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In this study, we develop and apply a new methodology for obtaining accurate and equitable property value assessments. This methodology adds a time dimension to the Geographically Weighted Regressions (GWR) framework, which we call Time-Geographically Weighted Regressions (TGWR). That is, when generating assessed values, we consider sales that are close in time and space to the designated unit. We think this is an important improvement of GWR since this increases the number of comparable sales that can be used to generate assessed values. Furthermore, it is likely that units that sold at an earlier time but are spatially near the designated unit are likely to be closer in value than units that are sold at a similar time but farther away geographically. This is because location is such an important determinant of house value. We apply this new methodology to sales data for residential properties in 50 municipalities in Connecticut for 1994–2013 and 145 municipalities in Massachusetts for 1987–2012. This allows us to compare results over a long time period and across municipalities in two states. We find that TGWR performs better than OLS with fixed effects and leads to less regressive assessed values than OLS. In many cases, TGWR performs better than GWR that ignores the time dimension. In at least one specification, several suburban and rural towns meet the IAAO Coefficient of Dispersion cutoffs for acceptable accuracy. [ABSTRACT FROM AUTHOR]

Railway stations function as nodes in transport networks and places in an urban environment. They have accessibility and environmental impacts, which contribute to property value. The literature on the effects of railway stations on property value is mixed in its finding in respect to the impact magnitude and direction, ranging from a negative to an insignificant or a positive impact. This paper attempts to explain the variation in the findings by meta-analytical procedures. Generally the variations are attributed to the nature of data, particular spatial characteristics, temporal effects and methodology. Railway station proximity is addressed from two spatial considerations: a local station effect measuring the effect for properties with in 1/4 mile range and a global station effect measuring the effect of coming 250 m closer to the station. We find that the effect of railway stations on commercial property value mainly takes place at short distances. Commercial properties within 1/4 mile rang are 12.2% more expensive than residential properties. Where the price gap between the railway station zone and the rest is about 4.2% for the average residence, it is about 16.4% for the average commercial property. At longer distances the effect on residential property values dominate. We find that for every 250 m a residence is located closer to a station its price is 2.3% higher than commercial properties. Commuter railway stations have a consistently higher positive impact on the property value compared to light and heavy railway/Metro stations. The inclusion of other accessibility variables (such as highways) in the models reduces the level of reported railway station impact. [ABSTRACT FROM AUTHOR]

This paper evaluates how consumers value differences in neighborhood composition and street layout, factors not previously included in empirical studies of house value. Highly connected street patterns are important to New Urbanism. We use measures of neighborhood street connectivity and their interaction with other neighborhood attributes to evaluate how street layout affects property values. We employ two different methods of indexing street layout. Both methods show layout has a significant impact on price, but conclusions are sensitive to the method used. In pedestrian oriented neighborhoods, a more gridiron-like street pattern increases house value using one measure, but greater connectivity decreases house value using the other. In auto-oriented developments, a more gridiron-like street pattern reduces house value using either measure. [ABSTRACT FROM AUTHOR]

Accurate and efficient valuation of property is of utmost importance in a variety of settings, such as when securing mortgage finance to purchase a property, or where residential property taxes are set as a percentage of a property's resale value. Internationally, resale based property taxes are most common due to ease of implementation and the difficulty of establishing site values. In an Irish context, property valuations are currently based on comparison to recently sold neighbouring properties, however, this approach is limited by low property turnover. National property taxes based on property value, as opposed to site value, also act as a disincentive to improvement works due to the ensuing increased tax burden. In this article we develop a spatial hedonic regression model to separate the spatial and non-spatial contributions of property features to resale value. We mitigate the issue of low property turnover through geographic correlation, borrowing information across multiple property types and finishes. We investigate the impact of address mislabelling on predictive performance, where vendors erroneously supply a more affluent postcode, and evaluate the contribution of improvement works to increased values. Our flexible geo-spatial model outperforms all competitors across a number of different evaluation metrics, including the accuracy of both price prediction and associated uncertainty intervals. While our models are applied in an Irish context, the ability to accurately value properties in markets with low property turnover and to quantify the value contributions of specific property features has widespread application. The ability to separate spatial and non-spatial contributions to a property's value also provides an avenue to site-value based property taxes. [ABSTRACT FROM AUTHOR]

Since real estate is heterogeneous and not all its quality attributes are observable, the repeat sales model pioneered by Bailey et al. (1963) has become one of the standard methods to estimate a constant-quality price index. The model, however, fails to adjust for depreciation, as age and time between sales have an exact linear relationship. This paper proposes a new method to estimate an age-adjusted repeat sales index by decomposing property value into land and structure components. As depreciation is more relevant to the structure than land, the property’s depreciation rate should depend on the relative size of land and structure. The larger the land component, the lower the depreciation rate of the property. This new method is applied to property transactions in Hong Kong and Tokyo. Hong Kong is shown to have a higher depreciation rate based on a fixed structure-to-property value ratio, while the resulting age adjustment is larger in Tokyo because its land value has shrunken over time. [ABSTRACT FROM AUTHOR]

