An econometric model of housing price, permanent income, tenure choice, and housing demand

This paper addresses the determination of housing price, permanent income, tenure choice, and housing demand. Full housing demand elasticities incorporate the interactive effects among the four stages of the model. Price and income have major effects in the tenure choice equation. Sociodemographic variables, such as age, have complex effects that may be lost in simpler forms of estimation.     

住房价格指数以及区位对住房价格的影响——北京市住房价格实证分析

根据北京市的1308个新建住宅项目数据,建立了Hedonic模型,着重分析了时间、距离、环线以及行政区等变量对住房价格的影响,构建了北京市住房Hedonic价格指数和住房价格的梯度曲线.     

What moves housing markets: A variance decomposition of the rent–price ratio

We apply the dynamic Gordon growth model to the housing market in 23 US metropolitan areas, the four Census regions, and the nation from 1975 to 2007. The model allows the rent–price ratio at each date to be split into the expected present discounted values of rent growth, real interest rates, and a housing premium over real rates. We show that housing premia are variable and forecastable and account for a significant fraction of rent–price ratio volatility at the national and local levels, and that covariances among the three components damp fluctuations in rent–price ratios. Thus, explanations of house-price dynamics that focus only on interest rate movements and ignore these covariances can be misleading. These results are similar to those found for stocks and bonds.     

A dymimic model of housing price determination

This paper presents and estimates a model of the resale housing market. The data are a cross-section of monthly time series obtained from the multiple-listing service for a suburb of San Diego. The model is specified and estimated as a dynamic multiple indicator multiple cause system of equations where the capitalization rate is taken to be an unobservable time series to be estimated jointly with the unknown parameters. These are estimated by maximum likelihood using an EM algorithm based upon Kalman filtering and smoothing.The specification of the model features hedonic equations for each house sale and a dynamic equation for the capitalization rate which is constrained to make the expectation of prices equal the present value of the net returns to home ownership whenever the economic variables stabilize at steady state values. Out of steady state, the capitalization rate slowly adapts to new information.The model attributes a large portion of housing price increases of the 1970's to a fall in the capitalization rate which in turn was driven by rental inflation, tax rates and mortgage rates. Post-sample simulations indicate an initial flattening of housing inflation rates and later a fall brought on by the increase in steady state capitalization rates. In-sample simulations show that although both Proposition 13 and the inflation induced rise in the marginal income tax rates provided partial explanations for the fall in capitalization rates, the single most important factor was the acceleration in price of housing services which interacted with the tax treatment of home ownership to produce an amazing 18% average annual rate of price increase over the last seven years of the 1970's.     

Property taxation and the demand for housing: An econometric analysis

There is disagreement among economists regarding the effect of a local increase in property taxation on the housing market. In defining the price of housing services studies of the demand for housing have treated the property tax exclusively as an excise tax on housing consumption. Two recent theoretical developments suggest this is a misrepresentation of the tax. One theory holds that the excise effects of property taxation may be shifted backward to the factors employed in the production of housing. The other theory concludes that the property tax is not an excise, but rather serves as an efficient price for local public services. To investigate these hypotheses, data from the Annual Housing Survey were employed to estimate a housing demand model which included the net effective property tax rate among the set of independent variables. In addition to revealing the property tax-housing demand relationship, the model provides more reliable estimates of income and price elasticities by eliminating specification errors found in previous studies. Results indicate that the property tax reduces the housing consumption of central city homeowners, but does not distort the suburban housing market.     

惊呼声中的住宅价格

今年以来,上海商品住宅价格在连续3年稳步上涨的基础上快速上扬,并呈现涨速加快态势.引起了社会各界的广泛关注。从根本上讲,商品住宅价格快速上涨是商品住宅供求矛盾加剧的表现。但是,目前相当大比例的普遍居民抱怨商品房价格上涨太快,房价已超出了自己的经济承受能力。     

Managing hedonic housing price indexes: The French experience

Despite their theoretical advantages, hedonic housing price indexes are not so commonly computed by statistical agencies or real estate professionals. Many published indexes still rely on mean or median prices, or favor repeat-sales methods, which require less information about the attributes of the housing units and less econometric expertise on the part of the index compilers, but may be less accurate and robust. In France as in other countries where housing sales have to be recorded in front of a notary, data on transaction prices and characteristics of dwellings are available. Such data have been centralized since 1994, and quarterly hedonic housing price indexes have been computed for more than 10 years. This paper describes the institutional setting of housing transactions in France, and the collaboration between the notaries and the national statistical agency (INSEE). The former are responsible for data collection and regular computation, whereas the latter takes scientific responsibility for the method. The detailed information on the individual properties transacted remains proprietary data, but disaggregated indexes are publicly and freely available. This organization and assignment of roles has proven effective and might be extended to countries with similar institutional settings.     

