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• Mediation analysis is used to identify both the direct and indirect effects of skills acquired by early adulthood on homeownership later in life. • The AFQT score, a measure of cognitive skills, has large indirect effects through the mediator variables—education and income. • Through both direct and indirect channels, AFQT scores in early adulthood are shown to explain one-quarter to one-third of the homeownership gaps between White, Black, and Hispanic households. • Reducing disparities in educational outcomes would meaningfully contribute to reducing gaps in minority homeownership. This paper shows that skills acquired by early adulthood affect homeownership levels achieved later in life in important ways. The paper examines three sets of skills—cognitive skills, as measured by the Armed Forces Qualifying Test (AFQT) score; non-cognitive skills (specifically, the degree to which people believe that they have control over the outcome of events in their lives), measured by the Rotter score; and social skills, using a Social score based on Deming (2017). Mediation analysis is used to identify both the direct and indirect effects of these skills, as captured by the three different types of scores, on homeownership. We show that the AFQT score measuring cognitive skills not only captures direct effects on the homeownership rate, but even larger indirect effects through the mediator variables—education and income. AFQT scores in early adulthood are shown to be highly predictive of homeownership outcomes, explaining roughly one-quarter to one-third of the disparate outcomes between White, Black, and Hispanic households. We also examine the degree to which the AFQT, Rotter, and Social scores explain variation in homeownership rates over an individual's life cycle. The findings suggest that reducing disparities in educational outcomes would meaningfully contribute to reducing minority homeownership gaps. [ABSTRACT FROM AUTHOR]

• We avail of a new housing and financial sector model of the Irish economy to characterise the determinants of Irish house prices over the period 1995–2019. • The suite of models are used to examine the contribution of developments in both monetary policy and financial stability as well as the performance of the real economy and supply-side of the Irish residential sector. • Our results have interesting implications for the growing literature examining the intersection of monetary policy and financial stability on house prices. While many western economies experienced substantial fluctuations in house prices since the turning of the century, the Irish residential market stands out as a particular case. Irish house prices experienced profound increases in the period leading up to the global financial crisis (GFC); thereafter the concomitant downturn in both the real Irish economy and financial sector precipitated a dramatic decline in prices between 2007 and 2012. However, since 2012 prices have increased in a sustained and persistent manner. A number of possible reasons are commonly cited for the recovery. In this paper we avail of a new housing and financial sector model, which are part of a broader macro-econometric model, COSMO, of the Irish economy to characterise the determinants of Irish house prices over the period 1995–2019 and in particular to examine the reasons for the post 2012 recovery. The suite of models are used to examine the contribution of developments in both monetary policy and financial stability as well as the performance of the real economy. The role played by the sluggish response of the supply-side of the Irish residential sector is also assessed. The supply-side of the Irish market was especially impacted by the GFC and has struggled to respond to the surge in housing demand which has accompanied the general economic recovery since 2012. Our results have interesting implications for the growing literature examining the intersection of monetary policy and financial stability on house prices. [ABSTRACT FROM AUTHOR]

• Negative reviews have a greater effect on pricing, especially for lower-priced listings. • Reviews related to facilities and location have a larger impact on listing prices. • Reviews have a larger impact for listings near the city center. • There exists a lag effect for the impact of reviews on Airbnb prices. This study investigates the influence of customer review content and other attributes on Airbnb listing prices, using data from listings across 26 U.S. regions. By integrating sentiment analysis and topic modeling with hedonic and quantile regression models, this paper examines the significant role of electronic word-of-mouth in the short-term rental market, by studying how review sentiments and topics affect pricing strategies. The findings reveal that negative reviews have twice the impact on listing prices as positive reviews; and fourfold for lower-priced listings. Moreover, the results of topic modeling show that both positive and negative reviews related to facilities and location have a larger impact on listing prices. Additionally, the study looks at how the distance of listings from the city center and the timing of reviews affect pricing adjustments. The influence of reviews diminishes for listings located farther from the city center, indicating that Airbnb listing prices near the city center are more sensitive to changes in price determinants. The study also uncovers the existence of a lag effect in how reviews impact prices, showing that Airbnb hosts may not adjust prices as quickly as hotel owners. Overall, the study enriches existing literature by taking into account the review content and type of customer reviews, offering a more comprehensive understanding of short-term rental pricing. [ABSTRACT FROM AUTHOR]

This paper analyzes online real estate listings to estimate the listing price elasticity of search activity for the individual seller for both the rental and sales market. This elasticity is an essential parameter in the literature modeling the process of selling a home, as it indicates the extend to which potential buyers will react to the listing price. Furthermore, we argue that our estimates are an approximation for the average price elasticity of demand facing the individual seller, which is an indication for the amount of competition in the market. A novel dataset tracking real estate advertisements on a daily basis allows to control for unobserved heterogeneity between properties by using property fixed effects, exploiting the variation caused by changes in listing prices and search behavior throughout the listing process. The findings indicate that a one percent increase in the listing price reduces search activity for the property by 6.7 percent for the sales market and 6.6 percent for the rental market. Additionally, we find that an increase in the number of listings in a market segment enhances the listing price elasticity. • We estimate the own listing price elasticity of online search activity for the sales and rental housing market. • A Poisson regression model is used to measure the extend to which search activity reacts to listing price changes. • The elasticity approximates the average Lerner index and is an indication for the amount of competition in the market. • An increase in the number of listings in a market segment enhances the price elasticity and competition in general. [ABSTRACT FROM AUTHOR]

