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.     

House price dynamics,conditional higher-order moments,and density forecasts

Most studies on housing price dynamics are only concerned with the conditional mean and variance, but overlook other higher-order conditional moments and the structural change characteristics inherent in housing prices. In order to take into account these two important issues, this study utilizes the generalized Markov switching GARCH model to explore house price dynamics and conditional distribution for US market over 1975Q1–2007Q4. The housing return follows two distinct dynamics: the bust regime and the boom regime. The volatility pattern is different in the bust and boom regimes. In addition, the conditional densities derived by the regime-switching model change dramatically over time and are significantly different from normal distribution. More importantly, the regime-switching model can detect in advance a weak US housing market such as the one that occurred in the middle of 2007. The in-sample fitting ability of regime-switching model, which incorporates higher-order moments, has significant improvements compared to the single-regime AR and AR-GARCH models. For the out-of-sample Value-at-Risk forecasting performance, the ability of regime-switching AR-GARCH model to forecast one-step-ahead density is better compared to the single-regime AR-GARCH model.     

Can learning explain boom-bust cycles in asset prices? An application to the US housing boom

This paper argues that boom-bust behavior in asset prices can be explained by a model in which boundedly rational agents learn the process for prices. The novel feature of the model is that learning operates in both the demand for assets and the supply of credit. Interactions between agents on either side of the market create complementarities in their respective beliefs, yielding strong internal propagation. The model is applied to US housing markets. Quantitative exercises explain the recent boom-bust in US house prices from observed fundamentals whilst replicating key moments of housing market variables at business cycle frequencies.     

Global imbalances,cross-market linkages,and the financial crisis: A multivariate Markov-switching analysis

Based on multivariate Markov-switching models, this paper presents new results on the interactions between global imbalances, credit spreads, housing markets, macroeconomic variables, commodities and equities during Q1-1987/Q1-2011. We show that rising global imbalances and the uncontrolled development of the US mortgage and housing markets have been deeply destabilizing the economy, with various shocks impacting subsequently equity markets and macroeconomic variables. But we also uncover, surprisingly, that the cross-market linkages with the commodity markets are strong. Finally, we identify that the US housing market lies at the epicenter of the crisis through its multiple and highly significant interactions with the other variables in the system (including the global imbalances). Sub-samples and alternative time series estimates are provided to check the statistical congruency of the various models.     

On the user cost and homeownership

This paper studies the differences in the cost of housing services for renters and homeowners and calculates the bias that results when we value owner-occupied housing services using a rental equivalence approach. Our framework is a life-cycle model with endogenous tenure choice with households facing idiosyncratic uninsurable earnings risk and housing price risk. We model houses as illiquid assets that provide collateral for loans. To analyze the impact of preferential housing taxation on the tenure choice and the bias, we consider a tax system that mimics that of the US economy. Namely, owner-occupied housing services are not taxed and mortgage interest payments are deductible. Through simulations, we show that a rental equivalence approach (relative to a user cost approach) overestimates the cost of housing services. The magnitude of the bias is very sensitive to both the income tax rate and the size of adjustment costs in the housing market.     

Are cyclical patterns of international housing markets interdependent?

This paper investigates the relationships among the US, UK, and Canadian housing markets from two aspects: the driving forces of housing cycles and the structures of correlation coefficients in different phases of housing cycles. The results indicate that the structures of driving forces and correlation coefficients are deeply hinged on the international housing markets. For the US and Canada pair, the driving forces of cyclical patterns are related to each other and the regime-switching correlation coefficients are always positive. However, for the US and UK pair and the UK and Canada pair, the driving forces are independent and there is no consistent pattern for the correlations.     

Housing price variability: national and local impacts

This article examines the influence of national and local forces on housing prices in 20 local US real estate markets during the recent housing price run-up and decline. We use reduced-form panel data fixed-effects models with robust SEs to determine the impact of national and local effects on housing prices in 20 US cities across time. A national home price index and mortgage rate are used to measure national impacts on the local markets. A mix of socio-economic variables estimates local impacts. We find no results indicating that national trends lack relevance in local markets; however, we find wide support for the additional inclusion of local socio-economic factors in all markets. The findings are consistent with an environment in which national polices and trends influence all markets; however local policymakers and investors can continue to expect geographic differences in market outcomes.     

“两房”与美国的住宅金融市场--兼论中国保障房融资机制创新

金融危机使“两房”和证券化倍受诟病。本文试图从历史、政治、经济、内生机制和外部市场环境等多个视角系统梳理美国住宅金融体制演变及“两房”和证券化的作用。通过梳理历史,客观评析了“两房”的创立对促进美国传统住宅金融向现代金融转变的积极作用,分析了网络经济泡沫破灭后金融市场环境和“两房”自身资产结构变化及诱发的危机的金融与实体经济因素。并着重剖析了后危机时代“两房”成为政府救市的工具运作机理和未来美国住宅金融市场改革的要点。最后提出我国保障房融资机制匮乏,应建立政策性住宅金融体系。     

How much does household collateral constrain regional risk sharing?

