摘要
1998年我国房地产业市场化以来，房地产市场得到了迅猛发展，为带动相关产业发展、拉动整个国民经济增长及改善人民生活质量做出了不可替代的贡献，成为了我国国民经济发展中重要的基础性产业。然而，房地产关系国计民生，其价格水平的高低不但决定着房地产行业自身能否健康发展，同时对关联行业的发展、经济发展、居民生活质量、国家金融安全等方面产生影响，特别是对社会公平与稳定将产生巨大影响。值得注意的是，近年来部分地区房地产价格涨幅远远超过其他省份，各地区房地产价格存在明显的差异。房地产价格的区域差异不仅表明了不同地区房地产市场发展程度的差异，更反映了不同地区的经济发展水平和人民生活质量，而过度的差距将极有可能进一步引发全社会的公平和稳定。因此，深入剖析房地产价格区域差异产生的根源，对于客观准确认识房地产市场发展的区域不平衡是至关重要的，对于我国房地产市场健康有序的发展具有现实意义。
基于上述，本文以房地产市场发展现状为背景，以我国房地产市场价格为研究对象，在总结现有经验研究的基础上，分析了我国房地产市场价格演变的地区性差异，结合我国房地产市场状况运用计量方法甄别我国房地产市场价格区域差异的影响因素，在此基础上，构建我国房地产市场发展水平指标体系，对我国房地产市场进行重新划分，以不同区域为研究对象，运用微观计量经济学方法对我国房地产市场价格的地区性差异特征、阶段变化特征和波动特征及其区域差异进行实证检验。本文的主要内容和结论如下：
首先，从整体上分析我国房地产市场的发展现状及房地产价格演变的区域性差异。我国房地产市场化运行以来，房地产市场在投资和需求等多方面取得了飞速发展，但是房地产价格呈现出极大的区域差异性，东部地区的房地产价格明显高于中西部地区，特别是北京和上海等地的房地产价格明显高于其他省份，东中西各区域内部房地产价格也存在明显的差异性。
其次，甄别影响房地产价格区域差异的因素。在对收入水平、经济波动、土地供给水平、人口数量、信贷规模水平和城市规模对房地产价格产生区域差异性影响的理论分析基础上，从我国房地产市场发展现实出发，运用逐步面板回归方法对影响我国房地产价格，产生区域差异的因素进行了细致的判断和识别。计量经济分析结果表明，对于现阶段我国的房地产市场发展状况而言，收入水平、经济波动、土地供给水平和信贷规模水平对房地产价格的区域差异产生了显著的影响，而人口数量和城市规模并未对现阶段我国房地产价格区域差异产生显著影响。
再次，依据我国房地产市场发展水平不同，按照甄别出的房地产价格区域差异影响因素，建立指标体系进行聚类分析，以不同区域作为研究对象，采用1999年至2010年房地产价格及甄别变量的季度数据，应用空间面板数据模型，研究了各区域房地产价格的区域性特征及影响因素对房地产价格区域差异的影响程度。实证结果表明，房地产价格之间存在一定的空间联动性，收入水平对房地产市场处于发展期的地区影响程度高于房地产市场处于高速成长期的区域；经济发展水平高的区域房地产价格容易受到经济波动的影响，土地供给对于经济发达区域房地产价格影响不显著，经济发展水平欠发达区域房地产价格对信贷规模的依赖程度高。因此，为各地区有针对性地进行房地产市场的宏观调控提供了一定的现实依据，由于不同区域内影响房地产价格的主要原因不同以及相关因素对不同区域房地产价格的影响程度存在较大差异，因此各级地方政府及相关部门在制定相关的房地产市场调控政策时应充分考虑因地制宜的原则。
然后，应用结构变化理论对我国房地产价格进行检验，找到房地产价格结构变化点，并以此为基础，将1999年至2010年我国房地产市场进行阶段划分，并运用基于结构变化的面板数据模型深入揭示我国房地产价格区域差异的阶段性特征及影响因素对各区域房地产价格影响的动态性和阶段性特征。实证结果表明我国房地产价格的结构变化时点2005年1季度和2008年4季度，据此将我国房地产市场划分为三个阶段，这三个阶段也正是我国房地产价格从适度增长到快速增长再到适度增长的转变，且在三个阶段区域间房地产价格差异越来越明显。收入水平在三个时期对于房地产市场发展水平较低的区域影响程度最大；房地产发展水平高的区域始终对经济波动最为敏感；土地供给在房地产市场化初期对不同地区均产生影响，但是伴随着市场化的不断深入，土地供给对房地产市场发展水平高的区域不产生影响；在房地产市场快速发展阶段，信贷规模对于房地产市场发展水平高的区域作用不显著。因此，在制定房地产调控政策时，要充分考虑各地区房地产价格的动态性和阶段性变化特征，注意房地产调控政策的时效性。
最后，以不同区域为研究对象，应用面板数据协整及基于面板误差修正模型的Granger因果关系检验等经济计量分析方法实证检验了房地产价格波动与收入波动、经济波动、土地供给波动及信贷规模波动之间的长短期作用特征。实证研究结果表明：我国房地产价格波动行区域差异显著。无论是长期均衡还是短期波动，收入的波动和经济的波动均能引起各个区域房地产价格的波动，信贷规模只在长期上引起房地产价格的波动，土地供给在短期上引起房地产价格的波动；房地产价格的波动在长期均衡和短期波动状况下均能够引起不同区域信贷规模的波动，在长期上，房地产价格的波动在长期上对房地产市场发展水平低的区域收入水平不产生影响，房地产价格波动对不同区域的经济波动和土地供给波动均不产生影响，在短期上，房地产价格的波动不会影响房地产发展水平居中的经济波动，只能引起该区域的土地供给波动。因此，在制定房地产调控政策时，需要结合各地房地产市场真实的运行状态，制定切实有效地房地产调控政策。
本文得到的研究结论有助于更加清晰地理解在我国房地产市场化进程中我国房地产市场价格区域差异的特征，甄别不同影响因素及影响程度的差异。这些结论为保证我国房地产市场健康有序的发展，因地制宜地制定我国各区域房地产价格调控政策，保持各地区房地产市场均衡发展，有一定的借鉴意义。
Since 1998,China’s real estate began the market-oriented,the real estate market has been rapiddevelopment, and made an irreplaceable contribution to the development of related industries,pulling the entire national economic growth and improving people's quality of life, to become animportant basis industry in China’s national economic development.However,the real estate isclosely related to people’s livehood, the price level of the real estate not only determines the healthdevelopment of the real estate industry itself but also impact on the development of relatedindustries,economic development, quality of life of residents, the country's financial security,especially will have an enormous impact on social equity and stability.It is noteworthy that recentyears the real estate price