Are Rising College Premiums Capitalized into House Prices? Evidence from China

Many areas in China experienced steeply rising house prices beginning in 2003. We test whether a change in local residency requirements may have played a role in driving up house prices in some places by tying access to Chinese universities to local homeownership status in the presence of a rising college premium. We generate a novel dataset that combines China housing market and neighborhood data with household and university admission data. We find evidence of capitalization effects and a sizable increase in the likelihood of homeownership postpolicy change in places with the greatest preferential access to China's elite universities.     

Marking Single–Family Property Values to Market

This paper is the text of the 2001 Presidential Address for the American Real Estate and Urban Economics Association. House price prediction accuracy is a function of: (1) the procedure used to identify within–metropolitan–area housing submarket boundaries, (2) the econometric technique used to estimate the parameters of the house price model and (3) the characteristics of the local housing market. This paper empirically examines several procedures for delineating within–metropolitan–area housing submarket boundaries. In addition, the paper examines the increase in prediction accuracy that can be achieved by employing spatial econometric techniques to spatially adjust ordinary least squares house price predictions. Finally, the paper examines the influence that local housing market characteristics have on house price prediction accuracy. Housing market characteristics examined here are: (1) structural characteristics of neighborhood properties, (2) heterogeneity of the neighborhood housing stock and (3) housing market liquidity. Prediction accuracy is examined using hedonic house price equations with over 40,000 single–family transactions for Dallas, Texas.     

Did Affordable Housing Legislation Contribute to the Subprime Securities Boom?

We use a regression discontinuity approach and present new institutional evidence to investigate whether affordable housing policies influenced the market for securitized subprime mortgages. We use merged loan‐level data on nonprime mortgages with individual‐ and neighborhood‐level data for California and Florida. We find no evidence that lenders increased subprime originations or altered loan pricing around the discrete eligibility cutoffs for the Government‐Sponsored Enterprises' (GSEs) affordable housing goals or the Community Reinvestment Act. Although we find evidence that the GSEs bought significant quantities of subprime securities, our results indicate that these purchases were not directly related to affordable housing mandates.     

Time-varying connectedness of metropolitan housing markets

We construct a time-varying measure of connectedness for 382 U.S. metropolitan housing markets using monthly house price data from 1975 to the present. Housing connectedness in the long run is found to be much stronger than the instantaneous connectedness, both of which exhibit notable variation over time and across metropolitan areas. Unlike stock market connectedness, housing market connectedness leads the business cycle; it helps predict the likelihood of future recessions.     

Why Are Foreclosures Contagious?

This article investigates the mechanism by which foreclosed properties depress neighboring property prices. Using a novel dataset on housing capital expenditure, I verify as accurate the claim of disinvestment theory made in earlier studies. When capital expenditure investment, neighborhood price trends, number of Multiple Listing Service listings and neighborhood fixed effects are controlled for, the negative effect on property prices is significant from nearby foreclosures, real estate owned (REO) listings and REO sales, but not from default and delinquent properties. The effect is larger in a depressed market than in an appreciating market. I argue that the most plausible explanation for these results is that a foreclosure discount drives down the reference prices for nearby properties and depresses neighborhood values. This discount information is revealed to the public through foreclosures, REO listings and REO sales.     

Economic Effects of Racial Integration: An Analysis of Hedonic Housing Prices and the Willingness to Pay

This study evaluates household economic effects stemming from neighborhood racial integration in Oakland, California. To that end, housing market data are applied to estimate hedonic price and willingness-to-pay functions for neighborhood racial composition. Results of the analysis indicate the problematic nature of the constant willingness-to-pay assumption and suggest this standard method may underestimate the household economic effects of racial integration. The paper concludes with implications for neighborhood integration policy.     

Submarket Dynamics of Time to Sale

We argue that the rush to apply multiple regression estimation to time on the market (TOM) durations may have led to important details and idiosyncrasies in local housing market dynamics being overlooked. What is needed is a more careful examination of the fundamental properties of time to sale data. The approach promoted and presented here, therefore, is to provide an examination of housing sale dynamics using a step-by-step approach. We present three hypotheses about TOM: (i) there is nonmonotonic duration dependence in the hazard of sale, (ii) the hazard curve will vary both over time and across intra-urban areas providing evidence of the existence of submarkets and (iii) institutional idiosyncrasies can have a profound effect on the shape and position of the hazard curve. We apply life tables, kernel-smoothed hazard functions and likelihood ratio tests for homogeneity to a large Scottish data set to investigate these hypotheses. Our findings have important implications for TOM analysis.     