We study the impact of the risk retention rule - requiring 5% of underlying credit risk for commercial mortgage backed securities - on commercial real estate markets. Since the primary objective of this rule is for the deal sponsors to have skin in the game, we expect that underwriting standards should tighten following the implementation of the rule. Consistent with this notion, we find the reform led to a decrease in price premium and probability of rating shopping by the sponsors, as well as longer time-to-securitization and lower default probability. We also show that the Dodd-Frank risk retention rule can impact banks' credit supply by curtailing credit growth. As a result, we provide novel evidence on the effect of the risk retention rule on underwriters most exposed to the regulation. [ABSTRACT FROM AUTHOR]

Separating urban land and structure values is important for national accounts and for analysis of real estate risk over time. A large part of the literature on urban land valuation uses the land residual method, which relies on the assumption that structures are easily replaced. But urban land value depends on accessibility to nearby land uses, implying that infrastructure and the slowly changing built environment are the most important components of land value. Investments in structures are only slowly reversible, implying that land and structure function as a bundled good whereas land residual theory severs the connection between land value and structure value over time. We develop a simple theoretical model that includes option value and compare to a nested land residual model before and after a shock to values. Cross-sectionally our model shows that land residual theory overestimates structure value. Over time almost all of any change in property value is allocated to land residuals. Data from Maricopa county, AZ, 2012–2018 strongly support option value models when nested within a general model that also includes land residuals. FHFA estimates use entirely different cost estimation methods: our analysis of FHA data suggest that our conclusions generalize to the U.S. as a whole, and that high and rising land value ratios over 50 years (the "hockey stick" pattern found in the literature) are likely an artifact of the residual model. [ABSTRACT FROM AUTHOR]

Estimating the value of multifamily properties and other commercial real estate properties is an important but difficult task for real estate investors and researchers. The commonly used capitalization rate model, which involves the estimation of capitalization rates, has limitations in practice, especially during periods of financial stress. This paper proposes a new property valuation methodology that directly estimates the value of multifamily properties by accounting for both market trends and property operating performance. Our results show that this new model significantly improves the valuation of multifamily properties, particularly distressed properties. This methodology can also be applied to the valuation of other commercial real estate properties. [ABSTRACT FROM AUTHOR]

Automated valuation models (AVMs) are widely used by financial institutions to estimate the property value for a residential mortgage. The distribution of pricing errors obtained from AVMs generally show fat tails (Pender 2016; Demiroglu and James Management Science, 64(4), 1747–1760 2018). The extreme events on the tails are usually known as "black swans" (Taleb 2010) in finance and their existence complicates financial risk management, assessment, and regulation. We show via theory, Monte Carlo experiments, and an empirical example that a direct relation exists between non-normality of the pricing errors and goodness-of-fit of the house pricing models. Specifically, we provide an empirical example using US housing prices where we demonstrate an almost perfect linear relation between the estimated degrees-of-freedom for a Student's t distribution and the goodness-of-fit of sophisticated evaluation models with spatial and spatialtemporal dependence. [ABSTRACT FROM AUTHOR]

This paper proposes a generalized repeat sales regression (GRSR) that uses repeat sales from the entire market, in which properties may have heterogeneous value appreciation processes, to estimate price indices for not only the entire market, but also submarkets or customized portfolios of properties that only have small numbers of value observations. Monte Carlo simulations provide strong evidence that the GRSR indices more accurately measure the index for the entire market as well as individual property value appreciation than conventional RSR indices. This paper also proposes a Chi-square test to detect the heterogeneity in property value appreciation across submarkets/portfolios, and use simulations to show that the test is powerful in small samples. This paper finally illustrates the application of the GRSR using a historical dataset of the Chicago housing market from 1970 to 1986. [ABSTRACT FROM AUTHOR]

Accurate and unbiased property value estimates are essential to credit risk management. Along with loan amount, they determine a mortgage's loan-to-value ratio, which captures the degree of homeowner equity and is a key determinant of borrower credit risk. For home purchases, lenders generally require an independent appraisal, which, in addition to a home's sales price, is used to calculate a value for the underlying collateral. A number of empirical studies have shown that property appraisals tend to be biased upwards, and over 90 percent of the time, either confirm or exceed the associated contract price. Our data suggest that appraisal bias is particularly pervasive in rural areas where over 25 percent of rural properties are appraised at more than five percent above contract price. Given this significant upward bias, we examine a host of alternate valuation techniques to more accurately estimate rural property values. [ABSTRACT FROM AUTHOR]

Using a hedonic pricing model, this paper investigates the responsiveness of residential property values in a well-defined inner-city neighborhood of Kenosha, Wisconsin, to the presence of two small former industrial sites contaminated by various environmental pollutants, or brownfields, and a local neighborhood park, or greenspace. Using readily available data on sales and assessments for residential property in close proximity to the brownfields and the greenspace, we estimate well-behaved and statistically significant property value gradients with respect to the park, the environmental amenity, and the brownfields, the environmental disamenities. These functions are then used to estimate the possible impact that brownfield remediation may have on total property value. We estimate that remediation and redevelopment of the brownfields into greenspaces would increase property values for the 890 neighborhood residences between $2.40 and $7.01 million. These results suggest that small brownfields have a measurable impact on property values and that readily accessible data can be used to help local policymakers make decisions on remediation issues. [ABSTRACT FROM AUTHOR]

