Assessing the Market Value of Real Estate Property with a Geographically Weighted Stochastic Frontier Model

In this study we consider the problem of sellers, buyers and real estate appraisers in determining the price for a house, taking into account the characteristics of the house and its location as well as the goals of these three different parties. The appraiser's job is to determine the fair market value of the house, while the buyer and seller want to find, respectively, the lowest and highest feasible price for it. We combine recent developments in geography and econometrics to develop an approach that determines local estimates of property values from the perspectives of the buyer, seller and appraiser, taking into account the characteristics of the house as well as its location. We illustrate our approach analyzing closing prices in one residential real estate market.     

The Suburban Housing Market: Effects of City and Suburban Employment Growth

Using a data set of over 88,000 housing sales, we find that city employment growth has a significant positive effect on suburban house values; this effect is largest for housing closest to the central business district and declines with increasing distance from it. City employment growth has a negative effect on the rate of suburban house construction; the magnitude of the effect increases with distance. Suburban employment growth has little aggregate effect on house prices, and there is less variation by distance. Suburban growth has a significant effect on construction rates, especially at locations near the urban fringe.     

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.     

Discount Brokerage in Residential Real Estate Markets

Transaction costs are thought to affect asset prices and market liquidity, but the direction and magnitude of these effects continue to be the subject of debate. In the single‐family residential market, discount brokers offer to list a house for a lower price and thus reduce the transaction costs associated with obtaining a match. In this article we obtain empirical estimates of the price and liquidity impact of a seller selecting a discount broker to market a single‐family residential property. The unique data set allows for the identification of residential properties that were listed by a discount brokerage firm. The empirical results confirm the predictions of our theoretical model. Using a sample of 318,221 listings and 243,625 sales, we find that houses listed by discount brokers sell at prices similar to non‐discount brokerage listings, but are less likely to sell, and when they do sell, take approximately three days longer to sell. The results indicate that lower transaction costs do not impact housing prices in this market, but that they are related to asset liquidity.     

Oil Prices and Urban Housing Demand

We develop a model of a monocentric, oil‐exporting city. The model predicts a “twist” (rotation combined with a level shift) of the house price gradient with an oil price change due to the combined producer price and transportation cost effects. Empirical findings support the predictions, with house price changes positively linked to the price of oil in cities specialized in oil and gas‐related industries, and negatively linked in suburban areas of all cities. These results quantify the large and differential risks to house prices associated with oil price changes both within and across cities. Overall, estimates suggest a 50% change in the price of oil results in a city‐wide house price change of 15% over five years in a city specialized in the production of oil (export employment share of 50%), whereas house prices for units greater than 15 miles from the city‐center change in relative terms by ?1.5% over the same period.     

Estimating Loan‐to‐Value Distributions

We estimate a model of house prices, combined loan‐to‐value ratios (CLTVs) and trade and foreclosure behavior. House prices are only observed for traded properties and trades are endogenous, creating sample‐selection problems for existing approaches to estimating CLTVs. We use a Bayesian filtering procedure to recover the price path for individual properties and produce selection‐corrected estimates of historical CLTV distributions. Estimating our model with transactions of residential properties in Alameda, California, we find that 35% of single‐family homes are underwater, compared to 19% estimated by existing approaches. Our results reduce the index revision problem and have applications for pricing mortgage‐backed securities.     

Effects of innovation on employment: A dynamic panel analysis

This paper estimates the effect of innovation on employment at the firm level. Our uniquely long innovation panel data set of German manufacturing firms covers more than 20 years and allows us to use various innovation measures. We can distinguish between product and process innovations as well as between innovation input and innovation output measures. Using dynamic panel GMM system estimation we find positive effects of innovation on employment. This is true for innovation input as well as for innovation output variables. Innovations show their positive effect on employment with a time lag and process innovations have higher effects than product innovations.     