This paper investigates the relative importance and effect of conventional and unconventional Canadian monetary policy surprises on housing prices. Using a credible approach to identify structural monetary policy shocks in Canada and a comprehensive Bayesian VAR model to analyze their effects on financial and macroeconomic variables, we find that both conventional monetary policy and quantitative easing shocks have a significant and persistent effect on housing prices in Canada. However, the inflationary effect of a quantitative easing shock is more pronounced than that of an easing target monetary policy surprise. Specifically, the peak effect of a 25-basis point expansionary conventional monetary policy shock is a 2.30% increase in real housing prices while a comparable quantitative easing surprise leads to a peak of 4.56% increase in real housing prices. We conclude that expansionary monetary policy in various forms has had significant inflationary effects on Canadian housing prices. But quantitative easing surprises stand out as the most prominent contributory factor to the escalating Canadian real estate price. Quantitative easing impact consistently outweighs the effects of forward guidance and conventional monetary policy shocks. • Identifies Canadian monetary policy shocks, both conventional and unconventional. • Analyzes impact on housing prices using Bayesian VAR for new insights. • Quantitative easing (QE) impacts housing prices more than conventional shocks. • A 25bps conventional shock raises housing prices by 2.30%; QE by 4.56%. [ABSTRACT FROM AUTHOR]

• Loan-to-value limit was effective in reducing households' leverage. • Affected households paid higher interest rate spreads and had higher loan-service-to-income ratios. • Lona-to-Value limit changed households' housing choices, as constrained households bought less expensive houses. This paper investigates the impact of changes in lending limits on household leverage and housing choices. Using credit registry data and a difference-in-differences estimation strategy we determine how a change in the loan-to-value (LTV) ratio - a macroprudential policy tool - affected constrained households. Our results show that the policy change was effective in reducing households' leverage as constrained households took out smaller loans and had lower loan-to-income ratios. Such households also paid higher interest rate spreads and had higher loan-service-to-income ratios than the control group. Finally, we also show that the policy change affected households' housing choices, as constrained households bought less expensive houses. Our results highlight the improvement of the risk profile of households following the introduction of the LTV limits. [ABSTRACT FROM AUTHOR]

· A partial understanding of the channels through which homeownership affects labour market outcomes may contribute to the inconclusiveness of empirical studies. · This paper focuses on a so far neglected channel through which homeownership affects labour market outcomes of the unemployed: financial hardship. · Following 3826 unemployed Australians over time, we specify a matching estimator analysis with specific endogeneity controls. · We find that homeownership indeed reduces perceived and experienced measures of financial hardship. · Given falling homeownership rates, our findings are both timely and imperative to understand the effect of homeownership on labour market outcomes. We follow 3,826 Australian unemployed persons, approximately half of whom are homeowners. We conduct a matching analysis and find that homeownership reduces both experienced and perceived financial hardship. Building on recent findings in the literature that the presence of financial hardship deteriorates job search quality (i.e., stressors like financial hardship lead to the adoption of haphazard rather than focused job search strategies), we introduce financial hardship as a novel channel through which homeownership affects labour market outcomes of the unemployed. In our matching analysis, we include historical labour market performance and personality traits linked to mobility preferences, to address endogeneity. We also confirm that homeownership reduces residential mobility and increases neighbourhood social capital but find no effect on reservation wages of the unemployed. Considering declining homeownership rates across the OECD in recent years, our findings are both timely and imperative to understand the effect of homeownership on labour market outcomes of the unemployed. [ABSTRACT FROM AUTHOR]

• Introduction to the joint special issue of land economics (LE) and the journal of housing economics (JHE) focused on property value applications using Zillow's ZTRAX data. • ZTRAX is a real estate–focused database with over 400 million public records spanning nearly all U.S. counties across more than 30 years. • Includes comments from Zillow. • This special issue contains seven papers that use the ZTRAX data. Four consider environmental issues: flooding, chemical accidents, and green space, two analyze farmland values and one looks at property tax salience. • All these papers take advantage of the scope of the ZTRAX data to carry out broad geographic analyses that have not been previously undertaken in their respective literatures. This is the Introduction for the joint special issue of Land Economics (LE) and the Journal of Housing Economics (JHE) focused on property value applications using Zillow's ZTRAX data. ZTRAX is a real estate–focused database with over 400 million public records spanning nearly all U.S. counties across more than 30 years. The spatially explicit data on deed transfers, sale prices, and property characteristics has provided the basis for analyses on themes such as disaster risks, including wildfires, flooding, and chemical accidents; natural resources, including water quality, farmland, and coal; and land uses, such as open space, national parks, and critical habitat designation, among others. [ABSTRACT FROM AUTHOR]

