Measuring a boom and bust: The Sydney housing market 2001–2006

The Sydney housing market peaked in 2003. The period 2001–2006 is, therefore, of particular interest since it captures a boom and bust in the housing market. We compute hedonic, repeat-sales and median price indexes for five regions in Sydney over this period. While the three approaches are in broad agreement regarding the timing of the turning point in the housing market, some important differences also emerge. In particular, we find evidence of sample selection bias in our hedonic and repeat-sales data sets (with the former focusing more on better quality dwellings and the latter more on lower quality dwellings). These sample selection biases could in turn cause bias (in opposite directions) in our hedonic and repeat-sales indexes. Median indexes may likewise be biased as a result of an apparent decline in the average quality of dwellings sold in the latter part of the sample. We also find evidence of convergence in prices across regions during the boom and divergence in the subsequent bust.     

Efficiency and Seasonality in the UK Housing Market, 1991–2001*

This paper considers the informational efficiency of the UK owner‐occupied housing market over the period 1991–2001. Original small‐area, monthly, quality‐adjusted house price index series are developed from raw housing transaction observations for a number of UK counties and cities. These series are then tested in an autoregressive setting for characteristics indicative of weak market efficiency and seasonality. The major conclusion drawn is that there exists little evidence to support notions of inefficiency in these markets over the period considered.     

Dissecting the myth of the house price in Chinese metropolises: allowing for behavioral heterogeneity among investors

This paper aims to demystify the housing boom in Chinese metropolises by allowing for behavioral heterogeneity among investors. We construct an agent-based model where investors are categorized into two groups: fundamentalists and chartists. In addition, the investment strategy switching is allowed between these two groups contingent on the historical performance. Using the data of five Chinese metropolises over the period 2008–2014, the results suggest that chartists dominate the housing market and make the house price maintain an upward trend, while fundamentalists play a stabilizing role. Specifically, fundamentalists can serve as a “price anchor” in the market, because the proportion of the fundamentalists is negatively associated with both the growth rate of the house price and the deviation relative to the fundamental value. Overall, the impact of the chartists on the house price is much greater than that of the fundamentalists, which contributes to the ever-increasing house price in Chinese metropolises.

     

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.     

Subprime lending and the housing bubble: Tail wags dog?

The cause of the “housing bubble” associated with the sharp rise and then drop in home prices over the period 1998–2008 has been the focus of significant policy and research attention. The dramatic increase in subprime lending during this period has been broadly blamed for these market dynamics. In this paper we empirically investigate the validity of this hypothesis vs. several other alternative explanations. A model of house price dynamics over the period 1998–2006 is specified and estimated using a cross-sectional time-series data base across 20 metropolitan areas over the period 1998–2006. Results suggest that prior to early 2004, economic fundamentals provide the primary explanation for house price dynamics. Subprime credit activity does not seem to have had much impact on subsequent house price returns at any time during the observation period, although there is strong evidence of a price-boosting effect by investor loans. However, we do find strong evidence that a credit regime shift took place in late 2003, as the GSE’s were displaced in the market by private issuers of new mortgage products. Market fundamentals became insignificant in affecting house price returns, and the price-momentum conditions characteristic of a “bubble” were created. Thus, rather than causing the run-up in house prices, the subprime market may well have been a joint product, along with house price increases, (i.e., the “tail”) of the changing institutional, political, and regulatory environment characteristic of the period after late 2003 (the “dog”).     

What factors drive the price–rent ratio for the housing market? A modified present-value analysis

We consider which factors determined the price–rent ratio for the housing market in 18 U.S. metropolitan statistical areas (MSAs) and at the national level over the period of 1975–2014. Based on a present-value framework, our proposed empirical model separates the price–rent ratio for a given market into unobserved components related to the expected real rent growth and the expected housing return, but is modified from standard present-value analysis by also including a residual component that captures non-stationary deviations of the price–rent ratio from its present-value level. Estimates for the modified present-value model suggest that the present-value residual (PVR) component is always important and sometimes very large at the national and MSA levels, especially for MSAs that have experienced frequent booms and busts in the housing market. In further analysis, we find that house prices in MSAs that have larger PVR components are more sensitive to mortgage rate changes. These are also the MSAs with less elastic housing supply. Also, comparing our results with a recent statistical test for periodically-collapsing bubbles, we find that MSAs with large estimated PVR components are the same MSAs that test positively for explosive sub-periods in their price–rent ratios, especially during the 2005–2007 subsample. Our approach allows us to estimate the correlation between shocks to expected rent growth, the expected housing return, and the PVR component. We find that the expected housing return and movements in the PVR component are highly positively correlated implying an impact of the expected housing return on house prices that is amplified from what a standard present-value model would imply. Our results also show that most of the variation in the present-value component of the price–rent ratio arises due to the variation in the expected housing return.     

