Supply constraints and housing market dynamics

Although the volatility of house prices is often ascribed to demand-side factors, constraints on housing supply have important and little-studied implications for housing dynamics. I illustrate the strong relationship between the volatility of house prices and the regulation of new housing supply. I then employ a dynamic structural model of housing investment to investigate the mechanisms underlying this relationship. I find that supply constraints increase volatility through two channels: First, regulation lowers the elasticity of new housing supply by increasing lags in the permit process and adding to the cost of supplying new houses on the margin. Second, geographic limitations on the area available for building houses, such as steep slopes and water bodies, lead to less investment on average relative to the size of the existing housing stock, leaving less scope for the supply response to attenuate the effects of a demand shock. My estimates and simulations confirm that regulation and geographic constraints play critical and complementary roles in decreasing the responsiveness of investment to demand shocks, which in turn amplifies house price volatility.     

Heterogeneous expectations,boom-bust housing cycles,and supply conditions: A nonlinear economic dynamics approach

We combine a standard stock-flow housing market model, incorporating explicit relationships between house prices, the housing stock, and the rent level, with a parsimonious expectation formation scheme of housing market investors, reflecting an evolving mix of extrapolative and regressive expectation rules. The model results in a two-dimensional discrete-time nonlinear dynamical system. Based on realistic parameters, the model is able to generate endogenous boom-bust housing market dynamics with lasting periods of overvaluation and overbuilding. We thus exploit our model to investigate how real forces, in particular supply conditions, interact with expectations-driven housing market fluctuations.     

我国保障房建设的PPP模式与公众参与改进

加快保障性住房建设,大幅提升保障性住房供给,可以解决由住房供给结构严重失衡引发的高房价等一系列社会和经济问题。但是由于融资渠道狭窄,我国保障房的建设推广遭遇资金瓶颈。本文在剖析PPP模式的内涵及优势的基础上,探讨了适合我国基本国情的保障性住房PPP模式的具体运作流程,并提出通过引入公众参与机制,构建政-企-民三方合作框架,改进PPP模式下保障房供给的构想,以期实现PPP融资模式在我国保障性住房建设中的推广应用。     

Price dynamics in public and private housing markets in Singapore

In down-payment constrained housing consumption models, increases in house prices could trigger household mobility decisions in housing markets. This study empirically tests house price dynamics associated with the mobility of households in the public resale and private housing markets in Singapore. The results show that stochastic permanent breaks were found in the public housing resale prices and private housing prices. The relative prices drift apart occasionally, but mean-revert to a long-run fundamental equilibrium. Error correction mechanisms and lagged public housing prices were also found to have significant explanatory effects for price changes in the private housing markets. The results support the hypothesis that household mobility creates co-movements of prices in public and private housing submarkets in the long run.     

The Valuation of Real Capital: A Random Walk down Kungsgatan

This paper analyzes the temporal pattern of prices for single-family housing. We estimate models of house price dynamics using a repeat sales framework, and we use the results to test for a random walk in asset prices. For eight large samples of housing transactions, representing essentially all house sales in Sweden during a 12-year period, we reject the hypothesis that house prices follow a random walk in favor of a model of first-order serial correlation.     

Green Online vs Green Offline preferences on local public goods trade-offs and house prices

This paper focuses on the relationship between (i) house prices and (ii) local green public goods. The main objective of the paper is to analyse a specific house-pricing mechanism which reflects the utility of being Green Offline, i.e. having access to green areas, versus the utility derived from the ability to be Green Online. The focus will be on data from European Union countries, and in particular Germany. Our results show that on an aggregate level for the EU there appears to be a clear indication for an irrational house-pricing mechanism, ignoring the negative trade-off effect from Green Online and Green Offline public investments (goods and assets). Meanwhile, on an individual level, for the case of Germany, more detailed bounded rationality effects of fashion-driven supply on house pricing are observed, positively related to Green Online values but negatively related to high Green Offline preferences. In conclusion, we find that house prices throughout Europe do not reflect a rational social change in green preferences, but tend to irrationally overprice Green Online values, which may create instability on the local housing market in the long run.     