• Land use change projections are important tools for land use planning and the implementation of farmland protection policies as they identify agricultural lands that are most at risk of being developed and help inform conservation priorities. However, these projections are highly dependent on their underlying assumptions and market trends. Since socioeconomic shocks can alter market trends, it is critical to assess the need to projections if these underlying assumptions and trends no longer hold. The goal of this paper is to assess how the COVID-19 pandemic may have altered land use projections, particularly housing demand at the urban-agricultural interface. • This paper uses ZTRAX program U.S. housing transaction data and novel, nationwide land-use projections to conduct a national hedonic difference-in-difference analysis to investigate how the COVID-19 pandemic has altered development pressure at the urban-agricultural margin. The analysis includes state-level analyses for 33 states and a national analysis with a sample of 3.7 million property transactions that occurred outside of highly developed areas. • We use the land use projections to define treatment and control groups, such that treated parcels are those in an area that is projected to be developed by 2040 ("high-risk"), and control parcels are all other parcels in our sample. • We find evidence that following the pandemic onset development pressure has decreased in areas projected to be developed. We also find evidence that this pattern holds in areas of high development risk around cities larger than 50,000 people, but around small cities, with less than 50,000 people, we find evidence that development pressure has increased in these areas projected to be developed. • Updated land use protections provide vital information for land-use planners and policy makers at state and local levels, where the majority of land use planning and policy decisions occur, which motivates our state-level analyses, which is the focus of our paper. As human populations grow, one strategy for meeting housing demand is through the development of agricultural land and other open space, which can generate negative externalities. This may be addressed at local, state, or federal levels with land-use planning, including farmland preservation policies. Efficient land-use planning in the presence of competing land uses requires knowledge of development risk, housing preferences, and the full costs of farmland loss. We conduct a national scale hedonic analysis using the ZTRAX program U.S. housing transaction data to investigate how COVID-19 has affected property prices in suburban and rural areas with farmland at high risk of development, for the purpose of understanding the effects of COVID-19 driven shifts in housing location preferences. Our analysis demonstrates that the pandemic caused differential price impacts across the 33 states that we analyzed. Furthermore, our estimates suggest heterogeneous price effects driven by the characteristics of nearby urban areas, with prices appreciating faster on land at risk located near smaller urban areas than those near larger urban areas. Our analysis finds that the spatial pattern of development pressure on agricultural lands, as measured through transaction prices, changed in the aftermath of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

A substantial increase in electricity demand has triggered a rising investment in energy infrastructure in the US over the last decade. This paper examines the capitalization effects of electricity transmission lines (TMLs) on nearby farmland values and housing prices in the Midwest from 2015 to 2019, based on 16,026 parcel-level farmland sales data from FarmlandFinder and 1,905,280 housing transaction data from the Zillow Transaction and Assessment Dataset database. Our estimation results reaffirm the disamenity effects of TMLs on housing property values and find that the disamenity effects are larger on houses in urban areas than in rural areas. Nearby TMLs generate premiums for surrounding farmland, which contrasts with the disamenity evidence due to aesthetics (either visual or audible) in the literature. We further show that farmland parcels within 0–2 km of TMLs in high-wind areas are approximately 3.10% more expensive than comparable parcels in low-wind areas. Our paper provides novel and contrarian evidence on the effects of TMLs on property values amid rising investment in energy infrastructure. • This paper examines the capitalization effects of electricity transmission lines (TMLs) in US Midwest housing and farmland prices. • The analysis is based on nearly 20,000 farmland sales transactions and 2.5 million Zillow housing sales from 2015 to 2019. • TMLs are disamenities for urban housing prices, but generate premium for farmland prices. • The premium of TMLs in farmland markets are stronger in high-wind-resource areas. [ABSTRACT FROM AUTHOR]

Making use of data from the Brazilian Census, this paper presents descriptive evidence on Brazilian slums while attempting to test the squeezing hypothesis from the squatting literature. A comparison of mean values for a host of household and neighborhood variables often shows wide, and usually predictable, differences in values between neighborhoods designated as slums by the Census and nonslum neighborhoods that lack this designation. The paper presents a variety of descriptive regressions making use of these rich data, while providing evidence consistent with the squeezing hypothesis in city-level regressions showing that a higher population share or land share in slums leads to higher formal rents. [ABSTRACT FROM AUTHOR]

• This paper analyzes different appreciation patterns for neighborhoods with different level of income and housing prices. • The effect of neighborhood characteristics on housing prices is different for high-income neighborhoods than for low-income neighborhoods. • Moreover, within low-income neighborhoods, neighborhoods that have been gentrified have different appreciation patterns. • The effect of gentrification on housing prices is heterogeneous. On average housing prices are not affected by gentrification. • Gentrification appreciates housing prices in neighborhoods experiencing early gentrification, but not in those being gentrified for longer periods of time. Using data from Chicago, this paper analyzes different housing appreciation patterns from 1983 to 2005 depending on the initial level of income of the neighborhoods where these properties are located. Findings suggest that appreciation patterns of low-income neighborhoods are different than those of high-income neighborhoods. Moreover, appreciation of housing prices in low-income neighborhoods that have experienced gentrification is different than in other low-income neighborhoods not gentrified. To analyze this issue further, we compare the behavior of housing prices in neighborhoods experiencing different stages of gentrification with housing prices in low-income neighborhoods that have not been gentrified. Housing price appreciation is only observed in neighborhoods gentrified that had low levels of income when gentrification was measured. One interpretation of these findings is that housing prices appreciate in neighborhoods experiencing early stages of gentrification, but not in neighborhoods that have been gentrified for longer periods of time. These results could suggest that gentrification may cause displacement pressures in the early stages, but prices are stabilized in neighborhoods being gentrified for some time, reducing the probability of displacement of the low-income population. [ABSTRACT FROM AUTHOR]