House price risk and the hedging benefits of home ownership

Using a repeat-sales methodology, this paper finds that estimates of house price risk based on aggregate house price indices substantially underestimate the true size of house price risk. This is the result of the fact that aggregate house price indices average away the idiosyncratic volatility in house prices. Additional results show that the idiosyncratic risk exceeds the hedging benefits of home ownership. These results imply that for many home owners, owning a house may well add more price risk than it hedges away. These findings are based on a detailed dataset of individual housing transactions in the Netherlands.     

Hedonic versus repeat-sales housing price indexes for measuring the recent boom-bust cycle

Standard housing price indexes rely on strong constant-quality assumptions and often conflict. Hedonic price indexes overcome limitations of median price and repeat-sales indexes but their implementation has been limited by a lack of data. This paper constructs hedonic indexes at the zip code level for the Los Angeles and San Diego metropolitan areas using considerably more detailed data than previously available. Our sample was collected by a mortgage technology firm, and consists of almost 1.1 million transactions during the boom-bust cycle since 2000. Our hedonic regressions include new spatial models that capture correlations within submarkets (using zip codes as proxies) and allow temporal asymmetry. Compared to a repeat-sales price index constructed from the same data, the hedonic indexes indicate that the market peaked about 11 months later in Los Angeles and about 2 months earlier in San Diego, show less pre-peak appreciation and post-peak depreciation in low-tier housing and more pre-peak appreciation in high-tier housing. We also find that the intensity of the cycle varies greatly across zip codes and price-tiers in a pattern consistent with foreclosure activity.     

House prices and consumer welfare

We develop a new approach to measuring changes in consumer welfare due to changes in the price of owner-occupied housing. In our approach, an agent's welfare adjustment is defined as the transfer required to keep expected discounted utility constant given a change in current house prices. We demonstrate that, up to a first-order approximation, there is no aggregate change in welfare due to price increases in the existing housing stock. This follows from a simple market clearing condition where capital gains experienced by sellers are exactly offset by welfare losses to buyers. We show that this result holds (approximately) even in a model that accounts for changes in consumption and investment plans prompted by current house price changes. There can, however, be changes in welfare due to additions to the stock of housing, or to changes in the price of renovating and upgrading the existing stock of housing. For the United States, we estimate the welfare cost of house price appreciation to be an average of $127 per household per year over the 1984–1998 period.     

The down-payment constraint and UK housing market: Does the theory fit the facts?

This paper considers empirical implications of the down-payment constraint for the UK housing market. It shows that, at the aggregate-level, models of the housing market with this constraint are consistent with a number of stylized facts. The paper then exploits variation across local housing markets and considers how leverage affects the response of house price inflation to shocks. The evidence, based on data for 147 district-level housing markets for the period 1993–2002, suggests that a large incidence of households with high leverage (loan-to-value ratios) raises the sensitivity of house prices to a shock. This is also consistent with the down-payment constraint model.     

Forecasting the US housing market

The recent housing market boom and bust in the United States illustrates that real estate returns are characterized by short-term positive serial correlation and long-term mean reversion to fundamental values. We develop an econometric model that includes these two components, but with weights that vary dynamically through time depending on recent forecasting performances. The smooth transition weighting mechanism can assign more weight to positive serial correlation in boom times, and more weight to reversal to fundamental values during downturns. We estimate the model with US national house price index data. In-sample, the switching mechanism significantly improves the fit of the model. In an out-of-sample forecasting assessment the model performs better than competing benchmark models.     

The housing bubble and a new approach to accounting for housing in a CPI

Over the course of the recent house price bubble in the United States, the price of homes rose rapidly from 1999 Q4 to 2005 Q4 (11.3% annually as measured by the Case-Shiller index, and 8.4% annually as measured by the Federal Housing Financing Agency) but slowly as measured by owner equivalent rents (3.4%), so measured core inflation remained relatively docile during this period, since only rents are used to measure inflation for housing services in the United States. Over the last several decades, the US Bureau of Labor Statistics (BLS) has experimented with both rental equivalence and user cost approaches for accounting for owner occupied housing (OOH) services in the CPI. We explain the basics of these approaches, and outline the BLS experiences with using them. This assessment leads us to conclude that the time has come to try a new approach: the opportunity cost approach. We argue this approach has advantages over both the conventional rental equivalence and user cost approaches, though it embeds components of the measures for both those approaches and builds solidly on the research of Verbrugge and others at the BLS. Also, we take up empirical issues that must be faced regardless of which of the approaches discussed is adopted. We explain how the repeat-sales and various hedonic regression methods can be placed in a common framework, thereby facilitating understanding of the properties of and the tradeoffs between the methods. We also consider measurement complications that arise because the land and structure components of properties depreciate at different rates.     