Predicting Spatial Patterns of House Prices Using LPR and Bayesian Smoothing

This article is motivated by the limited ability of standard hedonic price equations to deal with spatial variation in house prices. Spatial patterns of house prices can be viewed as the sum of many causal factors: Access to the central business district is associated with a house price gradient; access to decentralized employment subcenters causes more localized changes in house prices; in addition, neighborhood amenities (and disamenities) can cause house prices to change rapidly over relatively short distances. Spatial prediction (e.g., for an automated valuation system) requires models that can deal with all of these sources of spatial variation. We propose to accommodate these factors using a standard hedonic framework but incoporating a semiparametric model with structure in the residuals modeled with a partially Bayesian approach. The Bayesian framework enables us to provide complete inference in the form of a posterior distribution for each model parameter. Our model allows prediction at sampled or unsampled locations as well as prediction interval estimates. The nonparametric part of our model allows sufficient flexibility to find substantial spatial variation in house values. The parameters of the kriging model provide further insights into spatial patterns. Out–of–sample mean squared error and related statistics validate the proposed methods and justify their use for spatial prediction of house values.     

National Vacancy Rates and the Persistence of Shocks in U.S. Office Markets

In this paper, we develop and estimate a model that decomposes the variance in office vacancy rates into market-specific, time-specific, and random components. The results indicate significant differences in natural vacancy rates across markets. We also find some persistence in deviations from these natural vacancy rates. The analysis is applied to both central business district (CBD) and suburban office markets. We find that natural vacancy rates differ across CBD markets and across suburban markets. Further, the persistence of disequilibrium in one CBD market seems to differ significantly from that in another. This is not shown to be true for suburban markets.     

限价房的品质定位研究

限价房是政府主导的限定目标客户的特定住宅，是我国现阶段城市住宅建设的标尺，它的产品品质定位应充分体现节约环保概念，从而引导社会大众科学和适度的消费住房。根据小康社会和节约型社会建设理念，沿着住宅产品生产的关键路线，提出关于限价房的建设标准、建筑设计关键点、配套标准、节能环保技术的选用和工程质量管理的主要环节等一些见解，以期有益于限价房的规划设计和工程质量的保证，进而推动限价房及住宅建设的科学发展。     

Extension and Application of the Mills-Muth Urban Residential Land Use Simulation Model: Milwaukee, 1977–2020

The Mills-Muth urban residential land use simulation model is extended to include two residential income classes and a proportion of residential to urban land that varies with distance from the CBD. Land area, population, households, population density and residential property value are simulated for the central city, its suburbs and the Milwaukee urban area for the years 1977, 1980, 1985, 1990 and 2020, for two scenarios that differ primarily with respect to income growth rates and automobile commuting costs. The main finding is the powerful positive effect of even relatively small real income growth on suburbanization.     

基于ESDA方法与空间计量模型的房价溢出效应分析

一个地区房价的波动可以通过时间滞后传递到其他地区，从而产生房价溢出效应。本文以我国31个省际区域2005～2014年的数据为样本，运用探索性空间数据分析（ESDA）对31个省的房价空间分布格局及演变态势进行分析。然后运用空间计量模型分析我国省际房价变动的影响因素，并从地理因素和经济因素两个方面研究房价溢出效应。研究结果表明：中国31个省域间的房价存在明显的空间相关性；地区的城市化率、城镇就业人员平均货币工资、二、三产业产值占GDP比重对房价有显著的影响，房价存在显著的空间溢出效应，经济距离对地区房价影响比地理距离的影响更显著。     

Property Taxes and Residential Rents

Property taxes are a fundamental source of revenue for local governments, constituting 73% of local government tax revenue in the United States. In this article, we empirically investigate the impact of residential property taxes on residential rents. Using data from the American Housing Survey and the National League of Cities, we estimate numerous specifications of a hedonic rent equation with comprehensive unit-level, neighborhood-level and city-level controls. We find that a one standard deviation increase in the property tax rate raises residential rents by roughly $400 annually.     

Information Externalities,Neighborhood Characteristics and Home Mortgage Pricing and Underwriting

Theories of rational redlining suggest thinness in housing markets should lead to greater uncertainty in house price appraisals, increasing mortgage denial rates or pricing. Empirical tests found support for this theory in mortgage underwriting using 1990s data. Using 2006 data and bank‐specific regression models, we revisit this topic in light of two developments leading to the recent mortgage bubble: the widespread securitization that allowed banks to shift loan risk to investors and the advent of risk‐based pricing. Consistent with expectations, we find that information externalities have become economically very small and have shifted from underwriting to pricing decisions.     

