北京市房地产泡沫状况与成因分析

对北京市房地产开发投资、固定资产投资、商品房销售情况进行量化分析,并计算地价与GDP、物价增长率的相关指标,据此分析北京市房地产市场的经济波动状况以及泡沫情况,并从价格预期、土地稀缺性、流动性膨胀、银行信贷非理性膨胀、税收政策几个方面对影响泡沫形成的因素进行分析,为相关市场参与者提供相关依据。     

房地产税收对商品房价格的影响研究

中国房地产市场的需求弹性小于供给弹性,政府对房产拥有者征税,税收负担其实更多地落在了购房者身上。中国现行的房地产税制对于稳定房地产市场,抑制过度投机,降低商品房价格的作用不明显。应改变住房需求弹性,在房地产保有环节征税,促进中国房地产市场的健康发展。     

The Positive Externalities of Chapter 13 “Cramdowns” Could Prevent the Next Foreclosure Crisis

Revision of Bankruptcy Code 11 U.S.C. § 1322(b)(2) would permit “cramdowns” wherein bankruptcy judges would administer the modification of residential mortgages only when mortgage-lending abuses were most rampant (a real estate bubble). Foreclosure spill-over effects systemically worsened the housing crisis and were not evenly diffused throughout the broader housing market. Throughout 2003–2006, an oversupply of underpriced mortgage finance emanating from lax underwriting standards bid up residential prices. Relaxation of underwriting protocols came about from the mortgage market’s institutional swing from regulated agency securitization (predominantly government-sponsored enterprises “GSEs”) to unregulated securitization (shadow banking). This resulted in an untenable residential-price bubble as synthetically inexpensive credit from investors’ mispricing amplified mortgage demand, while greater mortgage quantity nudged up housing prices. The result was a self-referential cycle of waning residential prices supporting and perpetuating nigh incessant foreclosures: the bubble had burst. Cramdowns would incentivize lenders to be less inclined to loosen underwriting standards, or when done, to include this factor in the risk premium of the cost of credit. Enhancing Chapter 13 with the muscle to alter residential mortgages would ameliorate an institutionally structural issue endemic to the past (and upcoming?) foreclosure crisis.     

基于状态空间模型的房地产价格泡沫问题研究

文章首先对房地产价格泡沫进行了理论界定,并对基础价值的特点进行了分析。随后在检验变量之间协整关系的基础上,建立了商品房供给与需求的状态空间模型,基础价值作为一种状态变量被纳入到模型中,从而对上海市房地产价格泡沫问题进行了实证研究。研究结果表明上海市房地产价格泡沫已经出现,并且近四年来平均泡沫程度达到22.5%。     

土地财政制度对房地产价格的影响因素研究*

本文基于动态系统GMM模型,运用Stata软件和计量经济学方法,对2009—2015年中国15个大中城市房价水平的变化趋势进行研究。结果表明：（1）地方政府依靠土地财政和房地产维持地方财政,土地财政是导致房价上涨的根本原因。（2）在经济下行的背景下,地方政府和房企共同经营土地,地方政府试图通过做大土地财政拉动地方经济。（3）中央政府选择有利于中央政府效用水平增加的经济发展方式。所以中央政府、地方政府与房企会形成经济增长联盟共同推动房价上涨。（4）房企行为对土地财政导致的高房价具有放大效应,且作用效果在东部、中西部地区呈现明显的区域差异。本文的贡献是发现了房企行为与土地财政、房价上涨之间相互作用的逻辑关系,为找到缓解房地产价格上涨的措施提供了新的可能性。     

城中村改造对房地产市场影响的实证分析——以武汉市汉阳区为例

城中村改造作为城市化升级的重要步骤正在我国各大中城市如火如荼地展开,已经并必将继续对城市房地产市场产生重要而深远的影响。以武汉市汉阳区城中村改造为例,从供给、需求和价格的角度分析了城中村改造对房地产市场的影响。就现有的改造方式而言,其增加了土地与商品房的供应量,拉高了市区内部分市场的房价,改变了供给结构,但对需求影响甚微。因此城中村改造宜从改造主体、方式和进度上加以调控。     

中国房地产价格泡沫原因分析

房地产业与其他行业联系密切,对国民经济发展具有明显的拉动作用。20年来,中国房地产业逐步发展壮大。伴随着中国房地产市场的强劲增长,其价格出现了泡沫化倾向。本文分析了我国房地产价格泡沫的原因,指出流动性膨胀、房地产市场虚拟化、虚拟经济部门资金错配、土地价格不断上涨和房地产市场需求刚性是房地产价格出现泡沫的主要原因。当前的挤出政策治标不治本,改堵为疏才是正确选择。     

Impact Fees and Real Estate Prices: Evidence from 35 Chinese Cities

Local governments often charge developers impact fees to finance local public goods. This has been practiced in Chinese cities for more than two decades; however, no empirical studies have tested the effect of impact fees on real estate prices. Using a panel data set for 35 large- and medium-sized cities from 1998 to 2008, we find that impact fees lead to a significant increase in real estate prices. For a given city, an increase in impact fees by one yuan leads to an increase of about 5 yuan in the price of newly-built housing; a 1% increase in impact fees leads to an increase of 5 percentage points in the housing price index and 7 percentage points in the land price index.     