Do house prices impact business starts?

At the national level, business starts and housing prices both fell dramatically over the 2007–2009 period. Using a proprietary database of business starts this paper quantitatively models the interaction between house price and business starts from 2005 to 2009. We identify the impact by exploiting the cross-sectional variation in house price changes during the period. Controlling for observable and unobservable city characteristics, we find the significance of a robust relationship between house prices and business starts depends on the size of the business starts; a robust link exists between house prices and very small business, whereas, no significant robust link is seen for large business starts.     

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.     

Issues in measuring a monthly house price index in New Zealand

The sale price appraisal ratio (SPAR) method, which takes the ratios of the current house prices and their previous assessed values to construct an index, has been applied in New Zealand since the 1960s. This paper uses housing market transaction data for 12 cities in New Zealand (1994–2004) to develop monthly SPAR house price indices. These indices were subjected to a variety of statistical tests and benchmarked against the comparable monthly quality controlled weighted repeat sales indices. Finally, the paper provides some useful suggestions for future research based on the SPAR index and other alternative house price indices, such as the assessed value (AV) method.     

Daily House Price Indices: Construction,Modeling, and Longer‐run Predictions

We construct daily house price indices for 10 major US metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat‐sales method that closely mimics the methodology of the popular monthly Case–Shiller house price indices. Our new daily house price indices exhibit dynamic features similar to those of other daily asset prices, with mild autocorrelation and strong conditional heteroskedasticity of the corresponding daily returns. A relatively simple multivariate time series model for the daily house price index returns, explicitly allowing for commonalities across cities and GARCH effects, produces forecasts of longer‐run monthly house price changes that are superior to various alternative forecast procedures based on lower‐frequency data. Copyright © 2015 John Wiley & Sons, Ltd.     

关于提高住宅有效购买力的几点思考

随着我国住房制度改革的推进 ,房地产业面临着前所未有的发展机遇。然而 ,几年过去了 ,我们却不得不面对住宅潜在需求和有效需求不足的尖锐矛盾。产生这一现象的原因是多方面的 ,笔者认为最主要的原因在于商品住宅价格偏高、住房金融市场发展缓慢以及住房交易市场不健全三个方面。因此 ,要使住宅产业真正成为消费热点和新的经济增长点 ,就必须努力降低现有商品住宅价格、加快住房金融市场的发展以及完善住房交易市场     

基于土地杠杆的住房价格动态分解

住房可分为土地和依附于土地的建筑物两部分。基于土地杠杆基本概念,利用我国35个大中型城市数据,将住房价格动态分解为土地价格和建筑物价格,考察我国住房价格增长中土地增值的贡献比例与速度。对土地杠杆假说的实证检验发现,拥有更高土地杠杆的住房,其增值速度会更快。通过对土地杠杆假说的实证研究,对于了解潜在的房价决定机制、价格指数建立、土地利用限制的成本评估,以及制定住房政策和评估住房市场的合理性等,都具有重要的作用。     

Evolution of price effects after one-day abnormal returns in the US stock market

This paper provides a comprehensive analysis of price effects after one-day abnormal returns and their evolution in the US stock market, using Dow Jones Index over the period 1890–2018. We utilise several statistical tests and econometric methods (the modified cumulative abnormal return approach, regression analysis with dummy variables, R/S analysis (Hurst, 1951), and the trading simulation approach). The results suggest that a strong momentum effect between 1940 and 1980 after a day of positive abnormal returns was present in the US stock market, and it was exploitable for profit. However, after the 1980s this has since disappeared. Overall, price effects after one-day abnormal returns during the analysed period tend to be unstable in terms of their strength and direction (momentum or contrarian effect). Nowadays, the evidence for the price effects after one-day abnormal returns in the US stock market is weak. Our results, therefore, are consistent with the Adaptive Market Hypothesis (Lo, 2004).     

Measuring housing affordability: Looking beyond the median

We draw a distinction between the concepts of purchase affordability (whether a household is able to borrow enough funds to purchase a house) and repayment affordability (the burden imposed on a household of repaying the mortgage). We operationalize this distinction in the context of a new methodology for constructing affordability measures that draws on the value-at-risk concept and takes account of the whole distribution of household income and house prices rather than just the median. Empirically we find that the distinction between purchase and repayment affordability can be pronounced. In the Sydney prime mortgage market over the period 1996–2006, repayment affordability deteriorated very significantly while purchase affordability remained quite stable. This difference can be attributed to the loosening of credit constraints in the mortgage market which it seems has carried through primarily into higher house prices rather than an improvement in purchase affordability. We also show how median house-price-to-income ratio measures of affordability can be extended to take account of the whole distribution of income and house prices, and how as a result of differential skewness in the house price and income distributions the housing affordability problem may be significantly worse for lower income households than suggested by standard median measures.