Frothy Housing Markets and Local Stock-Price Movements

Prior empirical research finds habitat effects manifest in stock pricing among firms that share headquarters cities. We empirically investigate whether trends in residential real estate prices affect headquarters-city stock pricing phenomena for companies across U.S. metro areas for 1989?C2004. Specifically, we hypothesize that stocks of firms headquartered in ??hot?? residential real estate markets experience higher returns compared to stocks of firms from ??cold?? markets. We also hypothesize that stocks of firms headquartered in hot real estate markets display stronger return comovement with same-city stocks. We find support for these hypotheses during the 1999?C2004 sample period which coincides with the start of the housing bubble of the 2000?s; we find mixed results in earlier periods. Our findings indicate that city-specific home price patterns conditionally affect stock pricing of local firms, suggesting that investor behavior is influenced by localized shocks to household real estate wealth.     

Information, Search, and House Prices: Revisited

Buyers pay different prices for nearly identical homes. One explanation for this is that housing markets are thin, resulting in price bargaining between sellers and buyers. If the relative bargaining power of buyers varies, so will sales prices. One hypothesis is that the relative bargaining strength of buyers coming from outside the local market relative to that of local residents is weak, because distant buyers have high search costs and may know less about the nuances of the local market. Our results, based upon a large number of single-family home transactions from the state of Florida, lend support to this hypothesis. Another related hypothesis is that buyers?? price expectations are anchored to prices they were accustomed to at their previous residence. Hence, if they come from high price markets they will tend to pay more for their new home. This hypothesis is also supported by our results.     

Alternative Methods of Increasing the Precision of Weighted Repeat Sales House Prices Indices

Weighted repeat sales house price indices have become one of the primary indicators used to identify housing market conditions and to estimate the amount of equity homeowners have gained through house price appreciation. The primary reason for the acceptance of this methodology is that it derives a location specific (typically, census division, state or metropolitan area) average change in house prices from repeated observations of individual house prices. It is this repeat attribute that allows repeat sales price indices to claim that it is a preferable index which does a better job of holding quality constant. The amount of time between the two observed prices for a single property is determined by when the home transacts. Some homes transact twice in a period of months and others do not transact for decades. It is likely that individual house price appreciation rates vary from the mean appreciation rate, as estimated by the index, in a systematic fashion. In general, the longer the time between transactions the more variance there is in individual house price appreciation. This paper extends this concept to include new dimensions. For instance, houses that appreciate faster than the mean, as estimated by the index for that location, may experience a different variation structure than homes that appreciate slower. This process can be viewed as an asymmetric treatment of the variance of house price appreciation around the estimated index. In addition, the variance of expensive and affordable homes may also be different and time varying. This paper finds evidence that adding the dimensions of price tiers and asymmetry to the variance estimate has merit and does affect the estimated index as well as homeowner equity estimates. Homeowner equity estimates are especially sensitive to these added dimensions because they depend on both the revised index and the estimated variances, which are specific to each dimension considered—time between transaction, asymmetry, and price tier.     

The Construction of Residential Housing Price Indices: A Comparison of Repeat-Sales,Hedonic-Regression,and Hybrid Approaches

This article examines a number of hypotheses that underpin the repeat-sales and hedonic approaches to the construction of housing price indices, as well as the practical problems associated with the implementation of either approach. We also examine a hybrid procedure that combines elements of both the repeat-sales and hedonic-regression techniques. For our sample of individual home sales in Oakland and Fremont California over an 18-year period, repeat-sales methods are subject to sample selection bias; the maintained assumption of time constancy of implicit prices of housing attributes is violated; the repeat-sales estimator is extremely sensitive to influential observations; and the usual method used to correct for heteroskedasticity in repeat-sale housing returns is inappropriate in our sample. Hedonic techniques are better suited to contend with index number problems per se, as they can accommodate changing attribute prices over time. They also appear to give rise to more reliable estimates of price indices, as unusual observations have less effect on estimated price indices. Drawbacks of the hedonic approach include the usual concern with omitted attributes, and their effect on the estimated price index.     