Central City Revitalization: A Predictive Model

The object of this paper is to increase the understanding of the gentrification process by developing a set of representative indices that could be used to assess the likelihood of gentrification occurring in a central city neighborhood. Using Boston, Massachusetts as a representative city, economic, housing, social and amenity variables were collected from the 1970 U.S. Census. A sample of blocks that did and did not revitalize after 1970 was chosen. As the gentrification outcome was known with certainty, a logistic regression model was estimated. The estimated model quite accurately classified the neighborhoods into their respective grouping, resulting in a block-level statistical model of housing revitalization.     

Black and White Preferences for Neighborhood Racial Composition

The research investigates the existence, nature and magnitude of the preferences of races to voluntarily "self-segregate" into particular areas of urban housing markets. Housing market theory is employed to develop a model showing how housing price variations within a group can provide unambiguous evidence of their preferences for neighborhood racial composition. The model is operationalized in a multiple regression specification wherein the variations in a given racial group's housing prices become a function of the dwelling's attributes and the attributes of the neighborhood (including quality, status, stability and density) as well as housing submarket location and racial composition. The size and statistical significance of the coefficient of the last attribute provides the evidence sought.
The regressions are estimated using two micro-household data bases from St. Louis (1967) and Wooster, Ohio (1975), and results compared. Results show that St. Louis black owners had an aversion to larger black proportions within black submarket neighborhoods, with .7% lower housing prices associated with a 1% higher percentage black. Racial effects for black owners in preponderantly white areas and for black renters in all areas were statistically insignificant. St. Louis whites of both tenures did not demonstrate aversion to neighborhoods with higher percentages of blacks as long as they remained 25% black or less. In areas 25–50% black, however, white prices were 1.5% lower for owners and 3.2% lower for renters per 1% higher proportion black. Such associations continued in majority-black areas, although the magnitudes of the price effect became progressively smaller. Wooster whites showed an aversion to living in neighborhoods having even a few percent of blacks, with prices 11% lower for owners and 7% lower for renters in such areas compared to all-white ones.     

Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach

This article carries out an asset-pricing analysis of the U.S. metropolitan housing market. We use ZIP code–level housing data to study the cross-sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk–return analysis is cross-sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset-pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. Our results on the return-volatility-price relation are robust to (i) metropolitan statistical area clustering effects and (ii) differences in socioeconomic characteristics among submarkets related to income, employment rate, managerial employment, owner-occupied housing, gross rent and population density.     

House Search Duration in Hot and Cold Residential Markets

This study analyzes the determinants of house search duration of consumption‐driven buyers and individual investors in different housing market environments. We use data from surveys of recent house‐buyers in “hot” and “cold” housing markets in the 2000s housing bubble in California characterized by rising and declining residential house prices, respectively. The average house price and the surveyed geographical area are the same for both periods. Expected house ownership horizon is shown to be an important determinant of the realized search duration in addition to commonly considered housing and buyer characteristics. We find a statistically significant positive effect of it on the time until purchase in both housing price environments for consumption‐driven buyers. We also find that consumption‐driven house purchases were highly pronounced in coastal areas in the hot market and inland areas in the cold market. In contrast, long‐horizon investment activity leads that of consumption activity in those areas. Short‐horizon investors, on the other hand, concentrated their house search activity in inland areas in both housing market environments.     

Modeling Spatial Variation in Housing Prices: A Variable Interaction Approach

The absolute location of each real estate parcel in an urban housing market has a unique location-value signature. Accessibility indices, distant gradients and locational dummies cannot fully account for the influence of absolute location on the market price of housing because there are an indeterminable number of externalities (local and nonlocal) influencing a given property at a given location. Furthermore, the degree to which externalities affect real estate values is not only unique at each location but highly variable over space. Hence, absolute location must be viewed as interactive with other determinants of housing value. We present an interactive variables approach and test its ability to explain price variations in an urban residential housing market. The statistical evidence suggests that the value of location, as embodied in the selling price of housing units, may not be separable from other determinants of value. It is recommended that housing valuation models, therefore, be specified to allow site, structural and other independent attributes to interact with absolute location—{ x , y } coordinates—when accounting for intraurban variation in the market price of residential housing. This approach is especially useful when estimating the value of housing for geographic areas where very little is known a priori about the neighborhoods or submarkets.     

The Impact of Housing Vouchers on Mobility and Neighborhood Attributes

This article examines the effect of receiving a housing voucher on the mobility and neighborhood attributes of low‐income households. Housing policy has shifted toward vouchers in lieu of public housing projects to allow households to move away from high‐poverty areas. We use administrative records collected from an experiment to examine this issue. We find that households moved immediately after receiving the subsidy but did not relocate to lower poverty neighborhoods until several quarters later. Our findings suggest that recipients initially lease in nearby units to secure the subsidy, while continuing to search for housing in lower poverty neighborhoods.     