Infill investments are argued to mitigate environmental footprints, regenerate places and accommodating population growth, but frequently generate local opposition. However, there is a dearth of knowledge around how different types of infill affect different segments of local property markets, how persistent effects are and how far they reach. Using detailed geocoded infill development activity and sales data, we test the price level and trajectory impacts of five infill types, distinguished by the net scale of additional dwellings, on property prices within five concentric 100-meter rings. Using an adjusted interrupted time-series estimation strategy with locality, property and neighborhood characteristic controls we find that developments that generate a net increase in dwellings of four or less, typically result in an appreciation in the average sales prices of proximate dwellings. Moderate and large-scale developments generate negative price effects, but these effects predominantly affect apartments and townhouses, not the dominant detached house submarket. Over time, amenity effects and local market potential may even have a further positive expectation effect on detached house prices. Infill type differentiation shows that urban densification may result in positive affordability outcome in the apartment submarket, but has the opposite effects in the detached house submarket. Divergent price trajectories also contribute to widening wealth disparities. [ABSTRACT FROM AUTHOR]

This paper examines the principle-agency problem between landlords and real estate agents using novel data on rental contracts. Real estate agents are found to obtain higher contract rents by approximately 1% more for themselves (and family members) than for other landlords, which is economically small. The results suggest that the principle-agency program with real estate agents is less of a concern in the rental market than the ownership market. The reason potentially relates to the commission structure, the relatively low effort associated with finding a tenant, the landlord's ability to evaluate an agent's performance, and reputation concerns from repeated interactions. [ABSTRACT FROM AUTHOR]

This paper proposes an intensity-based pricing model with default dependence structure for CMBS bonds. Three features are incorporated into the proposed model. First, default is a Poisson jump process defined by a function of mortgage rating information. Second, property risks are modeled using a high dimensional Brownian motion process that captures both systematic risk and idiosyncratic risk in property value. Third, default dependence structure is built into the extended model. Based on a set of input parameters, we simulate various pricing effects on a hypothetical CMBS using the proposed model structure. The results of the base-line intensity model show that yield spreads on CMBS bonds increase in the recovery rate, but decreases in the hazard rate. Security structured with smaller subordination tranche exposes CMBS bonds to higher default risks. The model predicts that default clustering increases required yield spreads of CMBS bonds. At a 70% recovery rate and a 3% default hazard rate, yield spreads of Junior bonds are expected to increase by 169 basis points when counterparty risks increase by 50%. The results highlight the importance of clustering risks associated with counterparty default when valuing CMBS bonds. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between property pricing precision (deviation from an expected property value) and specialization in the listing process by agents. It is hypothesized that financially constrained, risk-averse sellers prefer finer gradations of pricing precision, i.e., less deviation from expected property value, and that a set of agents will rise to meet this preference. The findings in this work indicate that agents specializing in listing properties increase pricing precision. The contributions of this work are twofold: (a) it provides a unique and heretofore uninvestigated metric as its dependent variable, thus allowing for further investigation into the brokerage intermediation process beyond the scope of price and marketing time, and (b) it provides an identifiable agent trait that can allow for a better matching of sellers’ preferences with agents’ abilities. [ABSTRACT FROM AUTHOR]

The article presents information on factors influencing interest rates on delinquent property tax certificates. The ad valorem real property tax revenue system is a familiar feature in most areas of the United States because it is relatively easy to administer and extremely difficult to evade. Public records identify all parcels and their respective owners, making assessment and billing a manageable task. Additionally, property owners who fail to pay their taxes face the possibility that the property itself may ultimately be used to satisfy the tax obligation. This study examines the market for delinquent property tax certificates, a commonly used enforcement mechanism in property tax systems around the United States. The value of such certificates using a continuous-time framework and propose a statistical model that allows testing for factors that affect interest rates charged by investors who purchase the certificates as investment instruments. Using sample data from tax certificate sales in Florida from 1982 to 2000, the authors found that interest rates on certificates are negatively and significantly related to assessed property value and homestead status, and positively related to local ownership. They found an inverse relationship between interest rates and the number of certificates purchased by the certificate investor, indicating a significant clientele effect in this market. They also find that the implied effective tax rate is positively related to the interest rates charged by investors. Overall, the findings provide insight into the function of this unique market niche.

This paper uses option pricing to examine how the presence of hazardous materials affects real estate value. The party owner has two options. The first option is to remove the hazardous materials at the best time. The second option, embedded in the first one, is to redevelop the property at the best opportunity. The owner has three possible timing strategies with respect to the exercise of these two options: remove the hazardous materials first and retain the option to redevelop the property later, remove and redevelop at the same time, or do nothing. Conditions under which the presence of the hazardous materials may either expedite or postpone the decision to redevelop art also derived. If the regulatory environment does not allow the property owner to make optimal timing decisions with respect to the exercise of these options, then our results provide an indication of the cost of regulation as measured by the additional loss in property value. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to shed light on the history of commercial property values over the past decade, and to compare different methods of constructing commercial property value indices and returns series. We examine three types of indices: (i) Indices that attempt to reconstruct property market values by "unsmoothing" the appraisal-based Russell-NCREIF Index; (ii) Indices that trace average ex post transaction prices of commercial property over time; and (iii) an index based on unlevering REIT share prices. By comparing the different historical pictures that result from the various index construction methodologies, one gains insight into the nature of commercial property price and valuation behavior. The REIT-based values lead the other indices in time but display greater short-run volatility. The transactions-based indices lag behind the other series in time, and are consistent with the idea that institutional investors attempt to hold onto properties until they can sell them for a price at least equal lo the current appraised value, in effect trading off liquidity for reduced volatility. [ABSTRACT FROM AUTHOR]

