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.     

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.     

Bubble-like housing boom–bust cycles: Evidence from the predictive power of households’ expectations

This study examines the role of households’ expectations in predicting the housing boom–bust cycles in the United States. It incorporates two nonlinear features of housing price dynamics: a threshold co-movement between households’ expectations and housing price growth and a structural break in their interrelation. It uses the monthly good-time-to-buy (GTTB) index as a proxy for households’ expectations about the U.S. housing market, and employs the structural break threshold vector autoregression (SBTVAR) to specify breakpoints in housing market dynamics during the recent decades. The findings indicate that shifts in interactions between households’ expectations and housing price growth are synchronous with the recent housing boom–bust cycles. The SBTVAR framework outperforms other models as it captures more of the housing market's unique dynamic characteristics. The GTTB index, which governs expectation regime-switching patterns, is able to signal the recent housing bust three periods in advance.     

Testing the efficiency of the Norwegian housing market

The question of whether or not the housing market is efficient is posed by an increasing number of economists, policymakers, homebuyers, and homesellers. This article tests the efficiency hypothesis on data from the housing market in Oslo over the period 1991–2002, employing the Case–Shiller time-structure test on a repeat-sales house price index and returns to housing. We demonstrate that both the repeat-sales house price index and returns contain time structure and that the housing market is characterized by inefficiencies. We also find, surprisingly, that the housing market consistently yields higher appreciation at lower volatility than the stock market over the period.     

Residential land use regulation and the US housing price cycle between 2000 and 2009

In a sample covering more than 300 cities in the US from January 2000 to July 2009, we find that more restrictive residential land use regulations and geographic land constraints are linked to larger booms and busts in housing prices. The natural and man-made constraints also amplify price responses to the subprime mortgage credit expansion during the decade, leading to greater price increases in the boom and subsequently bigger losses. Contrary to prior literature, our findings indicate a significant link between supply inelasticity and price declines during the bust, whereas Glaeser et al. (2008) found little evidence of such a relationship from an earlier downturn from 1989 to 1996.     

城市住房价格指数编制方法的拓展设计及实证检验

科学监测城市房价走势,在当前环境下尤为重要。为拓展国际通行方法编制国内单一城市房价指数的适用性,引入样本匹配重复交易法构建房价指数,以提高样本容量与可比性。基于上海数据的实证结果表明,相较于传统重复交易法和特征价格法,样本匹配重复交易法能更准确地反映住房价格变动,结果异常波动性更小,噪声影响程度更低,在克服样本代表性误差和变量缺失误差方面效果更显著,对编制国内城市房价指数具有较好应用价值。     

Monetary Policy and the Housing Market: A Structural Factor Analysis

This paper studies the role of the Federal Reserve's policy in the recent boom and bust of the housing market, and in the ensuing recession. By estimating a structural dynamic factor model on a panel of 109 US quarterly variables from 1982 to 2010, we find that, although the Federal Reserve's policy between 2002 and 2004 was slightly expansionary, its contribution to the recent housing cycle was negligible. We also show that a more restrictive policy would have smoothed the cycle but not prevented the recession. We thus find no role for the Federal Reserve in causing the recession. Copyright © 2013 John Wiley & Sons, Ltd.     

Spillover effects of subprime mortgage originations: The effects of single-family mortgage credit expansion on the multifamily rental market

The dramatic expansion in subprime mortgage credit fueled a remarkable boom and bust in the US housing market and created a global financial crisis. Even though considerable research examines the housing and mortgage markets during the previous decade, how the expansion in mortgage credit affected the rental market remains unclear; and yet, over 30 percent of all U.S. households reside in the rental market. Our study fills this gap by showing how the multifamily rental market was adversely affected by the development of subprime lending in the single-family market before the advent of the 2007/2008 subprime induced financial crisis. We provide evidence for a fundamentals based linkage by which the effect of an innovation in one market (i.e, the growth in subprime mortgage originations) is propagated through to another market. Using a large database of residential rental lease payment records, our results confirm that the expansion in subprime lending corresponds with an overall decline in the quality of rental payments. Finally, we present evidence showing that the financial performance of multifamily rental properties reflected the increase in rental lease defaults.     

HEDONIC PRICE INDEXES FOR RESIDENTIAL HOUSING: A SURVEY,EVALUATION AND TAXONOMY

Every house is different. It is important that house price indexes take account of these quality differences. Hedonic methods which express house prices as a function of a vector of characteristics (such as number of bedrooms and bathrooms, land area and location) are particularly useful for this purpose. I consider here some developments in the hedonic methodology, as it is applied in a housing context, that have occurred in the last three decades. A number of hedonic house price indexes are now available. However, it is often difficult to see how these indexes relate to each other. For this reason I attempt to impose some structure on the literature by developing a taxonomy of hedonic indexes, and then show how existing indexes fit into this taxonomy. Also discussed are some promising areas for future research in the hedonic field. In particular, greater use needs to be made of spatial econometric and nonparametric methods to exploit the increased availability of geospatial data. The main criticisms of the hedonic approach are evaluated and compared with those of the repeat‐sales and stratified median methods. The overall conclusion is that the advantages of the hedonic approach outweigh its disadvantages.     

Depreciation, Maintenance, and Housing Prices

This paper investigates the effect of homeowner maintenance and improvements on the depreciation rate for housing and on house price indexes. We examine three specifications of a hedonic house price model: one that includes a variable for age, as a proxy for depreciation, and an age–maintenance interaction variable; one that considers depreciation but ignores maintenance; and one that ignores both depreciation and maintenance. The remarks of the listing agent as to the property's condition is our proxy for the level of maintenance characterizing the home. In our sample, we find that poorly maintained homes depreciate at a much faster rate than do homes with average maintenance, and that well-maintained homes depreciate somewhat more slowly. Omitting maintenance from the variable specification has little impact on hedonic house price indexes constructed with our data, but failing to consider dwelling age imparts a significant and growing downward bias to the indexes. Monte Carlo simulations investigating various data specifications support our empirical findings.     