Demography and the demand for housing A reinterpretation of the Mankiw-Weil demand variable

This paper argues that the Mankiw-Weil forecast of a 47% decline in house prices over the period to 2007 is based on a serious misinterpretation of their demand variable. In a time-series context this variable, which comes from a cross-section regression of house values against the age of occupants, is a measure of the adult population, not the demand for housing services or the stock of houses. Econometric work suggests that in addition to adult population, real income, relative prices and real interest rates are important factors determining the aggregate demand for housing. To be credible, forecasts of house prices need to integrate information on demand with information on cost factors and the supply of new houses.     

House Prices and Housing Investment in Sweden and the UK: Econometric Analysis for the Period 1970–1998

We estimate quarterly dynamic housing demand and investment supply models for Sweden and the UK for the sample period 1970–1998, using an Error Correction Method (ECM). To facilitate comparisons of results between Sweden and the UK we model both countries identically with approximately almost the similar type of exogenous variables. The long–run income elasticities for Sweden and the UK are constrained to be 1.0, respectively. The long–run semi–elasticity for interest rates are 2.1 and 0.9 for Sweden and the UK. The speed of adjustment on the demand side is 0.12 and 0.23, while on the supply side it is 0.06 and 0.48 for Sweden and the UK, respectively. Granger causality tests indicate that income Granger causes house prices for Sweden, while for the UK there is also feedback from house prices to income. House prices Granger cause financial wealth for Sweden, while for the UK it is vice–versa. House prices cause household debt for Sweden, while for the UK there is a feedback from debt. Interest rates Granger cause house prices for the UK and Sweden. In both countries Tobin's q Granger cause housing investment. Generally, the diagnostic tests indicate that the model specifications were satisfactory to the unknown data generating process.     

Housing prices and macroprudential policies: Evidence from microdata

This paper examines the efficacy of macroprudential policies in addressing housing prices in a developing country like India, utilizing two novel databases on city-level house prices in India. Though the empirical models provide evidence of a sizable effect of the fundamental factors in influencing house price dynamics, they also reveal strong countercyclical properties of macroprudential tools i.e., loan-to-value (LTV) limit, risk weights, and provisioning requirements, in influencing housing price movements. Among the macroprudential policy tools, the LTV limit emerges as the most potent one in influencing the price dynamics. A granular investigation of the effectiveness of macroprudential tools suggests that the countercyclical effect of the regulatory ratios for large-sized mortgages is much stronger as compared with those for the small-sized mortgages, attributed mainly to investment motives associated with the large-sized loans. We also find the presence of asymmetry in the impact of loosening versus the tightening of the LTV limit, which can be attributed to the procyclical behavior of the house prices.     

货币和税收政策对我国住房价格的影响——基于VAR模型的实证研究

基于我国1999-2010年房地产市场季度数据,本文建立向量自回归模型(VAR)和向量误差修正模型(VEC),将住房供给和需求同时纳入模型,分析我国利率政策、信贷政策和税收政策对住房价格的影响。结果显示,贷款利率在短期内对住房供给有负效应,但长期效应不明显;贷款规模对住房价格的短期冲击明显,二者之间存在正相关关系;针对保有环节征税可以通过影响住房供给,从而有效抑制住房价格上升。根据我国住房供求特点,应优先选择税收工具,通过促进住房供给实现控制房价的政策目标。     

新时期完善我国房地产市场体系研究

由于我国住房供给制度不够完善,致使住房供给和需求不匹配。高收入者能够购买多套住房,而低收入者却买不起房,只能借助于住房保障体系解决居住问题。由于国内外多种因素的影响,市场商品房价格不断提高。政府若能积极完善好住房保障体系,便能解决社会中大多数低收入者的住房问题,逐步下降商品住房房价。本文认为,我国房地产市场的主要问题是供给和需求体系的不匹配,社会低收入者住房保障不够完善。故此总结了新时期我国房地产市场发展的新问题,并深入分析了房地产市场体系中的缺陷,提出了完善房地产市场体系的措施和方法。     