Online businesses have been surging worldwide during the past decade, especially during the recent COVID-19 epidemic. However, the market share of online real estate transactions is still limited, mainly due to the information-asymmetry problem. In this study, we manually collect data on online judicial housing auctions in China, which is currently the largest online real estate market globally, and investigate how information disclosure facilitates real estate transactions. The empirical results suggest that disclosing better quality information online can attract more potential buyers. In particular, providing more comprehensive information such as professional appraisal reports or videos of the property can help to convert buyers' initial interests into completed transactions and higher sales proceeds. The positive effects of information are particularly strong when combined with offline services, in a more mature online market, and for low-value properties. We also provide preliminary analysis of factors affecting online-information-disclosure quality from both the macro and micro perspectives. We also provide preliminary analysis of factors affecting online-information-disclosure quality from both the macro and micro perspectives. [ABSTRACT FROM AUTHOR]

The determinants of mortgage default have been an area of rising interest since the 2008 recession. There are two distinguishing features of mortgage default analysis. First, predictor variables are often only recorded at origination. However, many important variables such as credit scores vary over time. Second, there are omitted variables (such as borrower's income and job security). If omitted variables are correlated with included regressors or if only origination values are used in a dynamic model, then biases may be present in econometric models for default risk. Our focus is to develop a ridge regression model to impute the dynamics of time-varying predictors and to capture unobserved borrower heterogeneity. The model is evaluated using cross-validation, and the relevant parameters are tuned to maximize out-of-sample predictive performance. After allowing for imputed dynamics and borrower heterogeneity, we find that the loan-to-value ratio becomes a larger signal of default risk and that credit scores as well as full documentation become smaller signals of default risk. These changes primarily are driven by imputing static variables, rather than dynamics, and may pertain to either omitted liquidity factors or strategic factors. [ABSTRACT FROM AUTHOR]

While the hedonic property value model and recently developed computable general equilibrium urban models assume the housing market is in equilibrium, recent years have witnessed extreme circumstances such as large changes in housing prices, high levels of mortgage default, and high levels of foreclosure that bring into question this assumption. This highlights the need for a better understanding of the dynamics of the housing market and the mechanisms that drive and sustain periods of disequilibrium. In this analysis, I develop a dynamic model of the housing market where vacancies naturally arise as the error correction mechanism. I estimate this model using annual U.S. panel data at the MSA level for 1990-2011. The results show that when there is excess demand, prices rise when vacancies fall but prices do not fall when there is excess supply and vacancies rise. This is consistent with the belief that prices are sticky downwards and hence prolong housing downturns. On the other hand, when there is excess supply, there is a relatively stronger decline in new housing in response to a rise in vacancies and much less of a new housing reaction when there is excess demand and vacancies fall. Furthermore, when I allow for a structural shift in the housing market brought on by the Great Recession (2006-2011), I find that the housing market became more responsive on both sides - excess supply and demand - during this period. [ABSTRACT FROM AUTHOR]

Using a unique and comprehensive dataset of loan-level home equity lines of credit serviced by large US national banks, we confirm that default risk of home equity lines of credit increases at end of draw. More importantly, we quantify the increase in default risk with the size of positive payment shock at end of draw. Furthermore, we find the effects are more pronounced when borrowers are under greater liquidity or refinance constraints and less pronounced if banks manage the credit risk proactively by freezing the credit lines. Our findings are robust across various model specifications and risk segments, payment shock definitions, and after controlling for sample selection bias from HELOC payoffs. These results have important implications for evaluating and managing HELOC credit risk: (i) the need to capture payment shocks, liquidity and refinance constraints in credit risk models, (ii) the benefit of smoothing payment shocks in contract design as well as the workout process, and (iii) the need to consider proper timing for tightening HELOC lending standards. [ABSTRACT FROM AUTHOR]

This study analyzes the price and time-on-market effects of short sale and lender-owned properties in the single-family housing market during the recent housing crisis. Short sales increased dramatically during the downturn as an alternative to foreclosures and deed-in-lieu of foreclosure transactions for resolution of defaulted mortgage loans. Using multiple listing service data, this study provides evidence that the price discounts associated with short sales and lender-owned properties differed significantly early in the crisis, but by the end of our sample the discounts were relatively similar in the sample market, which was not as hard-hit by the housing market downturn as markets examined in prior research. Using new time-on-market estimation methodology, the time-on-market results indicate that both short sale properties and foreclosed properties stayed on the market significantly longer than non-distressed properties, which differs from prior findings that foreclosed properties sell faster than non-distressed properties. The study also provides some evidence that different seller types (i.e. short sale-seller versus lender-seller) exhibit differences in their abilities to time their market entry. [ABSTRACT FROM AUTHOR]