• We employ a boundary discontinuity design to separate the costs of easy access (EA) to urban parks. • On average, houses with EA to urban parks face a depreciation effect of 2.0% of their value. • The value reduction equals approximately $7,986 per house in 2018 price. • Numerous visits to areas with EA to urban parks lead to disamenities, ultimately causing negative effects on the EA houses. This paper employs a boundary discontinuity design to separate the cost of easy access (EA) to urban parks from the combined effects of proximity. 1 1 We define a house with EA to urban parks as a given house located on the park side of a major road, within a walking distance of d meters, which will be further discussed in Section 2.1. On average, houses with EA to urban parks experience a significant price reduction of 2.0%. This reduction equals approximately $7,986 per house in 2018 dollars, all else being equal. The average negative effect originates from EA to city parks. Mechanism analysis using novel cellphone data reveals that frequent visits to areas with EA to urban parks can lead to congestion disamenities that have a negative effect on the prices of EA houses. [ABSTRACT FROM AUTHOR]

• Retirement increases in the probability of making a residential move or the likelihood of becoming outright homeowners. • Individuals downsize both physically and financially and tend to move to better neighbourhoods or closer to the coast upon retirement. • Housing mobility choices are primarily influenced by the wife's retirement while housing downsizing decisions are only affected by the husband's retirement. This paper provides the first causal evidence on the impact of retirement on housing choices. Our empirical strategy exploits the discontinuity in the eligibility ages for state pension as an instrument for the endogenous retirement decision and controls for time-invariant individual characteristics. The results show that retirement leads to a statistically significant and sizable increase in the probability of making a residential move or the likelihood of becoming outright homeowners. We also find that individuals downsize both physically and financially and tend to move to better neighbourhoods or closer to the coast upon retirement. We additionally discover that some housing adjustments take place up to 6 years before retirement. Moreover, our results reveal significant heterogeneity in the retirement impact by gender, marital status, education, housing tenue, income and wealth. Within traditional heterosexual couple households, housing mobility choices are primarily influenced by the wife's retirement while housing downsizing decisions are only affected by the husband's retirement. [ABSTRACT FROM AUTHOR]

This paper exploits a unique set of Dutch micro data between 2006 and 2014 to analyze the heterogeneous responses in prepayment behavior to changes in financial incentives. Prepayment is defined as paying back a part of the mortgage on top of the contractual payment schedule, excluding refinancing. Because interest rates on savings have decreased while the rates on existing mortgages are generally fixed for some years, the value of prepaying a mortgage has increased. This corresponds with the surge in prepayments at the Dutch mortgage market. Using various econometric specifications, that take into account unobserved heterogeneity and endogeneity, the paper finds that incentives to prepay explain only a part of prepayment behavior. However, incentives to prepay explain a much larger part of prepayments for wealthier households and for households with a high net-of-tax interest rate differential. [ABSTRACT FROM AUTHOR]

This paper provides the introduction to the special issue on Race and the City in the Journal of Housing Economics in 2018. The paper surveys relevant topics on racial and ethnic discrimination and residential segregation, and provides a more detailed discussion of the specific papers in the special issue. The paper primarily focuses on the literatures on discrimination in housing, on-line markets and policing. In terms of racial segregation, the paper discusses work related to the pattern of residential segregation and the causes and consequences of segregation. [ABSTRACT FROM AUTHOR]

This paper makes the first attempt to empirically examine the effect of site value taxation on the value of land and explore the differential effects across various types of land use. Using municipality-level panel data, the study shows that raising the tax rate on land while lowering the tax rate on buildings leads to an increase in land value per acre. Further, this impact differs between residential land and commercial and industrial land. Residential land appears to be more responsive to changes in the tax differential than commercial and industrial land. The paper contributes to the literature on land value taxation by testing important theories that have never been tested before and offering the first empirical evidence on the impact of site value taxation on land value. [ABSTRACT FROM AUTHOR]

This paper studies how information frictions in the securitization market amplify the response of mortgage credit supply to house price shocks. Securitization prices and quantities endogenously result from an optimal contracting problem between investors and banks. Banks are better informed than investors about the quality of mortgages they originate, leading to adverse selection in securitization. Investors use the quantity sold as a screening device to induce banks to reveal truthful information. We find that adverse selection amplifies the response of a bank's mortgage credit to house price shocks. The degree of amplification is also a function of the technological differences in managing portfolios between banks and investors. The model is informative on how information frictions can induce large fluctuations in mortgage credit supply. • Banks and investors interact in a securitization market affected by private information. • Investors screen banks' mortgage portfolios by designing securitization contracts. • House price shocks affect securitization through nonlinear price and quantity effects. • Aggregate credit supply becomes a nonlinear function of securitization liquidity. • Adverse selection amplifies the credit supply response to house price shocks. [ABSTRACT FROM AUTHOR]

This paper examines the impact of two nationwide reforms to the National Flood Insurance Program on both flood insurance and property markets. The 2012 and 2014 reforms aimed to phase out subsidies on flood insurance premiums. Using a difference-in-differences framework comparing treated and similar but untreated properties, we find that the reforms led to a 14.3% relative increase in the price of flood insurance, an 8.2% decrease in insurance demand, a 4.2% decrease in property prices and a 2.3% decrease in property transaction volumes. As flood risk continues to accelerate across the United States, properly pricing insurance premiums can effectively discourage households from living in risky areas, but may involve potential trade-offs such as the unintended outcome of a large drop-off in insurance coverage. • Recent reforms in the National Flood Insurance Program caused a 14.3% increase in the price of insurance for affected properties. • In response, insurance demand dropped by 8.2%. • The sales prices of affected properties decreased by 4.4% and their transaction volumes fell by 2.3%. [ABSTRACT FROM AUTHOR]