in some areas rose far more than other places.there are significantdifferences in regional real estate prices. Regional differences in real estate prices not only showsthat the difference of the real estate market in level of development in different regions, but alsoreflects the different parts of the level of economic development and people's quality of life, andexcessive gap would most likely affect the fair and stable of the whole society. Therefore, it haspractical significance that the depth analysis of the root causes of regional differences in real estateprices, in order to objective and accurate understanding of the real estate market development,regional imbalances is crucial for the healthy and orderly development of China's real estatemarket.
Based on the above, this paper takes the real estate market development status as thebackground and the China’real estate market prices as the object of study .Base on the researchresult that exists nowdays,it analyzes the regional differences of China’s real estate marketprice.Combining with China's real estate market conditions,this paper uses the measurementmethods to indentify the regional difference influencing factors of the China's real estate marketprices.On this basis ,building the index system of China’s real estate market to redivision theChina’s real estate market,it uses micro-econometric methods to empirical test the regional ,thephase variation and volatility characteristics of China’s real estate market .the main contents andconlusions of this parper are as follows:
First of all, this paper analysis the current development of China’s real estate market and theregional differences in evolution of real estate prices.Since the market-orient of China's real estatemarket,China’s real market has rapid development in investment and demand aspects,however thereal estate prices shows significant regional differences. The real estate prices in the eastern part areobviously higher than the real estate price in central and westen regions, especially the real estateprices in Beijing and the Shanghai are significantly higher than other provinces.there are obviouslydifferences in the estate,central and westen regions real estate prices.
Secondly, it is important to screen the factors affect the regional differences of real estate prices. First of all, we theoretical analyze the income levels, economic fluctuations, the level ofland supply, the size of population, the level of credit scal and the urban scale.Based on thetheoretical anaylsis,this paper used the stepwise regression techniques to analyze the factors ofaffecting the real estate prices ,resulting regional differences according to the reality of China’s realestate marker.it carefully judges and recongnize the influencing factors of the regional difference inreal estate markets.The econometric analysis showed that at this stage in China's real estate marketconditions, income levels, economic fluctuations, the level of land supply and credit scale levelhave a significant impact on the on the regional differences in real estate prices. The size ofpopulation and urban size have no significant impact on the regional differences of China’s realestate price at this stage.