This study examines how heterogeneous traders on both sides of transactions behave in the housing market under information asymmetry. Two types of buyers, namely, informed and uninformed buyers, correspond to local and non-local buyers in the empirical tests. Non-local housing buyers in Hong Kong pay a 2.8% premium over local buyers in the second-hand market for housing units with similar observable attributes. We distinguish real estate developers from sellers in the second-hand market. The former has an incentive and ability to reduce information asymmetry by providing a quality guarantee on the building structure and signaling with brand name, none of which can be fulfilled by sellers in the second-hand market. Empirical results show that developers' efforts to reduce information asymmetry allow them to fetch a higher price than sellers in the second-hand market, holding property characteristics constant. Such efforts are particularly valued by uninformed buyers as non-local buyers prefer to purchase in the first-hand market rather than in the second-hand market, especially when the problem of information asymmetry is serious. [ABSTRACT FROM AUTHOR]

Prior studies show infrastructural improvements impact property values positively. The effect is often reflected soon after the announcement and continues until the project is complete. These studies, however, are primarily set in developed countries. Emerging markets pose unique risks where uncertainty around implementation and funding could dampen these positive effects significantly. We utilize a quasi-natural experiment around an inner-city road redesign and improvement project in Bangalore, the fastest growing city in India. We exploit the difference-in-difference regression approach to examine the project's impact on residential and commercial property values around two sets of geographically proximate roads, one of which was chosen for the redesign. Unlike in developed countries, we find that property values are unaffected by the announcement when uncertainty is the highest but start reflecting the positive value of the infrastructure once construction starts and show significant gains upon completion. Our findings carry important policy implications for structuring value capture strategies in emerging markets. [ABSTRACT FROM AUTHOR]

Capital constraints are a major obstacle that holds back cash-poor households from purchasing a home. A workaround is to compromise the housing size and quality by buying a starter home one can marginally afford first. This study aims to investigate how capital constraints distort the pricing of starter homes. In Hong Kong, the government builds subsidized starter homes, which can be resold either to any households at full market prices through the privatized submarket or to households of limited affordability at lower prices through the affordable submarket. The subsidy in the latter case comes from the equity contribution of the government. If there were no capital constraints, the price gap between the two submarkets should simply be the government's equity. However, our empirical analysis reveals a much smaller price gap, indicating that households with limited affordability are willing to pay a starter home premium in order to relax their capital constraints. Our estimation shows that the premium is in the range of 4.5% to 6.8%, and enlarges when the housing market becomes more unaffordable. The pricing of starter homes is based not only on their quality but also on their ability to relax capital constraints. [ABSTRACT FROM AUTHOR]

This article presents a methodology for producing a quarterly transactions-based index (TBI) of property-level investment performance for U.S. institutional real estate. Indices are presented for investment periodic total returns and capital appreciation (or price-changes) for the major property types included in the NCREIF Property Index. These indices are based on transaction prices to avoid appraisal-based sources of index “smoothing” and lagging bias. In addition to producing variable-liquidity indices, this approach employs the Fisher-Gatzlaff-Geltner-Haurin ( Real Estate Econ., 31: 269–303, 2003) methodology to produce separate indices tracking movements on the demand and supply sides of the investment market, including a “constant-liquidity” (demand side) index. Extensions of Bayesian noise filtering techniques developed by Gatzlaff and Geltner ( Real Estate Finance, 15: 7–22, 1998) and Geltner and Goetzmann ( J. Real Estate Finance Econ., 21: 5–21, 2000) are employed to allow development of quarterly frequency, market segment specific indices. The hedonic price model used in the indices is based on an extension of the Clapp and Giacotto ( J. Am. Stat. Assoc., 87: 300–306, 1992) “assessed value method,” using a NCREIF-reported recent appraised value of each transacting property as the composite “hedonic” variable, thus allowing time-dummy coefficients to represent the difference each period between the (lagged) appraisals and the transaction prices. The index could also be used to produce a mass appraisal of the NCREIF property database each quarter, a byproduct of which would be the ability to provide transactions price based “automated valuation model” estimates of property value for each NCREIF property each quarter. Detailed results are available at . [ABSTRACT FROM AUTHOR]

We investigate the economics of real estate investment when maintenance of a property enhances neighborhood value. Because a property owner does not recognize this positive externality for his/her neighbor, he/she under-maintains. Smaller properties benefit most from this externality. We show that subsidizing the maintenance expenses of properties can induce socially optimal maintenance. Without disturbing social optimality, the maintenance subsidy can be financed with either a flat tax or a tax that is proportional to the land value or the cost of the improvement. The flat tax is less costly. Commonly used subsidies in the real estate industry based on loan guarantees do not promote socially optimal maintenance. [ABSTRACT FROM AUTHOR]

In 1992, an alternative way was developed to test for property tax inequities related to property value. The method is substantially different from generally accepted regression approaches. Tests were applied by looking for differences in assessments relative to market, both within and between neighborhoods making up whole assessment areas. In contrast, regression models were applied to these whole areas as single entities. The earlier regression approach has the disadvantage of not being able to isolate tax inequity based on differential treatments within neighborhoods. The more micro-oriented method used makes it possible to identify more comprehensively any inequity that exists in an assessment jurisdiction. Inequity is measured by the total variation in assessment/sales (A/S) ratios for any set of property sales. The coefficient of dispersion (COD) is the traditional measure of variation in A/S ratios for sets of sales data drawn from a specified time interval. Total inequity for residential property is said to be acceptable if COD is 15 or less.