Housing supply price elasticities revisited: Evidence from international, national, local and company data

This paper re-examines one of the key parameters in housing economics – the price elasticity of housing supply. In the international literature, there is little agreement on its value or even on the appropriate methodology for its measurement. The paper argues that different spatial scales capture different aspects of the problem and, therefore, there is merit from comparing results at international, national, local and firm level. Using standardised models, there is evidence that the responsiveness of housing supply to market conditions is lower in Britain than in the US or Australia. However, supply is more responsive to the change in house prices than their level. With exceptions, most past research on supply in Britain concentrates on the national or regional dimensions. The paper finds that there are also insights to be obtained from examining local and firm level data. Local estimation across the Thames Gateway shows the importance of planning constraints on supply elasticities, but historical patterns of land use and geography are also important. Firm level data indicate that supply elasticities are greater for large firms than for small firms.     

House Prices, Housing Investment and Demography Forecasts from the LBS/Abbey National Model of the UK Housing Market

A new housing sector has been incorporated into the London Business School model. This article outlines the new housing model, summarizes the research which has gone into its construction, and presents a forecast of the UK housing market. Using the new housing model, we forecast a moderate recovery in the housing market in the later part of 1991 and 1992. This recovery is however short-lived and does not result in such high rates of house price increase as previous house price booms (Chart 1).
Cuts in interest rates following entry to the exchange rate mechanism of the EMS prompt a recovery in house prices from the middle of 1991. House price inflation then peaks with an increase in average UK house prices in 1992 of 11 per cent over the previous year. Increases in real personal disposable income are modest, by the standards of the 1980s, and for this reason the recovery does not develop the momentum of previous house price booms. House price inflation moderates again in 1993 falling back to around 7 per cent. Housing starts and housing investment recover only slightly from their present depressed levels.
the recovery in house prices is weaker than that foreseen in our April Forecast Release. This is because real personal disposable income is now forecast to grow more slowly during 1991. Sterling's membership of the ERM is followed by a fall in interest rates, but it is the timing of interest rate cuts rather than their magnitude which differs from the earlier forecast. The changed profile of interest rates has altered the house price forecast only marginally.     

寻找中国房价的领头羊——基于20个大城市数据的实证分析

城市房价存在明显的时空关联性。本文通过构建一个简单的消费者均衡模型,并利用全局和局部Moran指数,论证了35个大中城市的房价在空间上的相关性,进一步利用交叉谱技术分析了18个大中城市房价变动周期的关联性和领先滞后关系。结果发现：1．我国35个大中城市的房价存在显著的空间自相关。2．采用Fisher’s Kapper统计量和Kolmogorov-Smirnov统计量检验发现20个城市中除重庆和厦门外,房价波动都具有显著的周期性。3．在18个大中城市中,并不存在完全同步的房价周期。同一区域不同城市之间房价周期的关联性强度存在显著差异。即使在具有较强相关性的城市之间,房价变动也并不同步而是存在多种领先滞后关系。     

What drives returns to euro area housing? Evidence from a dynamic dividend–discount model

We apply a dynamic dividend–discount model to analyse housing returns for eight euro area countries comprising over 90% of euro area GDP, both individually and as a panel. A vector autoregressive model (VAR) is estimated for four variables – excess return to housing, rents, the real interest rate and real disposable per capita income – using quarterly data over the period 1978–2009. This empirical investigation – which allows for a decomposition of house price movements into movements in rent (cash-flow) and expected return news components – indicates that the bulk of the variability of euro area house price movements can be attributed to movements in fundamentals. There remains nonetheless an important but less sizeable influence of market-wide (or expected-return) variations in house prices. Country-specific estimation indicates considerable heterogeneity around the euro area result, both for what concerns long-term impacts and dynamics. Notably, changes in expected returns play a relatively strong role in the house prices of Ireland and Spain.     