房地产业发展的根本出路在于体制改革

1998年中国商品房市场化改革为中国房地产业和中国经济带来了十余年的高速增长.近年来,中国房价的过快上涨,根本原因不在于人多地寡,也不在于住房需求快速增长,更不在于投机盛行,而在于土地供给的非市场化.中国房地产业要实现稳定健康发展,就必须实行彻底的市场化改革.一是要改革单边垄断的土地供给制度;二是要改革财权与事权不对等的财政分税体制;三是要改革政府行政管理体制,减少不合理的行政干预.改革可以从以下五个方面进行:一是建立公平公正的法治环境;二是培育多元的土地供应主体,有效扩大土地供给;三是需要将地方政府税源长期化,改变地方政府的土地财政利益导向;四是需要政府加大保障性住房建设并实行公平、公开、公正的分配;五是需要慎用行政手段,不断完善市场机制,充分发挥市场在资源配置中的主体作用     

Multivariate Analysis of the Condition of the Property Development Sector: Selected Local Real Estate Markets in the European Union

The aim of the study is to serve as a multidimensional analysis of relationships between the economic and financial standing of property developers and the residential property market situation. The discussion concerns the property development market situation in the context of the construction market situation, with particular emphasis on residential housing investment in selected EU countries. Property development companies whose activities focused on residential housing were assessed with respect to performance in the selected market on the stock exchange. Individual companies were classified using economic and financial indices. Despite the ongoing economic downturn in real estate markets, the results for these companies did not indicate poor performance on the stock exchange. In the study, a synthetic measure of development was used in linear ordering.     

诺贝尔奖得主泽尔滕对杭州房地产泡沫的看法

杭州的房地产问题具有普通性,2005年3月和11月,诺贝尔经济学奖得主泽尔滕教授两次来华讲学.在华其间,他与其博士后高雷博士深入地探讨了杭州市房地产市场的泡沫问题.泽尔滕教授认为必须警惕杭州房地产市场泡沫,他注意到杭州房地产市场交易量的增长已落后于房价的增长.泽尔滕教授和高雷博士认为从众效应会促使房价一路攀升直至最后崩溃.对我国房地产市场存在的问题,他们提出了具体的政策建议,如放宽对利率的限制、完善房地产金融体系、改进房地产贷款和抵押政策、封堵境外投机资金等.     

Housing price fluctuations and financial risk transmission: a spatial economic model

Financial risk derived from housing price fluctuations in China garnered much public concern recently. Based on the theoretical analyses of the transmission of financial risk from housing price fluctuations, this paper establishes panel spatial Durbin models to empirically analyse housing price fluctuations and financial risks transmission from a spatial economic perspective. Employing the panel provincial data from 1999–2015, we conduct an analysis on the 30 provinces in China as well as a comparison among the Eastern, Middle and Western regions of China. The results indicate that: (1) The soaring housing prices driven by bank credit, real estate developers’ heavy investment, local governments’ land revenue and individuals and households demands leads to financial risk in various sectors; (2) due to the ‘substitution effect’, the capital agglomeration in metropolis from bank credits, real estate developers, and individuals and households furthers the amassment of financial risks; (3) housing prices have a significant spatial contagion effect throughout the country, and financial risk could directly transmit across provinces through housing price fluctuations; (4) financial risks could indirectly transmit across provinces via the ‘imitative behaviour’ or ‘driving effect’ of different sectors for different regions of China.     

Clarification of misled statistic data: overestimated per-capita housing area

The per-capita urban housing area determines trends in the real estate market largely. These trends are important in formulating economic policies. The China Statistical Yearbook provides two groups of data for ‘per-capita urban housing.’ The demand–supply situation of the Chinese housing market must be analyzed and predicted by using different versions of data. This study uses data from Ministry of Housing and Urban-Rural Development of the People’s Republic of China, which comprise projected timing comparative data of the Chinese per-capita urban housing area, and predicts the future demand–supply situation of the Chinese housing market using the Gompertz model. The result shows that the per-capita urban housing area has declined since 2001, but the tight trend of the Chinese real estate market and the pressure of rising house prices will last for a relatively long time. The construction speed of commercial houses will only slow down if the urbanization proportion reaches 75%.     