Area-based initiatives (ABI) remain a popular approach to combating urban decline. In this paper we examine one such spatially concentrated effort in Oslo, Norway, to test whether the program has succeeded in making the targeted neighborhoods more attractive as measured by house prices. The Oslo ABI is an interesting case as it distinguishes itself by its extensive emphasis on improving the social fabric of distressed neighborhoods. Place-based policies generate spatial discontinuities in program implementation. We exploit this in a quasi-experimental difference-in-difference approach, enabling a systematic pre/post comparison of house prices in treatment and control areas. We find that in two target areas there is a significant rise in housing prices, while in one target area there is no significant effect. Finally, one area experiences significant negative effects. Hence, the results are mixed which is not inconsistent with the existing literature. The estimated coefficients are remarkably stable across different model specifications, and the spatial error model also produces similar results. Moreover, the empirical findings of the paper are subject to several robustness checks, which mainly support our conclusions. [ABSTRACT FROM AUTHOR]

This paper generalizes the simple two-city work-from-home model of Brueckner et al. (2022) by adding a group of non-remote workers, who must live in the city where they work. The results show that the main qualitative conclusions of BKL regarding the intercity effects of WFH are unaffected by this modification, with WFH yielding the same aggregate population and employment changes in the two cities and the same house-price and wage effects as in the simpler model. Even though the aggregate population effects are the same, the population relocation of non-remote workers is in the opposite direction to that of remote workers, which matches the direction in BKL. These conclusions are useful because they establish the robustness of BKL's highly parsimonious model. The paper also contains material surveying other theoretical research on WFH as well as empirical work in the area, including BKL's empirical findings in support of their model. • Generalizes the model of Brueckner et al. (2022) to include non-remote workers. • Provides material surveying other theoretical WFH research as well as empirical work. • Shows that BKL's main results are unaffected by the presence of non-remote workers. [ABSTRACT FROM AUTHOR]

Abstract This article provides the introduction to the special issue on 'Housing in Europe: a different continent – a continent of differences' in the Journal of Housing Economics in 2018. Europe is a large continent with a long and rich history, consisting of around 50 countries with vastly different institutional settings and government policies for housing and an abundance of quasi-natural experiments. Some countries have remarkably rich public data and some institutions and policy assumptions are all but the opposite of those familiar to US institutions. In this introduction we briefly outline the seven papers of this issue that exploit in one way or another this extraordinary richness for research. Each paper provides novel insights and has important implications. Collectively, they illustrate the potential opportunities for new and exciting research on housing in Europe. [ABSTRACT FROM AUTHOR]

• This paper develops a new approach to estimate the value of urban land. We extend AMM theory by adding the assumption of partial irreversibility. Bundled goods assumptions imply that land value with a structure can evolve differently than as-if vacant value, even in the first decades of structure life. • We develop a hybrid model that nests bundled goods with land residual methods and we develop a new test of predictive accuracy. • Granular house price indices produced by machine learning are used to estimate hybrid economic structure and land values. To our knowledge, this is the first time a spatially aware artificial neural network has been implemented in a real estate research paper. • We fit hybrid models to Maricopa County assessor data on houses up to 25 years old during a bust and recovery period (2007–2018). • Results support structure value that evolves at some fraction (<1.0) of property value: i.e., partial bundling. The hybrid model achieves substantially lower Coefficients of Dispersion (CODs) than the land residual method, and both methods easily beat standard AVMs that do not separate land and structure values. This paper develops a new approach to estimate the value of urban land. We extend AMM theory by adding the assumption of partial irreversibility. Bundled goods assumptions imply that land value with a structure can evolve differently than as-if vacant value, even in the first decades of structure life. We develop a hybrid model that nests bundled goods with land residual methods and we develop a new test of predictive accuracy. Granular house price indices produced by machine learning are used to estimate hybrid economic structure and land values. We fit hybrid models to Maricopa County assessor data on houses up to 25 years old during a bust and recovery period (2007–2018). Results support structure value that evolves at some fraction (<1.0) of property value: i.e., partial bundling. The hybrid model achieves substantially lower Coefficients of Dispersion (CODs) than the land residual method, and both methods easily beat standard AVMs that do not separate land and structure values. [ABSTRACT FROM AUTHOR]

This paper surveys research on homelessness. The emphases are on the last decade, rather than earlier; and the United States, rather than the rest of the world. The approach is more idiosyncratic than encyclopedic. The field has been converging on the conclusion that housing subsidies are the most attractive policy for reducing homelessness, but the optimal arrangement of subsidies is not obvious. Economists have much to contribute, in both theory—mechanism design and general equilibrium—and empirics. Aggregate-level studies can be used more for finding out what the effects of different policies are, and individual-level studies can be used more for assessing the costs and benefits of those effects. [ABSTRACT FROM AUTHOR]

This paper contributes to the international policy debate on the effect of macroprudential policy on housing-market dynamics. We use detailed New Zealand housing market data to evaluate the effect of loan-to-value ratio (LTV) restrictions on house prices. Our identification relies on the exemption for new builds from the LTV restrictions implemented during 2013–16 by the Reserve Bank of New Zealand. The empirical findings suggest that the LTV policy is effective at reducing house price inflation by limiting the credit-fuelled housing demand channel. The magnitude and duration of the policy effect depend crucially on the rate of house price growth at the time when the policy is implemented. When house prices are increasing quickly, the effect of LTV on house prices tends to be muted and short-lived. [ABSTRACT FROM AUTHOR]