Spatial Dependence and House Price Index Construction

Accurate estimation of prevailing metropolitan housing prices is important for both business and research investigations of housing and mortgage markets. This is typically done by constructing quality-adjusted house price indices from hedonic price regressions for given metropolitan areas. A major limitation of currently available indices is their insensitivity to the geographic location of dwellings within the metropolitan area. Indices are constructed based on models that do not incorporate the underlying spatial structure in housing data sets. In this article, we argue that spatial structure, especially spatial dependence latent in housing data sets, will affect the precision and accuracy of resulting price estimates. We illustrate the importance of spatial dependence in both the specification and estimation of hedonic price models. Assessments are made on the importance of spatial dependence both on parameter estimates and on the accuracy of resulting indices.     

The Hierarchical Trend Model for Property Valuation and Local Price Indices

This paper presents a hierarchical trend model (HTM) for selling prices of houses, addressing three main problems: the spatial and temporal dependence of selling prices and the dependency of price index changes on housing quality. In this model the general price trend, cluster-level price trends, and specific characteristics play a role. Every cluster, a combination of district and house type, has its own price development. The HTM is used for property valuation and for determining local price indices. Two applications are provided, one for the Breda region, and one for the Amsterdam region, lying respectively south and north in The Netherlands. For houses in these regions the accuracy of the valuation results are presented together with the price index results. Price indices based on the HTM are compared to a standard hedonic index and an index based on weighted median selling prices published by national brokerage organization. It is shown that, especially for small housing market segments the HTM produces price indices which are more accurate, detailed, and up-to-date.     

International harmony measures of accounting policy: comparative statistical properties

Van der Tas's (1988) I index and the between-country C index introduced by Archer et al. (1995) are competing measures of international harmony. We present comparative statistical properties of these indices, via a simulation study covering three accounting methods in 10 countries, with uniform, bimodal and unimodal distributions of companies across accounting methods. The indices are also adjusted for non-disclosures using techniques developed by Archer and McLeay (1995) and Archer et al. (1995). The I index and the between-country C index are mathematically equivalent in the two-country case even in the presence of non-disclosures. As more countries are compared, the two indices diverge. The means and standard deviations of the I index, with a correction proposed by Archer and McLeay (1995), decrease and there is little skewness or kurtosis. In contrast, as more countries are compared, the between-country C index exhibits more stability in means, lower standard deviations, higher skewness and kurtosis. The between-country C index may be superior to the corrected I index because (i) between-country C index means approximate their ‘expected values’ (where all observations equal expected values) more closely than do corrected I index means: and (ii) between-country C index means are more stable than corrected I index means where the data come from stable distributions.     

The Impact of Property Condition Disclosure Laws on Housing Prices: Evidence from an Event Study Using Propensity Scores

We examine the impact of seller??s Property Condition Disclosure Laws on residential real estate values. A disclosure law may address the information asymmetry in housing transactions shifting risk from buyers and brokers to the sellers and raising housing prices as a result. We combine propensity score techniques from the treatment effects literature with a traditional event study approach. We assemble a unique set of economic and institutional attributes for a quarterly panel of 291 US Metropolitan Statistical Areas (MSAs) across 50 US States spanning 21?years from 1984 to 2004. The study finds that the average sales price of houses in a metropolitan area increases by an additional 3 to 4% over a 4?year period if the state adopts a Property Condition Disclosure Law, which is consistent with approximately a 19 basis point or 6.4% reduction in the risk premium associated with purchasing owner-occupied housing. When we compare the results from parametric and semi-parametric (propensity score) event analyses, we find that the semi-parametric analysis generates moderately larger estimated effects of the law on housing prices.     

Constructing Commercial Indices: A Semiparametric Adaptive Estimator Approach

Constant-quality commercial indices generated by ordinary least squares may suffer an efficiency loss due to leptokurtosis caused by outliers in transactions data. When the subsequent nonnormality occurs, substantial improvement in index precision is obtained by estimating the hedonic model using a semiparametric adaptive estimator technique. When this method was applied to 1,846 office transactions that occurred in the Phoenix metropolitan area from January 1997 through June 2004, a substantial standard error reduction of approximately 9% was realized relative to ordinary least squares estimates. The difference in average returns between the semiparametric method and ordinary least squares was about 0.25% in each period, which represents a substantial increase in commercial property index precision. JEL Classification C4 R0     

Identification and critical time forecasting of real estate bubbles in the USA

We present a hybrid model for diagnosis and critical time forecasting of real estate bubbles. The model combines two elements: (1) the Log Periodic Power Law Singular model to describe endogenous price dynamics originated from positive feedback loops among economic agents; and (2) a diffusion index that creates a parsimonious representation of multiple macroeconomic variables. We explicitly compare the in-sample and out-sample behaviour of our model on the housing price indices of 380 US metropolitan areas. Empirical results suggest that the model is able to forecast the end of the bubbles and to identify the variables that are highly relevant during the bubble regime.     