珠三角房地产泡沫测度实证研究——以广州为例

在比较国内外房地产泡沫测度方法的基础上,以广州为例,选择因子分析法来测度珠三角房地产市场的泡沫程度。研究发现1996—2005年珠三角房地产市场的泡沫测度值波动较小,虽然在个别年份出现了泡沫,但房地产市场整体运行平稳。而以城市规划和土地储备制度为中心的政府有效宏观调控政策、房地产业的高度市场化和消费者理性是珠三角房地产市场平稳运行主要原因。     

房地产泡沫问题及实证分析

自1998年开始,随着福利化分房的结束,住房商品化的开始,我国房地产业进入了持续快速发展的新时期.与此同时,房地产价格也连续快速攀升.近年来,关于我国房地产泡沫问题的争论不绝于耳,但是一直未有定论.在借鉴国内外理论研究的基础上,引用最新的统计数据,运用定量方法,对我国1997-2006年房地产业运行中是否存在泡沫进行实证分析,得出结论:我国还不存在严格意义上的全国普遍性的房地产泡沫,但泡沫化倾向明显,需警惕.     

Alternative Land-Price Indexes for Commercial Properties in Tokyo

The System of National Accounts (SNA) requires separate estimates for the land and structure components of a commercial property. Using transactions data for the sales of office buildings in Tokyo, a hedonic regression model (the “builder’s model”) was estimated and this model generated an overall property price index as well as subindexes for the land and structure components of the office buildings. The builder’s model was also estimated using appraisal data on office building real estate investment trusts (REITs) for Tokyo. These hedonic regression models also generated estimates for net depreciation rates, which can be compared. Finally, the Japanese government constructs annual official land prices for commercial properties based on appraised values. The paper compares these official land prices with the land prices generated by the hedonic regression models based on transactions data and on REIT data. The results reveal that commercial property indexes based on appraisal and assessment prices lag behind the indexes based on transaction prices.     

政绩考核、产业政策与社会结构——基于OLG框架的房地产一般均衡

本文基于OLG框架构建的房地产一般均衡模型,揭示了我国房地产市场泡沫背后的经济机制与政府行为。单一GDP考核使得地方政府存在扩大支出的强烈动机,为了解决财政缺口,地方政府会选择扶持房地产业的发展,这种对房地产业的过度扶持会扭曲消费者购买更多房产,从而推动房地产市场的价量齐升。基于这些结论,我们提出,中央政府可以从规制的角度出发,适当调整地方政府的考核目标,在原来的GDP单一目标的基础上考虑民众的收入水平以及收入平等目标。均衡分析表明,这种调整会改变地方政府扶持房地产的激励程度．从而有效控制房地产市场的发展。     

Real estate markets and the macroeconomy: A dynamic coherence framework

This paper analyzes the dynamic interactions between real estate markets, in the US and the UK and their macroeconomic environments. We apply a new approach based on a dynamic coherence function (DCF) to study these interactions bringing together different real estate markets (the securitized market, the commercial market and the residential market). The results suggest that there is a common trend that drives the different real estate markets in the UK and the US, particularly in the long run, since they have a similar shape of the DCF. We also find that, in the US, wealth and housing expenditure channels are very conductive during real estate crises. However, in the UK, only the wealth effect is significant as a transmission channel during real estate market downturns. In addition, real estate markets in the UK and the US react differently to institutional shocks. This brings some insights on the conduct of monetary policy in order to avoid disturbances in real estate markets.     

市场情绪如何影响城市房价

基于行为金融学理论建立了房地产情绪指数影响房价的模型，借鉴Baker and Wurgler（2006）提出的构建资本市场投资者情绪指数的方法，从供需两方选取合适的情绪指标；同时，运用大数据方法，选取百度指数作为情绪指标，运用主成分分析法构建了我国35个大中城市房地产市场的情绪指数，实证研究了市场情绪对房地产价格的影响。另外，还测度不同区域房地产市场情绪指数，通过实证分析横向对比东部和中西部城市市场情绪对房价的影响程度。实证结果表明，市场情绪对房地产价格有着显著的正向影响；市场情绪对房地产价格的正向影响呈现区域异质性，东部地区市场情绪对房地产价格的正向影响强于中西部地区。     

China’s house price: Affected by economic fundamentals or real estate policy?

Many theory and empirical literature conclude that house price can reflect economic fundamentals in the long-term. However, by using China’s panel data of 35 main cities stretching from 1998 to 2007, we find that there is no stable relationship between house price and economic fundamentals. House price has deviated upward from the economic fundamentals since government started macro-control of the real estate market. We consider that the mechanism between the house price and economic fundamentals is distorted by China’s real estate policy, especially its land policy. Meanwhile the policy itself is an important factor in explaining the changes of China’s house price. Then we estimate the dynamic panel data model on house price and the variables which are controlled by real estate policy. The result shows: land supply has negative effects on house price; financial mortgages for real estate have positive effects on house price; and the area of housing sold and the area of vacant housing, which reflects the supply and demand of the housing market, has negative effects on house price. We also find some differences in house price influence factor between eastern and mid-western cities. Finally, we propose policy suggestions according to the empirical results.