We construct a new data set of consumption and income data for the largest US metropolitan areas, and we show that the extent of risk-sharing between regions varies substantially over time. In times when US housing collateral is scarce nationally, regional consumption is about twice as sensitive to income shocks. We also document higher sensitivity in regions with lower housing collateral. Household-level borrowing frictions can explain this new stylized fact. When the value of housing relative to human wealth falls, loan collateral shrinks, borrowing (risk-sharing) declines, and the sensitivity of consumption to income increases. Our model aggregates heterogeneous, borrowing-constrained households into regions characterized by a common housing market. The resulting regional consumption patterns quantitatively match those in the data.     

Testing for rational bubbles in the US housing market

The presence of a bubble in the US housing market prior to the 2007 subprime mortgage financial crisis is investigated. This is done by looking into the relationship between house prices and rental prices, known as the price–rent ratio, which is an important measure of a potential deviation between house prices and its fundamental value. Additionally, the interest rate is taken into account since it is an important factor in determining demand for housing mortgages and thereby influencing house prices, and explosive behavior of house prices is considered. These relationships are investigated through a theoretical and econometrical framework. The empirical evidence suggests that there was a bubble in the housing market prior to the financial crisis, even when controlling for the decreasing interest rate and the fundamental information given by the rental price in the period. Explosiveness was the main source of the price increase, such that a bubble was present in the housing market after correcting for other fundamental factors. The econometric procedures used in the analysis may therefore be relevant for monitoring the housing market.     

Speculative bubbles or market fundamentals? An investigation of US regional housing markets

This paper investigates the existence of speculative bubbles in the US national and 21 regional housing markets over three decades (1978–2015). A new method for real-time monitoring exuberance in housing markets is proposed. By taking changes in the macroeconomic conditions (such as interest rate, per-capita income, employment, and population growth) into consideration, the new method provides better control for housing market fundamentals and thereby it is expected to significantly reduce the chance of false positive identification. Compared with the method of Phillips et al. (2015a, 2015b), the new approach finds a dramatic reduction in the number of speculative housing markets and shorter bubble episodes in the US. It locates only one bubble episode in the early-to-mid 2000s over the whole sample period in the national housing market. At the regional level, it identifies two periods of speculation: late 1980s and early-to-mid 2000s. The early-to-mid 2000s bubble episode lasts longer and involves 16 metropolitan statistical areas.     

From real estate to consumption: the role of credit markets in the USA

The aim of this article is to test whether the credit market conditions affect the strength of transmission of real estate wealth effects on household consumption in the US economy. Although many different works have dealt with the analysis of the existence of a real estate wealth effect, most of them as a reaction to the dramatic increase of housing prices in several OECD countries, there are only few papers analysing whether the consumption response depends on the positive or negative sign of the wealth shock and, as far as we know, none of them takes the effects of credit market conditions on that asymmetric response into account. This article tries to fill the existing gap in the literature on this matter. From an econometric perspective, we estimate the asymmetries in the consumption response within the momentum threshold autoregressive model (M-TAR) proposed by Enders and Siklos (2001), but following Stevans (2004), it is applied to a multivariate framework. The main results show that the credit market conditions play a significant role in the transmission of changes in real estate wealth to consumption. In addition, we find that there exists an asymmetric behaviour in the US aggregate consumption spending responses to real estate wealth and credit market shocks, which is only significant when a negative shock takes place.     

Housing and unemployment: The search for the “American Dream”

This paper constructs a model of search and bargaining across two different markets: the labor market and the housing market. Interestingly, the model highlights that housing prices and frictions in the housing market have a profound impact on labor market activity through the desire of workers to eventually purchase a home, the “American Dream.” In particular, higher housing prices adversely affect workers’ incentives in the labor market as employment can eventually lead to access to housing through the ability to purchase a home. Similarly, labor market frictions can impact housing market activity. Notably, tighter housing markets are associated with higher unemployment rates and less job creation. Consequently, our work suggests that policymakers should be very careful in implementing policies targeted towards housing – housing markets are likely to generate significant external effects to other sectors of the economy, especially the labor market.     

