Analysis of Spatial Autocorrelation in House Prices

This article examines spatial autocorrelation in transaction prices of single-family properties in Dallas, Texas. The empirical analysis is conducted using a semilog hedonic house price equation and a spherical autocorrelation function with data for over 5000 transactions of homes sold between 1991:4 and 1993:1. Properties are geocoded and assigned to separate housing submarkets within metropolitan Dallas. Hedonic and spherical autocorrelation parameters are estimated separately for each submarket using estimated generalized least squares (EGLS). We find strong evidence of spatial autocorrelation in transaction prices within submarkets. Results for spatially autocorrelated residuals are mixed. In four of eight submarkets, there is evidence of spatial autocorrelation in the hedonic residuals for single-family properties located within a 1200 meter radius. In two submarkets, the hedonic residuals are spatially autocorrelated throughout the submarket, while the hedonic residuals are spatially uncorrelated in the remaining two submarkets. Finally, we compare OLS and kriged EGLS predicted values for properties sold during 1993:1. Kriged EGLS predictions are more accurate than OLS in six of eight submarkets, while OLS has smaller prediction errors in submarkets where the residuals are spatially uncorrelated and the estimated semivariogram has a large variance.  

对房价收入比科学涵义的再探讨

房价收入比是目前国际上常用的衡量城市居民住房消费能力和房价水平的综合指标。科学界定房价收入比的涵义,对于有效提高这一指标的应用价值至关重要。在此基础上,还应客观认识房价收入比在实际运用中的功能特征,以利房地产理论研究、政策制定以及企业经营。  

House prices, consumption, and monetary policy: a financial accelerator approach

We consider a general equilibrium model with frictions in credit markets used by households. In our economy, houses provide housing services to consumers and serve as collateral to lower borrowing cost. We show that this amplifies and propagates the effect of monetary policy shocks on housing investment, house prices and consumption. We also consider the effect of a structural change in credit markets that lowers the transaction costs of additional borrowing against housing equity. We show that such a change would increase the effect of monetary policy shocks on consumption, but would decrease the effect on house prices and housing investment.  

The effect of real rates of interest on housing prices

During the late 1970s, U.S. house prices were appreciating rapidly even though mortgage interest rates were climbing. Recently, interest rates have eased but prices have moderated. This study examines the role of appreciation expectations in overcoming the negative effects of nominal mortgage interest rates on house prices. Expectations of future appreciation are important determinants of house sales prices, remaining influential during periods of declining and moderating real prices, not just when prices are rising. The real rate of interest, as viewed by the homebuyer, is the mechanism for affecting change in housing price levels. Because the nominal interest rate is slow to reflect changes in expectations, these real rates vary over time. This ebb and flow of real interest rates appears to explain market price levels. Nominal rates play a role as well, primarily in the formation of appreciation expectations.  

The Dynamic Impact of Macroeconomic Aggregates on Housing Prices and Stock of Houses: A National and Regional Analysis

This article analyzes the dynamic effects of four key macroeconomic variables on the housing prices and the stock of houses sold on the national and regional levels using a nonstructural estimation technique. The impulse response functions derived from the VAR suggest that macroeconomic variables produce cycles in housing prices and houses sold. The housing market was found to be very sensitive to shocks in the employment growth and mortgage rate at both the national and regional levels. In particular, regional housing prices reflect regional employment growth, as well as national mortgage rates. The study also reveals that the economic variables have a different impact on the dynamic behavior of housing prices and the number of houses sold in different regions at different time periods and that these economic aggregates alone cannot explain the fluctuations in real estate values and construction levels that occurred in some regions.  

Testing for Bubbles in Housing Markets: A Panel Data Approach

We employ recently developed cross-sectionally robust panel data tests for unit roots and cointegration to find whether house prices reflect house related earnings. We use U.S. data for Metropolitan Statistical Areas, with house price measured by the weighted-repeated-sales index and cash-flows by market tenants’ rents. In our full sample period, an error-correction model is not appropriate, i.e. there is a bubble. We then combine overlapping 10-year periods, price–rent ratios, and the panel data tests to construct a bubble indicator. The indicator is high for the late 1980s, early 1990s and since the late 1990s. Finally, evidence based on panel data Granger causality tests suggests that house price changes are helpful in predicting changes in rents and vice versa. CERGE-EI is a joint workplace of the Center for Economic Research and Graduate Education, Charles University, and the Economics Institute of the Academy of Sciences of the Czech Republic.  

Anisotropic Autocorrelation in House Prices

This article examines anisotropic spatial autocorrelation in single-family house prices and in hedonic house-price equation residuals using a spherical semivariogram and transactions data for one county in the Philadelphia, Pennsylvania, MSA. Isotropic semivariograms model spatial relationships as a function of the distance separating properties in space. Anisotropic semivariograms model spatial relationships as a function of both the distance and the direction separating observations in space. The goals of this article are (1) to determine whether there is spatial autocorrelation in hedonic house-price equation residuals and (2) to empirically examine the validity of the isotropy assumption. We estimate the parameters of spherical semivariograms for house prices and for hedonic house-price equation residuals for 21 housing submarkets within Montgomery County, Pennsylvania. These housing submarkets are constructed by dividing the county into 21 groupings of economically similar adjacent census tracts. Census tracts are grouped according to 1990 census tract median house prices and according to characteristics of the housing stock. We fit the residuals of each submarket hedonic house price equation to both isotropic and anisotropic spherical semivariograms. We find evidence of spatial autocorrelation in the hedonic residuals in spite of a very elaborate hedonic specification. Additionally, we have determined that, in some submarkets, the spatial autocorrelation in the hedonic residuals is anisotropic rather than isotropic. The empirical results suggest that the spatial autocorrelation in Montgomery County single-family house-price equation residuals is anisotropic in submarkets where residents typically commute to a regional or local central business district.  

住房价格、住房投资、消费与货币政策——基于金融加速器效应的DSGE模型研究

以BGG模型为基础建立包含金融加速器机制的DSGE模型,采用数值模拟方法研究中国货币政策冲击对住房价格与住房投资及消费的影响,结果表明金融加速器机制明显放大了货币政策冲击对三者的影响;与不带金融加速器模型相比,使用带有金融加速器效应模型分析时,中国货币政策冲击对房价、投资和消费的影响程度更大,并且更符合现实数据特征。模拟结果还显示货币政策对消费的影响与已有文献的结论存在差异,即货币政策冲击对消费短期影响较大,且影响持续时间也较长。  

金融危机期房地产业健康发展问题

综观我国房地产业的现状,金融危机使房地产业加快进入调整期,但房价依然过高,房地产市场虚火仍旺,房价震荡跌涨是其理性回归过程,预期房地产业真正回升还将有一段时间。建议:改革土地转让收费制度,以大幅度降低住房价格;采用共有产权形式解决低收入群体的住房问题。只有广大百姓的安居,才是房地产业健康发展之路。  

房地产市场泡沫测度:珠三角实证

准确测度一国或地区的房地产市场泡沫水平和投机程度,是正确认识和有效解决房地产市场相关问题的基础.2008年,我国房地产市场价格在持续快速上涨后出现一定程度的回落,在市场的波动中如何准确测算其泡沫程度值得关注.目前对于房地产泡沫的测度方法不一,本文综合采用多种方法测算珠三角房地产市场泡沫,力求全面准确反映房地产市场真实的泡沫程度和房价合理度.结论显示:珠三角各地市房地产市场都存在不同程度的泡沫,当前的房价不尽合理,首付款和还贷压力均成为抑制市场需求的瓶颈.