Are Investors the Bad Guys? Tenure and Neighborhood Stability in Chelsea,Massachusetts

In this article, we examine the role of investors and occupant‐owners in an urban context during the recent housing crisis. We focus on Chelsea, Massachusetts, because it is a dense city, dominated by multifamily housing structures with high rates of foreclosure for which we have particularly good data. We distinguish between occupant‐owners and investors using local data, and we find that many investors are misclassified as occupant‐owners in the Home Mortgage Disclosure Act data. Then, employing a competing risks framework to study ownerships during the period 1998 through mid‐2010, we find that local investors, who tend to invest more in relation to purchase prices and sell more quickly, experienced approximately 1.8 times the mortgage foreclosure risk of occupant‐owners, conditional on financing. Nonlocal investors have no statistically significant difference in foreclosure risk from occupant‐owners. Nonetheless, those owners with subprime purchase mortgages (most of whom are occupant‐owners) faced the highest foreclosure risk when house prices fell.     

住宅小区选址评价指标体系和模型分析

文章首先从影响住宅小区选址评价的因素--社会政治因素、经济因素和环境因素入手,建立了住宅小区选址评价指标体系,分析了指标体系中的各项指标。运用数学方法构建了住宅小区选址决策模型,阐明了如何用层次分析法确定各指标的权重,以及如何运用定性与定量相结合的分析方法确定评价指标的数值。     

Amenity‐Based Housing Affordability Indexes

The recent slump notwithstanding, substantial increases in house prices in many parts of the United States have served to highlight housing affordability for moderate‐income households, especially in high‐cost, supply‐constrained coastal cities such as Boston. In this article, we develop a new measure of area affordability that characterizes the supply of housing that is affordable to different households in different locations of a metropolitan region. Key to our approach is the explicit recognition that the price/rent of a dwelling is affected by its location. Hence, we develop an affordability methodology that accounts for job accessibility, school quality and safety. This allows us to produce a menu of town‐level indexes of adjusted housing affordability. The adjustments are based on obtaining implicit prices of these amenities from a hedonic price equation. We thus use data from a wide variety of sources to rank 141 towns in the greater Boston metropolitan area based on their adjusted affordability. Taking households earning 80% of area median income as an example, we find that consideration of town‐level amenities leads to major changes relative to a typical assessment of affordability.     

Who Is at Risk of Losing and Gaining Health Insurance?

In this study, we examine annual transitions into and out of health insurance coverage using matched data from the 1996 to 2004 Current Population Survey (CPS). We find evidence of several characteristics that are strongly associated with the likelihood of losing or gaining health insurance including race, education, unemployment, part‐time employment status, employment size, and self‐employment.     

Financing Residential Development with Special Districts

This paper empirically examines the extent to which the property tax liability created by financing residential infrastructure using special district bonds is capitalized in house prices. We compare house prices for single‐family detached homes built within development districts to similar properties located outside development districts. Our hedonic specification includes the usual housing characteristics and controls for the influence of spatial attributes using Census Block Group “neighborhood” fixed effects. The preferred empirical specification restricts the data to neighborhoods that have numerous sales of recently constructed single‐family detached homes located both within and outside development districts. The empirical results indicate that house prices for homes located within development districts are lower than house prices for similar homes located outside of development districts, but the amount of property tax capitalization is significantly less than full. Results depend on our Generalized Methods of Moments estimator, which instruments property tax rates using the characteristics of development districts. We identify valid instruments by restricting transactions to properties located in rapidly growing suburban developments.     

Self‐Reported vs. Market Estimated House Values: Are Homeowners Misinformed or Are They Purposely Misreporting?

Extant research finds significant gaps between a homeowner's self‐reported house value and market estimates, and that the gap is largest for underwater homeowners. Prior studies, however, have largely overlooked the possibility that homeowners’ self‐reported house value may be more accurate due to private information. Previous research has also neglected the possibility that there could be discordance between what homeowners know and what they report as their house value. Using the Panel Study of Income Dynamics, this study examines how the choices of households reveal their knowledge of the true home value. In so doing, we find that that post move housing choices reveal that market estimates are accurate assessments of the housing value. Further, we find evidence that these underwater homeowners are aware of the actual house value, but are reporting them incorrectly. The results show that misreporting underwater homeowners are as likely to be late on their mortgage payments as homeowners that are reporting negative equity. Underwater homeowners’ reluctance to admit their losses accords with the theory of loss aversion.