Ever since Victor Gruen opened Northland in a Detroit suburb, thousands of shopping centers and office parks have sprung up along city peripheries. While automobile travel is necessary for this transition from the monocentric to the polycentric city, car travel alone, so this paper argues, is not sufficient. Instead, the decentralization of shops and jobs (two important "urban functions") hinges on the initial spatial distribution of the urban electorate, as embodied by the original city's shape ("urban form"). The electorate is more likely to tilt in favor of decentralization the less skewed is original city shape. Hence "function follows form". Given that "form follows function" eventually, too, cities either remain centralized and skewed in the long run, or shed all three: central jobs, central shops, and skew. We turn to a sample of U.S. metropolitan areas to illustrate these ideas. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of the ownership decision in the short-term and the long-term on subjective well-being. In the short-term, the subjective well-being score increases by about one point (on an eleven-point scale) on average, indicating the positive effects of ownership and confirming previous research. The long-term ownership effects, however, are considerably smaller, and owners perceive their subjective well-being to be about 0.7 points higher than before they bought their home. The results provide an explanation for this difference: individuals tend to adapt to their new housing situations after they have bought a home. The size of these ownership effects varies across different groups. [ABSTRACT FROM AUTHOR]

Abstract The developing technology of wavelet analysis offers a valuable tool in mitigating many of the limitations of earlier studies of housing price dynamics. This paper applies wavelet analysis to five first-tier cities in China to study housing price changes over time, to decompose housing prices into their trend and cycle components, and to explore co-movement and lead-lag relationships among these cities. We find the average cycle for all five cities to be 3.25 years, which is much shorter than the housing cycles observed in the United States. When we examine the cyclical lead-lag relationships among these cities, we find that during the 2008–2011 period, Shenzhen led Beijing, which led Guangzhou, which led Shanghai, and finally Tianjin followed. However, during the 2011–2014 period, the lead-lag relationships changed to Tianjin leading Shenzhen, then Shanghai, then Beijing, and finally Guangzhou. Although we generally observe a strong co-movement among the city pairs, the co-movement between Tianjin and each of the remaining four cities is weak. The weaker correlation between Tianjin and other cities indicates that real estate investors in these other four cities can improve their risk-return performance by adding Tianjin properties to their portfolios. [ABSTRACT FROM AUTHOR]

Abstract One of the major concerns with public education in the U.S. is that black and Hispanic students are concentrated in low performing schools where most of the students come from poor families. Underlying this concern is evidence showing that minorities perform better on standardized exams if they attend non-poor schools. One strategy to deconcentrate minorities within poor or low performing schools is to open up affordable housing opportunities within better school attendance zones (SAZs). In this paper I examine the efficacy of this approach using data on Florida elementary schools. I find that shifts in the proportion of a school district's affordable units in favor of better SAZs decrease the concentration of both black and Hispanic students in bad schools. However, different types of affordable units matter depending on the race of students and the definition of what constitutes a good school. [ABSTRACT FROM AUTHOR]

Abstract The housing choice voucher program aims to reduce housing cost burdens as well as to enable recipients to move to a broader diversity of neighborhoods. Prior evidence shows voucher recipients still end up in neighborhoods with relatively high poverty rates and low performing schools. These constrained neighborhood choices can in part be attributed to landlord discrimination and the geographic concentration of units that rent below voucher caps. In this paper, we consider an additional explanation: the role of information and social influence in determining the effective set of potential housing choices. Using a strategy based on proximity of households in origin census tracts, we find evidence consistent with social influence effects being present in the neighborhood choices of voucher holders. Pairs of households living within the same or adjacent buildings are significantly more likely to relocate to the same neighborhood as each other than are more distant households within the same origin neighborhood. Further, we show that voucher holders who move to the same neighborhood as a nearby voucher holder end up on average in neighborhoods that have higher poverty rates, lower levels of labor market engagement, and higher exposure to environmental hazards—in both absolute terms and relative to other voucher holders from their same origin tract. [ABSTRACT FROM AUTHOR]

Abstract Listing a house for sale has been referred to as the most agonizing and stressful decision associated with selling one's home. This may seem particularly true for homeowners expecting to sell for less than their original purchase price. In this paper, we investigate whether listing strategies among homeowners who face potential loss differ from those who do not. We use MLS data from the Randstad area of the Netherlands for the period 2008–2013 for which we have detailed information regarding the listing strategies. We find that those homeowners who expect loss set higher initial list price by 10% on average than those homeowners who do not. Sellers with prospective loss upon initial listing are more likely and more aggressively to revise their list price downward than other sellers. [ABSTRACT FROM AUTHOR]

Summary This paper analyzes the impact of the sale of rental housing in Amsterdam on the local housing market. This increases the supply of owner-occupied housing, but can also contribute to gentrification associated with the inflow of different household groups. Earlier literature focused on the former effect and reported a negative price effect. We take a fresh look at the issue by considering the sale of private as well as social rental housing, allow for differing time trends within the municipality, controlling for area fixed effects, distinguishing between short and long-term impacts and addressing endogeneity of the sale of rental housing. The main finding is a robust gentrifying effect of the sale of private rental housing in the core area of Amsterdam. [ABSTRACT FROM AUTHOR]

