prices and Incomes: Evidence from Local-house Markets[J].Real Estate Economics,2003,(34):417-439.
[10]Annett A..House Prices and Monetary Policy in the Euro Area.IMF country report,2005:No.05/266.
[11]况伟大.利率对房价的影响[J].世界经济,2010,(4):134-145.
[12]Nishimura K..How to Detect and Respond to Property Bubbles[Z].Presentation at the Reserve Bank of Australia-BIS Research Conference “Property Markets and Financial Stability”, Sydney, 21 August,2012.
[13]朱太辉,张晓朴.金融危机的人口-信贷-房价模型[J].金融评论,2015,(5):31-44.
[14]Bernanke B., Gertle r M. and Gilchris t S..The Financial Accelerator and the Flight to Quality[J].Review of Economics and Statistics,1996,(78):1-15.
[15]Kiyotaki N. and Moore J..Credit Cycles[J].Journal of Political Economy,1997,(105):211-248.
[16]Iacoviello M. and Pavan M..Housing and Debt over the Life Cycle and over the Business Cycle[J].Journal of Monetary Economics,2013,(60):221-238.
[17]Luukkonen R., Saikkonen P. and Ter?evirta T.Testing linearity against smooth transition autoregression models[J].Biometrika,1988,75(3):491-499.
[18]Colletaz G. and Hurlin C..Threshold effects of the public capital productivity: an international panel smooth transition approach[M].Document de recherche du LEO,2006,01.
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