Examines the impact of default-option value on the foreclosure of insured mortgages. Literature on default-option value; Decomposition of the theoretical default-option boundary into property-value and interest-rate effects; Development of empirical variables for statistical analysis.

Employing a recently developed panel econometric technique, first, we show that accounting for spatial dependence and heterogeneity yields more accurate risk factor coefficients and abnormal housing returns. Rather than systematic risks, idiosyncratic risks explain the variations in residential housing excess returns. After controlling for asset-specific and systematic risk factors, the positive and significant impact of the unobservable common factors on the excess returns suggests that speculative market forces drive the housing excess returns. Second, we then analyze the risks and returns of houses in affordable and expensive submarkets allowing for spatial dependence and heterogeneity. We find that houses in the affordable submarkets perform better than houses in the expensive submarkets. Thus, the potential demand for houses in the affordable submarket may aggravate the housing affordability crisis. Our study's results, therefore, encourage policymakers and investors to view the housing market as a collection of regional units and submarkets, but not as a single national market. [ABSTRACT FROM AUTHOR]

An economic experiment with endogenous institutions informs the political economy of land value taxation relative to uniform property taxation in terms of efficiency and sprawl reduction. Heterogeneous type distributions were used so that land value taxation was earnings-rational, relative to uniform property taxation, for 40, 60, and 80 percent of the participants. The model's induced values predict land value taxation leads to less sprawl, more earnings, and more tax revenue than uniform property taxation. Experimental data do not consistently match this prediction, where both tax institutions led to more sprawl and lower earnings than predicted. Results show participants voted for the tax institution that does not maximize their individual earnings in 16.7 percent of rounds. These earnings-irrational choices occurred when the type distributions were 40 and 60 percent in favor of land value taxation. The experiment results nonetheless show the absolute advantage of land value taxation for producing less sprawl, more tax revenue, and more earnings. Moreover, the behavioral evidence suggests that relative advantage of land value taxation in reducing sprawl is greater than predicted by the model. This suggests further inquiry about whether land value taxation promotion activities may best be targeted towards cities using uniform property taxation where economies are vibrant, land uses are already relatively intensive, and greater-than-average population density already exists. [ABSTRACT FROM AUTHOR]

We extend the literature on the impact of stormwater retention basins on house prices and time on the market. Our results indicate that properties located closer to a basin sell at a discount relative to properties located farther away, but the impact is not linear. We further provide evidence that home buyers pay premium prices to be located closer to a basin in construction, yet as the basin ages, property prices decrease. Although stormwater basins provide benefits for the community, results suggest that proximate households generally bear the cost. In the locations adjacent to the basins, discount prices of proximate homes tend to be larger in low-income areas. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of cash-only transactions on residential property values before, during and after the financial crisis. Using a comprehensive database of residential property sales in Tallahassee, FL from 2006 to 2015 and a propensity score matching model, we find that, on average, cash-only transaction is associated with a 4.9% discount to the overall housing price. Further analyses reveal that the cash-only discount is present only in the lower- price segment after the financial crisis. Although cash-only transactions are more common for distressed, investor-purchased and rental properties, we find no significant cash-only price discount for these property categories except for the lower-priced segment. Overall, we demonstrate that cash-only price discounts are less contingent on the distressed status, but more so driven by the increased supply and attractiveness of lower-priced homes by investors. [ABSTRACT FROM AUTHOR]

A co-listing strategy exists when two or more listing agents jointly represent the owner of a property who desires to sell it. This strategy is not new in the real estate brokerage industry, but its popularity has increased during recent years with the formation of teams of agents who repeatedly work together using the co-listing strategy. To date, the literature has not analyzed this business strategy. This study investigates the probability of selling, selling price, and time on market effects related to the use of the co-listing strategy. The results of this study indicate that co-listing is associated with a higher probability of sale, an increased selling price, and a marginal longer or shorter marketing time, depending on the situation. Comparing market outcomes for agents who form teams and repeatedly employ the co-listing strategy against market outcomes for agents who are involved in only one co-listing indicates that both types of co-listing produce higher prices and are more likely to result in a sale, but the effects for repeated co-listings are larger in magnitude. Additionally, repeated co-listing slightly reduces marketing time, but single co-listing slightly increases marketing time. The marketing time effects in both repeated and single co-listings, however, are too small to be economically important. In general, this study suggests that sellers are better served by the co-listing strategy compared to no co-listing, especially when the co-listing agents repeatedly work together in teams. [ABSTRACT FROM AUTHOR]