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.     

Hedonic prices and composite commodities

In this paper we conjecture and, to an extent, prove that recently noted restrictions required for the logical coherence and empirical relevance of hedonic price models make these models no more general than traditional housing services models. In particular, intra-urban variation in hedonic prices may not be substantively related to market equilibration at all, and therefore is not evidence for the existence of housing sub-markets. Moreover, in the case of jointly produced housing characteristics, the hedonic price models are found to be less general than the traditional homogeneous housing services models.     

Causes and Cures of the Great Recession

The Great Recession was not a failure of free markets. Rather it was a classic example of the undesirable unintended consequences of government intervention, both through expansionary monetary policy and misguided attempts to bolster the housing market in the USA. Getting government out of banking is the best way to end the disastrous boom and bust cycles that have characterised the last century and a half.     

Hedonic analysis of a housing market in disequilibrium

This paper tests the hypothesis that information about housing market activity and about specific dwellings becomes capitalized into single family dwelling prices through a disequilibrium adjustment process. A dynamic price adjustment model, which is an extension of the standard hedonic model widely used in the literature, is derived, specified, and tested with both micro and aggregated data from the city of Chicago and for the period 1972–1976. The results show that from 32 to 75% of the variance in dwelling prices, unexplained by the standard hedonic attributes under assumptions of equilibrium, is explained by market activity signals such as mortgage interest rates and neighborhood transaction rates of the preceding period. Dwellings about which there is less information, making comparison pricing difficult, are shown to command a price premium. The standard equilibrium hypothesis appears readily rejectable and better predictions are obtained from the disequilibrium specifications. Several directions for extending this line of research are discussed.     

A mixed index approach to identifying hedonic price models

Recent literature suggests identifying house price hedonic regressions by using instrumental variables, spatial statistics, the borders approach, panel data, and other techniques. We present an empirical application of a mixed index model, first proposed by Bowden [Bowden, R.J., 1992. Competitive selection and market data: the mixed-index problem. The Review of Economic Studies 59(3):625–633.] to identify hedonic price regressions. We compare the performance of the mixed index model to a traditional hedonic model and to a hedonic model that includes characteristics of the buyer of each house. We find the mixed index model outperforms the other models based on bootstrap distributions of predicted housing values, prediction variance, and predicted policy effects. The mixed index model distributions are less skewed and kurtotic than the other models, suggesting it more closely satisfies the classical linear regression assumption of normally distributed errors. Compared to the mixed index model, the traditional hedonic overstates the importance of lot size and school quality to house price and understates the importance of environmental quality.     

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.     

Credit allocation and the financial crisis: evidence from Spanish companies

The worldwide financial crisis of 2007–2008 raised serious concerns about the soundness of banks’ activities and about the extent to which banking regulation should supervise banks’ investment decisions. We contribute to this topic by examining the Spanish case, which has been emblematic of the bubble and burst dynamics in the credit market. In particular, we study the allocation of bank credit among Spanish companies from 1999 to 2014, showing that larger companies accumulated greater amounts of bank loans per unit of total assets, thus leading to a notable concentration. We also find that, during the Spanish boom period, bank loans shifted from the manufacturing to the construction industry, and in particular to the largest companies of the latter sector. This happened in spite of the high leverage of large construction firms, which was increasing also due to their growing debt. We argue that the higher operating benefits, reflecting the increase of the housing price during the boom period, overvalued construction firms as potential borrowers. The bankruptcy of several large construction companies during the Spanish crisis supports the need for monitoring and regulation, to avoid an excessive concentration of bank credit to a few large companies, especially if they belong to a specific sector.

     

Distributional aspects of public rental housing and rent control policies in Spain

This paper studies the importance of the economic advantages and some distributional consequences generated by public and subsidized rental housing as well as rent control policies in Spain. Individual benefits are defined as the difference between the rent the protected dwellings would have in the market, minus the rent actually paid for them. The market valuation is obtained with an hedonic function estimated for the uncontrolled private sector. Data for the Madrid Metropolitan Area in 1974 show that for both policies, benefits are of considerable importance, while its distribution among beneficiaries is very unsatisfactory according to horizontal and vertical equity criteria.     

Real option value over a housing market cycle

This paper analyzes how the dynamics of house prices are affected by the option to rebuild or enlarge existing dwellings. The nonlinear functional form for option value and zoning limits provides identification of changes in option value over the cycle. For homes with high development potential, our results show that about 40% of the price increases during the boom years after the fall of the Berlin Wall were related to increased option value. In the subsequent bust about 50% of their price decline was associated with decreased option value. For dwellings with low redevelopment potential 12% of the decline in real value can be attributed to changing option value.     

List price and sales prices of residential properties during booms and busts

This paper investigates the relationship between the list and sale price of residential properties over the housing cycle. In down or normal markets the list price generally exceeds the sales price; however, when the housing market is strong, homes sell for more than their list price. This observation is not consistent with the assumptions made in the standard model of home sellers’ search behavior. We consider alternative models. In one, sellers set list prices based on their expectations of future changes in sales prices and the arrival rate of buyers; however, demand shocks occur. This model partially explains our data from the Belfast, U.K. housing market, but it fails to predict the list to sales price ratio during a sustained housing boom. We next describe a model where sellers’ endogenously select their search mechanism depending on the strength of the housing market. We find support for the conjecture that sellers switch to an auction-like model during housing booms. There also is evidence that during a downturn in the market, sellers’ list prices are sticky.