Purchasing power parity, unit roots, and dynamic structure

Recent studies of purchasing power parity (PPP) account for the possible presence of unit roots in nominal exchange rates and relative price indices by applying standard unit-root tests to real exchange rates, which are ratios of nominal exchange rates and relative price indices. These studies occasionally find evidence of PPP, but as a whole, the evidence is not definitive. Standard unit-root tests impose a restrictive dynamic structure between nominal exchange rates and relative price indices. I specify and estimate a generalized dynamic structure. I reject the dynamic restrictions implicit in standard unit-root tests of PPP, and find stronger evidence of PPP than do most other recent studies.     

Local Traits and Securitized Commercial Mortgage Default

We expand on the standard commercial mortgage default model and create a new model by looking beyond the usual factors of option value, insolvency, property type, region, originator type, state foreclosure laws and macroeconomic measures. The new model incorporates measures of local economic conditions, specifically MSA-level commercial property market conditions, county level unemployment, and local home price appreciation. We estimate our new model using a dataset containing the performance histories of over 30,000 CMBS loans that were originated between 1998 and 2012. We find that those local trait variables affect the default rate of CMBS loans significantly and provide improved explanatory power over the standard model. We further explore the impact of local home price measures by comparing the explanatory power of lagged and contemporaneous home price indexes, comparing the power of home price indexes at the state, county, and zip-code level, examining the interaction of home price indexes with commercial property type, looking at the impact of home price indexes over time, and at the impact of introducing local commercial land price indexes. We find that local residential house price-related measures provide a high quality and high frequency signal of local market conditions.     

Cointegration and causality between macroeconomic variables and stock market returns

The purpose of this study is to investigate whether current economic activities in Korea can explain stock market returns by using a cointegration test and a Granger causality test from a vector error correction model. This study finds that the Korean stock market reflects macroeconomic variables on stock price indices. The cointegration test and the vector error correction model illustrate that stock price indices are cointegrated with a set of macroeconomic variables—that is, the production index, exchange rate, trade balance, and money supply—which provides a direct long-run equilibrium relation with each stock price index. However, the stock price indices are not a leading indicator for economic variables, which is inconsistent with the previous findings that the stock market rationally signals changes in real activities.     

Investing in wine,precious metals and G-7 stock markets – A co-occurrence analysis for price bubbles

This paper used the GSADF test to determine the periods defined in this paper as price bubbles in the three markets studied, i.e. the investment wine market, precious metal market and national stock market indices of G-7 countries. The results obtained enabled the calculation of the values of the phi correlation coefficients, which served the research objective of assessing the co-occurrence of price bubbles in the markets analysed. The research period adopted in the study was December 2003 to March 2022, and the data were examined at a monthly frequency.Based on the results, it was concluded that the periods of price bubbles in the investment wine market, relative to the other investments studied, are long and amount to a maximum of 50% of the time studied. Price bubble periods for investments in the DAX index and the Rhone 100 index or the Rest of the World 60 index will lower the risk of an investment portfolio in times of greatest turbulence in these markets. In addition, the co-occurrence of price bubbles was not confirmed for the S&P500 index and the Bordeaux Legends 40 investment. Moreover, no co-occurrence of price bubbles was identified between investments in most of the wine indices studied and investments in silver and gold. However, the same phenomenon was not confirmed for platinum investments.     