Thirdly, According to the different level of development state of China real estate market,based on the screened real estate different influencing factors, using the cluster analysis to divideinto different regions. Based on the divided regions, the application of spatial panel data modelfrom 1999 to 2010 examined the regional differences characteristics and empirically tested theimpact of various factors on the regional differences of real estate prices.The empirical resultsindicate there are certain space linkages between real estate prices. The income level of thedeveloping real estate market has higher impact than the high-growth markets. The real estateprices of region with a high level economic development are easily affected by economicfluctuation. The land supply has no significant effect to the real estate prices of economicallydeveloped regions.The real estate prices of economic less-development regional has higher degreeof dependence on the credit scal. Therefore, the empirical results provide a realistic basis to themacro-control of the regions real estate market. The main reason of affecting real estate prices indifferent regions are different as well as there are big difference that realted factors have differentinfluence degree,so the local government and relevant departments should take full account of thelocal real estate market conditions to make real estate market regulation policy.
Fourly, we use the application of structural change theory to determine the structural changespoint of the real estate price, based on the structural changes point of the real estate price the paperdetermined the real estate market development phasing from 1999 to 2010. Then applying the paneldata model based on structural changes to profoundly reveal the income levels, fluctuations in theeconomy situation, the level of land supply and the credit scale influenced the regional real estateprices to from dynamic and phase characteristics.The conclusion is as follows: the real esate priceshas two structural points,2005Q1and 2008Q4.According to China’s real estate market is divied intothree stages,the three stages is also China’s real estate prices from moderate growth shift to rapidgrowth then to moderate growth,and the difference of real estate prices in the three stages becomeincreasingly evident.Income levels in the three periods has mostly impacted on the low level realestate market.High level of real estate development area has always been the most sensitive toeconomic fluctuations.Land supply influences the real estate market prices in the early stage,butalong with the deepening of market-oriented,land supply has no influence to the high leveldevelopment real estate market.in the rapid development stage of real esatate market,the credit sizehas no significan influence in the high level real esteat market. Therefore, the local government and relevant departments should take full account of the dynamics and phase change characteristics ofthe real estate prices, paying attention to the timeliness of real estate control policy.
Finally, the different regions as the research object, the application of panel data cointegrationand Granger causality test based on the panel error correction model econometric analysis methodof this paper examines the real estate price fluctuations and fluctuations in income, economicfluctuations, fluctuations in the supply of land and the size of creditbetween short-and long-termrole in the volatility characteristics. The empirical results show that: significant regional differencesof China's real estate price fluctuations in line. Whether it is the long-run equilibrium, short-termfluctuations, income fluctuations and economic fluctuations can be caused by various regional realestate price fluctuations, the size of credit only in the real estate price fluctuations on the long-termland supply in the real estate price fluctuations on the short-term ; the volatility of real estate pricesin the long-run equilibrium and short-term fluctuations in conditions can cause fluctuations indifferent regions of the size of credit, in the long term, real estate price fluctuations in the long termreal estate market in level of development in regions with low income levels have an impact notimpact on economic fluctuations and fluctuations in the supply of land, real estate pricefluctuations in different regions, in the short term, real estate price fluctuations will not affect thereal estate development in the middle levels of economic fluctuations, and can only be caused byfluctuations in the supply of land in the region . Therefore, in the development of real estate controlpolicy requires a combination of real running status of the real estate market around thedevelopment of effective real estate control policy.
The conclusions of the study in this article contribute to more clearly understand thecharacteristics of the regional differences of China's real estate market prices in the process ofChina's real estate market, screening of different factors affect the degree of variation. Ultimately,in order to ensure the healthy and orderly development of China's real estate market, localconditions to develop the regional real estate price control policies in China, to maintain thebalanced development of the regional real estate market, there is some reference.
引文
①Hodrick和Prescott（1980）在分析美国战后经济周期波动时首次使用这种方法。
②刘金全：现代宏观经济冲击理论[M]，长春：吉林大学出版社，2000。
①或。
②W规律条件应该满足Lee（2004）求得的截面设置，但这些规则条件在面板数据的设置可能会变化（Yuetal.2007）.
①参见Kriishnaiah and Miao（1998），Zakes（1983）and Deshayes and Picard（1986）.Acomprehensive treatmentof asymptotic results related to structural change can be found in Csorgo and Horvath(1997).
②参考其它，如Christiano(1992),Chu and White(1992), Kim and Sigmund(1989) and Perron(1991) (trendingregressors), Kramer,Ploberger and Alt(1988)(serial correlation), Bai, Lumsdaine and Stock(1998) and Hansen
(1992)(models with integrated variables).
③参考Perron(1989,1994,1997a), Banerjee,Lumsdaine and Stock(1992),Zivot and Andrews(1992),Perronand Vogelsang(1992) and Gregory and Hansen(1996).
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