The spatial impact of employment centres on housing markets

The spatial impact of employment centres on housing markets. Spatial Economic Analysis. Local economic growth tends to affect neighbourhood house prices unevenly. It has been observed that prime locations experience price hikes far in excess of the surrounding local area. Yet, this phenomenon is not well captured by existing economic models. This research provides a model of spatial and temporal interactions between housing and employment markets. The results show that rapid growth of employment centres increases house prices in neighbouring locations even after adjusting for fundamentals. It is concluded that spatial clustering of companies creates an option value for existing and potential employees that goes beyond ease of access for commuting purposes.     

House price convergence in euro zone and non-euro zone countries

This study investigates whether single currency use increased house price convergence among various countries. First, the panel unit root test results indicate that the house prices in euro zone countries were more correlated than the house prices in non-euro zone countries. Second, the house prices in various European countries converged towards the house prices in Germany, which uses the single currency, rather than towards those in the United Kingdom, indicating that single currency use increased the influence of the German housing market on other markets. Finally, the log t regression model, a new convergence test, was employed and determined that the house prices in various European countries were not converging before 1992 but began to do so after that year. After the euro was implemented as an official currency, the house prices in various countries converged towards a consistent level. On the basis of the relative transition paths, this study determines that the differences among housing markets in various countries have continuously decreased since 1992. The empirical results indicate that the law of one price is applicable to tradable goods and that single currency use can integrate housing markets, which include non-tradable goods.     

Housing Wealth and UK Consumption

There is widespread disagreement about the role of housing wealth in explaining consumption. However, much of the empirical literature is marred by poor controls for the common drivers both of house prices and consumption, such as income, income growth expectations, interest rates, credit supply conditions, other assets and indicators of income uncertainty (e.g. changes in the unemployment rate). For instance, while the easing of credit supply conditions is usually followed by a house price boom, failure to control for the direct effect of credit liberalisation on consumption can over‐estimate the effect of housing wealth or collateral on consumption. This paper (Janine Aron, John Muellbauer and Anthony Murphyi, October 2006) estimates an empirical model for UK consumption from 1972 to 2005, grounded in theory, and with more complete empirical controls than hitherto used.     

Macroeconomic determinants of international housing markets

This paper examines the long-term impact and short-term dynamics of macroeconomic variables on international housing prices. Since adequate housing market data are generally not available and usually of low frequency we apply a panel cointegration analysis consisting of 15 countries over a period of 30 years. Pooling the observations allows us to overcome the data restrictions which researchers face when testing long-term relationships among single real estate time series. This study does not only confirm results from previous studies, but also allows for a comparison of single country estimations in an integrated equilibrium framework. The empirical results indicate house prices to increase in the long-run by 0.6% in response to a 1% increase in economic activity while construction costs and the long-term interest rate show average long-term effects of approximately 0.6% and ?0.3%, respectively. Contrary to current literature our estimates suggest only about 16% adjustment per year. Thus the time to full recovery may be much slower than previously stated, so that deviations from the long-term equilibrium result in a dynamic adjustment process that may take up to 14 years.     

Determinants of house prices in Istanbul: a quantile regression approach

This paper uses quantile regression methods where a hedonic equation is estimated for each quantile of the conditional distribution of housing prices. The survey data are used to investigate the relationship between house prices and housing characteristics in Istanbul. This data set includes some housing characteristics of the dwellings like numbers of room, bathroom, heating system, location of house etc. In the results of this paper show some similarities and differences from earlier studies on housing prices. We find that age, cable tv, security, heating system, garage, kitchen area, increasing numbers of room and bathroom increase the house prices. Our findings also show that side variable which is a special factor for Istanbul real estate market has negative effect on the prices. It is clear that the factors of housing prices can change because of the properties of country, region or city. The results of this study may give some important interpretations for developing real estate market.