Selectivity,Quality Adjustment and Mean Reversion in the Measurement of House Values*

This paper develops a model of price formation in the housing market which accounts for the non-random selection of those dwellings sold on the market from the stock of existing houses. The model we develop also accounts for changes in the quality of dwellings themselves and tests for mean reversion in individual house prices. The model is applied to a unique body of data representing all dwellings sold in Sweden's largest metropolitan area during the period 1982–1999. The analysis compares house price indices that account for selectivity, quality change and mean reversion with the conventional repeat sales models used to describe the course of metropolitan housing prices. We find that the repeat sales method yields systematically large biased estimates of the value of the housing stock. Our comparison suggests that the more general approach to the estimation of housing prices or housing wealth yields substantially improved estimates of the course of housing prices and housing wealth.     

Optimal Portfolio Choices, House Risk Hedging and the Pricing of Forward House Transactions

This paper develops a utility indifference model for evaluating various prices associated with forward transactions in the housing market, based on the equivalent principle of expected wealth utility derived from the forward and spot real estate markets. Our model results show that forward transactions in the housing market are probably not due to house sellers?? and buyers?? heterogeneity, but to their demand for hedging against house price risk. When the imperfections of real estate markets and the risk preferences of market participants are taken into consideration, we are able to show that the idiosyncratic risk premium, which mainly depends on the participants?? risk preferences and the correlation between the traded asset and the real estate, is a remarkable determinant of house sellers?? and buyers?? forward reservation prices. In addition, we also find that the market clearing forward price usually will not converge toward the expected risk-neutral forward price. The sellers?? or buyers?? risk aversion degrees and market powers are also identified to play crucial roles in determining the clearing forward price.     

Estimating price trends for residential property: A comparison of repeat sales and assessed value methods

The repeat sales methodology for estimating residential price indices is based on actual appreciation of individual properties. On the other hand, the repeat sales method wastes data, typically discarding a large percentage of all sales. This article explores two issues related to the subsample of repeat sales. First, are paired sales representative of the entire population of properties that sold? Second, is there evidence that sample selectivity biases the price trend estimates? Evidence from five metropolitan areas supports a negative answer to the first question and the second question. It appears that a “lemon” or “starter home” effect causes repeat residential sales to be a biased subsample of all transactions. Cumulative price trends for the repeat subsamples can differ from the full samples over periods ranging from two to ten quarters. While short-term price trends can differ widely, there are no systematic differences among the samples over long periods of time (e.g., three years or more).     

National Transaction-based Land Price Indices

Using data on a large sample of land transactions, this paper develops quarterly national land price indices for residential, commercial, and industrial land use categories over the 20?years period from 1991 to 2009. We find significant differences in variability across land uses, with residential exhibiting the most volatility. Our particular interest in this paper is to compare intertemporal land prices with other prominant real estate indices. In all cases, the transaction-based land price indices leads the other indices.     

Economic conditions, enforcement, and criminal activities in the district of Abidjan

Based on 1978?C2007 annual data on crimes recorded by the criminal police division and through a simultaneous equations model, we have shown that the probability of apprehension affects negatively the incidence of thefts and homicides as well as the incidence of aggregate crime. We have also provided evidence that exogenous shocks such as the devaluation of the CFA franc, the military coup d??état, and the civil war have significantly influenced criminal activity in Abidjan. The civil war which occurred in C?te d??Ivoire, while driving to a booming of property crimes, has deterred violent crimes given the crackdown effect of temporary massive presence of military and paramilitary forces in the streets of the city of Abidjan. In addition, using a sample of 1,600 households, our inquiry on the likelihood of crime victimization has pointed out that the risk of being victimized of any kind of crime increases with the income; the fact of being displaced due to the civil war and the decrease in the number of police stations in the neighborhood.     

Does bancassurance add value for banks? - Evidence from mergers and acquisitions between European banks and insurance companies

This paper investigates the risk and wealth effects of 72 mergers and acquisitions between banks in Europe and insurance companies during the period 1989-2004. The empirical results indicate that acquirers’ total risks remain constant relative to the world, home market indices and home banking indices. There are no changes for the systematic risks (beta) with respect to the world market index or the home banking index. After removing world and home market indices effect, systematic risk against home banking index reduce significantly for domestic deals. In addition, positive wealth effects are documented. Two factors have contributed to the bidders’ cumulative abnormal returns (CARs): relative deal size and being a serial acquirer. Finally, change of beta shows negative relations with CARs.