Abstract The Great Recession starting in 2007 has refocused attention on the importance of understanding housing market dynamics as contributors to macroeconomic fluctuations. While the sale-to-rent ratio of housing prices is generally regarded as a fundamental barometer of housing market health, the study of its determinants remains in its infancy. This paper examines the housing price ratio in Ireland since 2000, a period including an extreme housing market cycle. Using new data on first-time buyer loan-to-value ratios, a one-step error correction model of the housing price ratio in Ireland is presented for the first time. It finds clear evidence that, alongside user cost, credit conditions were central in determining equilibrium in the housing market. Throughout, and especially earlier in the sample, there is rapid adjustment of the housing price ratio to its implied equilibrium relation. There is evidence that the housing market regime changed during the period, in 2010 and again in 2014/2015. The preferred specifications imply that a ten percentage point increase in the median first-time buyer loan-to-value was associated with a 9% rise in sale prices, holding other factors – including rental prices and the system wide ratio of credit to deposits – constant. In addition to an understanding of the Irish market, the findings contribute to the evidence base for macroprudential policies that focus on mortgage lending and also hint at how housing market history may differ across rising and falling markets in forming expectations of capital gains. [ABSTRACT FROM AUTHOR]

Abstract This paper analyzes the relative merits of large place- and tenant-based housing programs in Finland in terms of housing affordability and neighborhood quality. Using hedonic regression methods and household micro data, we find that the rent savings to public housing tenants are considerable and comparable in size to the housing allowance. Furthermore, this public housing subsidy is less targeted towards low-income households than the housing allowance. At the same time, low-income public housing tenants live in poorer, less educated and lower quality neighborhoods than similar low-income households living in private rental housing. This suggests that place-based programs may lead to more segregation than tenant- based alternatives even when neighborhood mixing is an explicit aim of the program, as is the case in Finland. [ABSTRACT FROM AUTHOR]

China's urban housing price has dramatically increased in the past decade, surpassing income growth and raising fears of a real estate bubble. The increase in housing price is also accompanied by a growing number of vacant apartments. This paper argues that income inequality is one important factor driving up both the housing price relative to income and the housing vacancy rate. Using data from China's Urban Household Survey, the paper empirically examines the effects of income inequality on the housing price-to-income ratio and housing vacancy rate within each city. We find that the income GINI coefficient is positively related to the housing price-to-income ratio as well as the housing vacancy rate. In particular, a one percentage higher GINI coefficient is associated with increases in the housing price-to-income ratio and housing vacancy rate of 0.026 points and 0.166 percentage points, respectively. During 2002 and 2009, approximately 6% of the increase in the housing price-to-income ratio and 10% of the increase in the housing vacancy rate can be attributed to the increase of the GINI coefficient. Further studies show that the development of the capital market and housing rental market are somewhat helpful in mitigating the associations between income inequality and the housing price-to-income ratio and vacancy rate. [ABSTRACT FROM AUTHOR]

This paper examines why and how public housing provision may affect the supply of market-based housing in urban China. We illustrate how both the demand mechanism and the cost mechanism may lead to the crowding-out effect of public housing provision on market housing provision in post-reform urban China. Based on panels of both provincial-level and city-level data for the period of 1999–2010, our empirical results shows that: (1) the supply of public housing has crowding-out effect on the supply of market housing in China but its degree is generally moderate; (2) the crowding-out effect varies substantially under different scenarios; (3) the crowding effect changes over time but its estimation accuracy is gradually improving in the sample period. The findings in this paper have useful implications to the design of public housing programs in general. [ABSTRACT FROM AUTHOR]

This paper examines the impact of consumers’ creditworthiness, loan terms, loan amount, loan-to-value ratio, and loan purpose on mortgage pricing while controlling for market condition, macroeconomic performance, and loan sources. Applying quantile regression methods based on a lender-provided dataset covering the period of 2002–2007, this paper is able to differentiate these effects with respect to distribution of mortgage pricing. The regression results indicate that loan applicants with higher levels of creditworthiness in terms of credit score receive a lower mortgage premium above default and interest rate risk. For every 10 point increases in credit scores, the mortgage premium above default and interest rate risk declines consistently from by 1 basis point at the 10th quantile to 5 basis points at the 90th quantile. Loan applicants receive discounts ranging from 24 to 117 basis points, 22 to 115 basis points, 13 to 87 basis points for mortgage loans with LTV ratio below 60percent, between 60 and 70 percent, and between 70 percent and 80 percent, respectively. [ABSTRACT FROM AUTHOR]

This paper examines the causal effects of political uncertainty on housing markets. We used US gubernatorial elections from 1982 to 2018 as a source of exogenous variation in political uncertainty and exploited the regional variations in residential housing markets. We used neighboring states without elections and counties at the state borders without elections as control groups. We found that higher political uncertainty causes (a) a decrease in house price growth; (b) a decrease in the number of housing transactions; and (c) an increase in the number of building permits. These effects are stronger during election years when election outcomes present higher uncertainty. We further examined the impact of political uncertainty on mortgage markets and found that mortgage demand and supply decrease in election years. [ABSTRACT FROM AUTHOR]