The reduced form price elasticity of housing

This paper focuses on the modeling of the housing market. First, there is a discussion of terminology. The importance of distinguishing between housing and structures, and between reduced form and supply elasticities is emphasized. Second, the role of tastes and technology is emphasized. Third, the integration of the housing market into a general equilibrium urban model to investigate such issues as the effects of a housing subsidy is discussed. Throughout attention is drawn to what additional information is needed to provide an adequate empirical characterization of the housing market.     

Booms and busts in housing markets: Determinants and implications

This study looks at the characteristics and determinants of booms and busts in housing prices for a sample of eighteen industrialised countries over the period 1980–2007. From an historical perspective, we find that recent housing booms have been amongst the longest in the past four decades. Estimates of a Multinomial Probit model suggest that domestic credit and interest rates have a significant influence on the probability of booms and busts occurring. Moreover, international liquidity plays a significant role for the occurrence of housing booms and—in conjunction with banking crises—for busts. We also find that the deregulation of financial markets has strongly magnified the impact of the domestic financial sector on the occurrence of booms.     

Forecasting with an econometric model: Some recent results using the national institute model

It is widely believed that the large econometric models cannot be used for forecasting without considerable intervention on the part of the forecaster. In this paper we challenge this view by reproducing a number of recent forecasts published by the National Institute but without the ad hoc interventions used at the time. We show that in no case would the forecast, produced by the model used mechanically, have been radically different from that actually published. Further, in an ex-post comparison against actual out-turns, the mechanical model forecast is not obviously dominated by the published version.     

工程量清单计价模式的应用研究

工程量清单计价早已成为国际上普遍采用的工程计价方式,我国于2003年7月1日采用这种计价方式。在此之前,我国一直沿用的是定额计价的方式。文章对这两种计价模式的不同进行简单比较,对清单计价存在的问题及对策进行了详细阐述。     

The econometric forecasting model of Czechoslovakia

Conclusion The result of the construction, estimation, testing and forecasting uses of the VVS-2 model testify to the expediency of using comprehensive econometric models in socialist economy. The VVS-2 model expresses at a satisfying rate of accuracy the quantitative relations between the fundamental indicators of Czechoslovak economy and has produced satisfactory results also in calculating short-term forecasts. Some new methods and computer programs that have been developed and employed for model estimation may be considered a contribution towards the development of applied econometrics in socialist countries.At the Computing Research Centre, United Nations D.P. in Bratislava, research work has continued on the development and improvement of further comprehensive econometric models. Within this framework the VVS-2 model will be permanently reestimated and possibly also extended and re-specificated according to the practical needs of macroeconomic analysis and planning.Authors are indebted to Professor Anton Klas, director of the Computing Research Centre, United Nations D.P., for creating very favourable conditions for the research work.     

The use of proxy variables in housing price analysis

This paper presents a reexamination of data used by Berry to study housing prices in Chicago. The detailed data on 275 single-family houses are used to test the proposition that the tax assessment on improvements is a good proxy for the attributes of the houses. It is shown that the test used by Berry is irrelevant for the question of omitted variables bias, and the correct test is presented. It is concluded that the proxy corrects for a bias in the coefficient of percent black population, but increases the negative bias in the coefficient of percent Latino population.     

Estimation of variance of housing prices using spatial conditional heteroskedasticity (SARCH) model with an application to Boston housing price data

In this paper we investigate housing price volatility within a spatial econometrics setting. We propose an extended spatial regression model of the real estate market that includes the effects of both conditional heteroskedasticity and spatial autocorrelation. Our suggested model has features similar to those of autoregressive conditional heteroskedasticity (ARCH) in the time-series context. We utilize the spatial ARCH (SARCH) model to analyze Boston housing price data used by Harrison and Rubinfeld (1978) and Gilley and Pace (1996). We show that measuring the variability of housing prices is an important issue and our SARCH model captures the conditional spatial variability of Boston housing prices. We argue that there is a different source of spatial variation, which is independent of traditional housing and neighborhood characteristics, and is captured by the SARCH model.     

Modeling the price side of econometric models: An analysis of the underlying hypotheses

Using a non-linear vector autoregression, this paper investigates the dynamic interactions between a set of disaggregated price series. A hypothesis, positing that all sectoral prices are a function of a ‘major price index’, is tested and the way this hypothesis is used in econometric models is discussed. The model is based upon the theory of covariance stationary time series. Non-linear estimation procedures are used.