According to the Federal Reserve Board, banking firms have recently been shifting significantly larger portions of their loan portfolios into real estate. This increase in real estate lending has caused concern about the continuing economic health of banks on the part of state and federal regulators, since changes in real estate returns, evidenced by changes in property value, can potentially have a significant impact on bank default risk and profitability. However, concerned parties do not seem to have explicitly considered the relationship between mortgage default risk and the specific characteristics of real estate investments. This study examines the sensitivities of stock returns for different bank groups, based on the percentage of total loans in real estate and the percentage of loans in five different mortgage categories (construction and development loans, farmland loans, one- to four-family residential loans, multifamily residential loans, and nonresidential and nonfarm loans), to changes in real estate market returns. This is done by developing and using a three-index model. The results of this study indicate that bank stocks, overall, are very sensitive to changes in real estate returns. Banks, with a larger portion of their total loans invested in all types of real estate loans, except farmland loans, are most sensitive to changes in real estate returns. [ABSTRACT FROM AUTHOR]

Real estate returns often show highly positive autocorrelation. However, with the Hong Kong housing market data, we found two anomalies. For one, the autocorrelations of the district-level submarket returns are mostly negative. For the other, despite the negative or insignificant submarket autocorrelations, the autocorrelation of the aggregate market returns is highly positive. This study explains the two patterns. First, we show analytically how observed autocorrelation, transaction noise, and the speed of return adjustment are related. The model suggests that even if return adjusts instantly to news, the transaction noise in observed prices will lead us to observe a negative autocorrelation. An empirical approach is derived to recovering the adjustment speed of returns from the negatively biased autocorrelation. Second, the autocorrelation of returns of a market is a function of not only the autocorrelations of its submarkets, but also the cross lead-lag relationships between the submarkets. Strong cross lead-lag relationships inflate the autocorrelation of the aggregate market returns. Two competing hypotheses for explaining the cross lead-lag relationships between submarkets, namely spatial information diffusion and transaction costs, are tested. Empirical tests based on Hong Kong housing market data support the transaction cost hypothesis against spatial diffusion. [ABSTRACT FROM AUTHOR]

Renewable energy production is one of the most important policy instruments to fight climate change. However, despite global benefits, renewable energy production entails some local challenges, such as requiring more space per unit production capacity. In this paper, we study the external effects of large-scale conventional and renewable electric power generation facilities on local house prices. We combine information of all coal, gas, and biomass plants, as well as all wind turbines in the Netherlands, with 1.5 million housing transactions over a period of 30 years. Using a difference-in-difference as well as a repeated sales model, we study the effects of facility openings and closings. Our results show negative external price effects for gas plants and wind turbines, but positive effects for biomass plants, conditionally upon ex-ante lower priced locations. The external effects of power generating facilities on local housing markets are important to consider, especially with the current focus of public policies on the expansion of renewable energy generation. Our paper is one of the first to present a large-scale study, using detailed information, and comparing several different energy sources in one framework. [ABSTRACT FROM AUTHOR]

The loss on a distressed mortgage depends not only on economic and financial conditions but also on the value of the property and how it is transferred to a new owner. Using data from Fannie Mae, we investigate the differences in loss experience across alternative mechanisms for disposing of property (real estate owned or REO, deed in lieu, short sales, and foreclosure sales) from 2003 through 2017. In general, losses are lowest for short sales and foreclosure sales. But these lower losses depend on the overall distress level of the market. The more distressed the market is, the smaller the relative gains associated with these alternative approaches, as compared to traditional REO sales. In contrast, in markets with rapidly increasing distress short sales have lower losses relative to traditional REO sales. We use a variety of matching techniques to address selection issues associated with REO properties and find that the lower loss severities associated with non-REO sales remain. [ABSTRACT FROM AUTHOR]

This article reviews research on the economics of information in real estate. It covers equity investment in private and public markets and intermediation by brokers. The review shows how, by examining the nature and extent of information frictions in these important markets, research has improved our understanding of potential market failures and corrections which can improve market functioning. [ABSTRACT FROM AUTHOR]

We examine the role of information disclosure in the housing market, offering both theory and evidence for observed variability in disclosure strategies among property listings in a multiple listing service (MLS). Our initial empirical findings and the theoretical literature suggest a positive link between information disclosure (e.g., number of photos) and marketing outcomes (e.g., sale price, liquidity). While intuitive, it raises an interesting puzzle: why then do some agents disclose less information? Analytically, we show that it can be optimal to omit information in some circumstances, particularly when homes are more heterogeneous or have greater scope for taste-specific attributes. Empirically, the data support the prediction that less information disclosure is beneficial for a large subsample of properties (i.e., high-end homes). Our results also reveal scope for new principal-agent issues, as agents generally disclose less when they market their own homes, and even less for their higher-end homes when it is a more optimal strategy. [ABSTRACT FROM AUTHOR]

This study investigates whether the local housing markets can be affected by the occurrence of a large-scale but distant hurricane without direct impact. Using a dataset of residential transactions in Miami-Dade County, FL between 2005 and 2014, we find that the impact of a property's flood risk exposure on its value varies over time, with a price penalty of 4% in hurricane striking period. By contrast, within a quiet hurricane period, properties within high flood hazard zones demand a price premium ranging roughly from 4% to 6%, which may represent the price impact of water-related amenities. The premium declined significantly upon Hurricane Sandy. Several possible explanations are provided and tested to explain the main findings. Our findings indicate that the occurrence of a disastrous hurricane which impacted faraway regions also raised local home buyers' perception of flood risk, but for a short period of time (one quarter). [ABSTRACT FROM AUTHOR]