房地产“限购令”的调控机制与政策反思*——基于单中心双环城市模型的分析

近年来中国城市住房价格快速上涨,政府推出房地产“限购令”,以期调整房地产市场,控制城市房价。本文构建了带“限购令”政策约束条件的单中心双环城市住房市场模型,利用数值模拟的方法,从理论上分析房地产“限购令”的政策效果和作用机制。结果显示,限购政策使大中小城市房价均有所下跌,中小城市房价的下降幅度大于大城市的幅度,城市的投机性住房需求越大,限购政策的效果越明显。本文认为“限购令”作为非市场调控手段,仅可作权宜之计而非长久之策,应充分考虑城市的异质性特征,对限购政策进行辨证选择。     

Consumer confidence and economic activity: a factor augmented VAR approach

This study aims to analyse the effects of the consumer confidence on economic activity for the US market. We use the empirical factor-augmented vector autoregression (FAVAR) method, which enables us to incorporate a wide range of economic activity factors into the analysis. The consumer confidence index (CCI) is chosen as the principal variable that is presumed to represent the degree of optimism on the state of economic activity. The results show that consumer confidence and economic activity are strongly correlated for manufacturing-related factors, such as industrial production and inventories. We also observe strong relation among CCI and personal consumption expenditures, as well as housing market variables.     

Land and housing: The twin forces of non-balanced growth

In a three-sector closed economy where housing land is accumulated for the construction of houses, we depict significant effects of housing and land market on sectoral growth. We assume agriculture is the most intensive in the use of land, followed by manufacturing and then services. In the long run, land intensity differences in conjunction with labor growth contribute to sectoral growth gaps. In the short run, due to housing land accumulation, the economy transitions along a non-monotonic convergent path to the steady state. Using the US data, we quantify that land accounts for about one-tenth of long-run and short-run sectoral output growth gaps. We also incorporate sector-specific land-use restrictions to show that, despite these regulations, land and housing have qualitative effects on non-balanced growth.     

Speculative behavior in a housing market: Boom and bust

We study a housing market with household buyers, speculative investors and property developers in a Walrasian scenario. We show that in addition to the factors that affect the real demand of household buyers and the development cost of property developers, investors' speculative behavior is an important factor explaining housing price evolution and dynamics. In particular, investors' extrapolative expectations may drive the housing price to persistently deviate from its benchmark value and even to explode. In contrast, investors' mean-reverting strategy can balance out the position of trend extrapolators, which may stabilize an otherwise explosive housing market. Moreover, the evolutionary process of housing prices driven by investors' speculative behavior is path-dependent in the sense that different initial market conditions may result in different price paths, which corresponds to the localization property empirically documented in the real housing market. In addition, within the stylized model, we provide some policy implications through analyzing the limitation and effectiveness of policy adjustments via down payment and development cost, and find that the decrease of development cost is a better measure to adjust the housing market when it booms or busts.     

异质性预期、投资者行为与房价波动：上海和广州的双城记?

房地产市场中存在大量的投资者,其市场行为会使房价出现大幅的波动,从而引起市场不稳定。文章在引入投资者异质性预期假设的基础上,构建了包含房地产消费者、投资者、供给者在内的房地产市场均衡模型,分析了房地产市场中基本面型投资者和趋势型投资者的异质性行为对房价变动的影响,并利用上海和广州两个一线城市的实际数据进行了对比分析。研究结果表明：在房地产市场中,两类投资者对于未来房价不同的预期以及投资行为会引起房价的变动;上海投资者的行为整体上会使上海的房价始终处于不断上涨的趋势中,而广州投资者的行为会随着投资策略的转变而使静态下的“整体上推动房价趋势型变化”转变为“整体上将房价‘拉回’基本面价格”;房地产市场中的投资者占比会显著影响房价的变动趋势,当基本面型投资者占比上升时,房价偏离度和房价变动率降低,而当这类投资者占比达到峰值时,房价会出现拐点;投资者之间的策略转换速度也会通过引起基本面型投资者占比的变化,引起房价的频繁波动,而且策略转换速度越快,房价波动越频繁。     

Using time-varying transition probabilities in Markov switching processes to adjust US fiscal policy for asset prices

This paper tests for nonlinear effects of asset prices on the US fiscal policy. By modeling government spending and taxes as time-varying transition probability Markovian processes (TVPMS), we find that taxes significantly adjust in a nonlinear fashion to asset prices. In particular, taxes respond to housing and (to a smaller extent) to stock price changes during normal times. However, at periods characterized by high financial volatility, government taxation only counteracts stock market developments (and not the dynamics of the housing sector). As for government spending, it is neutral vis-a-vis the asset market cycles. We conclude that, correcting the fiscal balance and, notably, the revenue side for time-varying effects of asset prices provides a more accurate assessment of the fiscal stance and its sustainability.     

普通住宅房价与地价因果关系的检验及其政策含义

本文在综述房价与地价关系研究成果的基础上,结合土地市场与住宅市场二者属性,构建一个认识房价与地价关系的基础。理论研究表明,在不完全竞争的市场中,地价是房价上涨的一个重要但非决定性因素,土地需求作为引致需求受房价影响较大。同时,本文利用1998年至2009年季度数据对房价和地价进行G ranger因果关系检测,计量结果表明：短期内房价与地价互为影响,房价对地价影响更为显著;长期内,房价是地价的G ranger因,而不是相反。计量结果可以揭示房地产市场信号短期与长期传递的机制。在此基础上,本文提出房地产市场治理的应对之策。