Urban Housing Markets Modelling: Short-Run Equilibrium Implications

This paper tests for the existence of short-run equilibrium in the urban housing market in Metropolitan Toronto. The alternative hypothesis is the housing market segmented with respect to locational and structural attributes. We found insignificant differences in attribute prices across hypothesized submarkets. This implies that an unstratified hedonic price regressions model, based on the assumption of short-run equilibrium, is equally efficient in the analysis of housing prices as a model based on a number of subsamples stratified along lines of segmentation.     

Evidence of the Dual Nature of Property Value Recovery Following Environmental Remediation

The literature on home value diminution attributable to environmental degradation and its possible reversal typically ignores indirect effects upon neighborhood characteristics that can exacerbate the overall change in property values, resulting in underestimates of diminution and overestimates of recovery. Furthermore, to the extent that direct price effects and neighborhood transition effects respond differently to remediation efforts, the relatively new postremediation literature misses an important part of the recovery process. This study examines both direct and indirect effects and finds in the case of Houston Environmental Protection Agency Superfund sites that, while the direct value impacts of proximity to toxic waste sites was significantly reduced after remediation, the indirect effects associated with induced demographic changes were much slower to reverse, producing a housing market inertia that stifled full home value recovery.     

Why Do Sellers Hold Out in the Housing Market? An Option‐Based Explanation

In the residential housing market, home owners are reluctant to sell in a declining market. We build a model which focuses on the embedded call option associated with home ownership that allows owners to delay the (irreversible) sale. When prices are low, the (opportunity) cost of a sale, i.e., a higher implied gain from a future sale, likely exceeds its immediate trade benefit and an owner is better off waiting for market conditions to improve. The model also highlights the importance of supply conditions: a more constrained supply is associated with a longer delay. Using state‐level residential housing data, we find evidence consistent with the model. Transaction volume is increasing (decreasing) in the rental growth rate (volatility) in the cross section; their effects are amplified in areas with low supply elasticities, and in times with low market prices. Overall, this paper provides a rational explanation for delayed trading decisions in the housing market.     

Externalities of residential property flipping

This study investigates whether flipping activities impose an externality on the transaction prices of the neighboring nonflipped properties. Using a data set of residential property transactions in Clark County, Nevada for the period 2003–2013, we find that flippers impose a significant positive impact on the price of neighboring nonflipped properties in an up market, but a significant negative effect in a down market. This procyclical impact of flipping activity contributes to the volatility of housing prices, hence magnifying boom and bust cycles and increasing the likelihood of a mortgage crisis.     

Lender Forbearance: Evidence from Mortgage Delinquency Patterns

The length of time that residential mortgages remain in delinquency prior to foreclosure is examined using an Accelerated Failure Time (AFT) model and a database of 207 foreclosed conventional and Veteran's Administration (VA) mortgages. The results suggest that the primary factors influencing the timing of the lender's foreclosure decision are the borrower's equity position and the erosion of that position with continuing delinquency. Borrower bankruptcy and VA guarantees also lengthen the delinquency period. Delinquency periods for fixed rate mortgages (FRM) decrease when the market interest rate increases.     

The price effects of greening vacant lots: How neighborhood attributes matter

We identify the effects of greening vacant lots on nearby housing prices and show how neighborhood attributes matter to these outcomes. Using data from a longstanding program in Philadelphia, we find that prices for houses within 1,000 feet of a greened vacant lot rise by about 4%, consistent with the literature, with the effect size increasing over time. Using the extensive data available in Philadelphia, we show how these effects vary by the attributes of the neighborhood in which they occur, with larger effects in areas with a high share of vacant land and higher-than-average median household incomes, with peak responses estimated at 19% and 15%, respectively. We demonstrate the importance of sample selection bias adjustment for identification of the effect of vacant lot greening.     

Internet Search Behavior,Liquidity and Prices in the Housing Market

We employ detailed internet search data to examine price and liquidity dynamics of the Dutch housing market. We show that the number of clicks on properties listed online proxies demand and the number of listed properties proxies supply. From this internet search behavior, we create a market tightness indicator and we find that this indicator Granger causes changes in both house prices and housing market liquidity. The results of a panel VAR suggest that a demand shock results in a temporary increase in liquidity and a permanent increase in prices in urban areas. This is in accordance with search and matching models.