Foreclosures lead to lower house prices in the short run. However, whether or not foreclosures also have long-run or legacy price effects has not been addressed extensively. Do neighborhoods with a greater number of past foreclosures exhibit long lasting house price discounts? This paper examines both transitory and legacy foreclosure price effects. We use almost 20 years of data from one of the epicenters of the foreclosure crisis: Orange County, Florida. We measure the number of recent and past foreclosures within narrowly defined neighborhoods for each house sold during 2016–2019:Q2. We compare transaction prices with different numbers of recent and past foreclosures, while controlling for differences in observed property characteristics and taking measures to reduce the impact of unobserved heterogeneity. We find that greater numbers of recent and past foreclosures are associated with lower house prices. We find strong transitory effects consistent with the existing literature. We also find significant but modest legacy effects on surrounding prices. These long-run discounts are about 0.41 percent to 0.79 percent in Orange County, Florida. [ABSTRACT FROM AUTHOR]

Whether household wealth affects labor market behavior is an important empirical question in economics. As the literature only discusses the effect of the absolute value of housing wealth on homeowners' labor supply, this paper studies how a homeowner's relative housing wealth—i.e., perceived housing wealth gain compared with their reference group-affects labor market behavior. Using China's housing boom as a natural experiment, we first construct homeowners' reference housing wealth using the hedonic method and then estimate the effect of homeowners' relative housing wealth on labor supply. Subsequently, we identify a causal effect of relative housing wealth on homeowners' labor supply using an instrumental variable approach and find that an appreciation in relative housing wealth does not significantly influence homeowners' employment, but significantly reduces their working hours. Our results show that this reduction in working hours is mainly driven by female homeowners. Our results also suggest that the effects of relative housing wealth vary across educational backgrounds, marital statuses, and locations. We find that the effect is more pronounced for female homeowners who are less educated, married, and living in rural areas. Moreover, a set of robustness checks corroborates the validity of our identification strategies and tests the sensitivity of the results. [ABSTRACT FROM AUTHOR]

In timing property listings, real estate developers can exercise the "option to wait" or "option to presell" to mitigate price uncertainty risk. In this study, we study the effectiveness of both strategies under a unified framework. We test our hypotheses using residential development data from Hong Kong between 1995 and 2015. Empirical evidence shows that when the presale option is unavailable, developers tend to adopt the waiting strategy when facing price uncertainty risk. Conversely, when a presale option is available, developers will accelerate sales when price volatility is high. Moreover, the effectiveness of the presale option depends substantially on government restrictions. Our approach facilitates the identification of the net effect of either tool and provides an opportunity to unify conflicting findings in the literature. [ABSTRACT FROM AUTHOR]

Real Estate Investment Trusts (REITs) renew and recycle their property portfolios through divestment of inefficient assets and new acquisitions. Most previous literature focuses on the wealth effect of acquisition on REIT-level performance, while the property-level renewal process of REIT portfolios (especially divestments) remains unclear. Using a unique property-level dataset of Japanese REITs, we fill this gap by investigating the determinants of property divestment and the management strategy leading up to the divestments. We find that REITs strategically choose properties designated for divestment. The criteria include: (i) economic obsolescence that is captured through relatively large operating expense and/or a high rental yield within the REIT portfolio, (ii) mismatch in the geographical focus of the REIT, and (iii) a significant change in the capital value since acquisition. Especially during the periods of REIT growth, most of the above criteria apply, suggesting that the long-run renewal of a portfolio leads to its efficient asset allocation. We also provide evidence of property-level earnings management by REITs: the size of the capital expenditure is reduced just before the divestment to increase the net cash flows to appeal to potential buyers. [ABSTRACT FROM AUTHOR]

Households with children may Tiebout (1956) sort to safe cities. Cities that cut funding for police protection may become less attractive to households with children, spurring housing developers to build smaller houses with fewer rooms. Voting data on police tax levies using regression discontinuity suggests that newly-built houses have more rooms in cities that renew rather than fail their tax levies. The treatment effect peaks in the second year after the tax levy at 1.9 rooms, a sizeable difference over the mean of 6.6 rooms. House size tells a similar story: the difference between newly-built houses in communities that pass and fail public safety tax levies is 317.6 square feet (29.5 square meters), representing 15% of the mean house size in the sample. The results become evident 2 years after the tax levy and persist in the third year before petering out in the fourth year. The effect may stem from communities signaling a decreased commitment to public safety, rather than an increase in the crime rate itself, because cutting small tax levies has about the same effect on house size as cutting large tax levies. [ABSTRACT FROM AUTHOR]

Reverse mortgages are a financial tool for lower-income seniors to release home equity and increase their retirement income. In the United States, reverse mortgages are generally insured by the Federal Housing Administration (FHA) through the Home Equity Conversion Mortgage (HECM) program, which protects borrowers from owing more than the value of their house. Previous research on reverse mortgage valuation typically focuses on mortgage termination risks related to mortality and morbidity, but few studies explore the impact of early surrender on the entire risk profile of reverse mortgages. To fill this gap, we propose a utility approach to investigate borrowers' surrender behavior. We explore how a surrender-and-refinance strategy affects the cash flows of the HECM insurance program and also assess its tail risk. [ABSTRACT FROM AUTHOR]