This paper provides new evidence on the incidence and theoretical predictions of housing allowances. It offers a comprehensive reexamination of allowance algorithms, to shed light on their objectives and impacts, while also addressing empirical modelling considerations and identifying limitations in literature. Notably, it offers readers a comparative analysis by investigating US vouchers as a reference point. Theoretically, I find housing allowances are typically neither a price nor income equivalent. Housing allowance schemes,mostly being universal in functional form across countries, manifest as personal subsidies inverse to resources i.e., some benefit amount minus income deduction. I discover that New Zealand's Accommodation Supplement (AS) manifests as a negative income and wealth tax benefit which, over time, is regressive to rents and incomes. Empirically, I estimate the effects of an increase in costs and demand for the AS on rents exploiting a panel of housing markets geocoded using census tracts at Area Unit (AU) level. The rent model extends, using Geographically Weighted Panel Regression (GWR) to control for any time-variant neighborhood spillover effects on rents. Costing NZ$ 5.225 billion over 2006–2013, AS for renters was not demand deterministic and had no significant direct impact on the revenues of low-income landlords. An increase in subsidy demand coincides with possible overcrowding whereas has no impact on increasing rental supply or a move into renting. [ABSTRACT FROM AUTHOR]

Uninformed buyers may pay more when purchasing complex assets, such as houses. This paper compares local house buyers who are later foreclosed with those not foreclosed for various buyer-types, namely, owner-occupier households, investor-companies, second-home buyers, and small-scale investors. Data from one of the foreclosure epicenters, Orange County, Florida, reveal that subsequent foreclosures are associated with higher prices for comparable housing at the time of purchase. The premium paid by buyers between 2000 and 2007 who experience foreclosure after 2007 is larger closer to the 2007 market peak, approaching 3 percent. We find considerable heterogeneity across buyer-types. In particular, foreclosed second-home buyers and small-scale investors systematically pay more, while investor-companies and owner-occupiers do not. The pattern is consistent with the hypothesis that the premium paid by foreclosed households reflects poor information or limited financial acumen. • This paper compares buyers who are later foreclosed with those not foreclosed. • Buyer include investor-companies, owner-occupiers, second-home buyers, and small-scale investors. • Data cover one of the foreclosure epicenters, Orange County, Florida. • We find that buyers who experience foreclosure after 2007 pay more for comparable housing. • We find considerable heterogeneity across buyer-types. [ABSTRACT FROM AUTHOR]

This paper presents a simple model of the rental and homeownership markets in a unified framework. The paper then investigates the model’s positive and normative properties, applying ideas developed in search and matching theory. I analytically address the comparative static and welfare implications of the model. In addition, as an extension toward realism, I consider a version of the model with free entry of housing supply, while the benchmark model assumes exogenous housing supply. To examine the benchmark model’s dynamics, I generate the impulse responses of house prices, rents, and housing occupancy patterns to an increase in housing supply and show that house prices react more than rents in the short run. [ABSTRACT FROM AUTHOR]

This paper investigates how the demand for residential real estate depends on age and other demographic characteristics at the household level. Based on a detailed cross-sectional survey of English households, it finds that housing demand is significantly determined by a household’s human capital, and that housing demand generally increases with age. After retirement it declines, but only to a small extent. High education levels, good health, and high income will increase a household’s demand for housing even when households age. These results are relevant for countries that experience population shrinkage, but where total housing demand could still grow in the future despite stagnating household numbers and aging populations. The paper further shows that changes in demographics lead to very heterogeneous demand responses for different housing attributes, providing information regarding the future qualitative demand for housing. [ABSTRACT FROM AUTHOR]

This paper describes the production of a panel of price indices for housing services, other produced goods and services, and all produced goods and services for each metropolitan area in the United States and the non-metropolitan part of each state for each year from 1982 through 2012. Our general approach is to first produce interarea price indices for a single year 2000 and then use BLS time-series price indices to create the panel. Our geographic housing price index for 2000 is based on a large data set with detailed information about the characteristics of rented dwelling units and their neighborhoods throughout the United States that enables us to overcome many shortcomings of existing interarea housing price indices. For most areas, our price index for all goods other than housing is calculated from the price indices for categories of nonhousing goods produced each quarter by the Council for Community and Economic Research, formerly the American Chambers of Commerce Researchers Association. In order to produce a nonhousing price index for areas of the United States not covered by their index, we estimate a theoretically-based regression model explaining differences in the composite price index for nonhousing goods for areas where it is available and use it to predict a price index for these goods for the uncovered areas. The overall consumer price index for all areas is based on the preceding estimates of the price of housing and other goods. Electronic versions of the price indices are available online. The paper and its online appendices report many sensitivity analyses, and the paper compares the new housing price index with the most widely used indices of differences in the rents of identical units across areas. [ABSTRACT FROM AUTHOR]

This paper examines how various demographic and economic factors impact household formation both within and across cohorts. The results show substantial differences in the share of young adults living with their parents over time. Differences in demographics, housing costs, and business-cycle conditions can explain as much as 70 percent of the difference in household-formation rates across cohorts, a result driven in large part by increased sensitivity of young adults’ household-formation decisions to economic conditions. Changes in parenting styles and shifting social norms likely also play roles. [ABSTRACT FROM AUTHOR]

This paper revisits the interactions between housing dynamics and the business cycle in a two-sector model developed and calibrated from the multi-sector neoclassical growth model originally envisioned by Davis and Heathcote in 2005. A two-sector model with housing sector specific capital and productivity shocks can successfully predict a correct positive correlation between housing prices and residential investment. The model can also replicate the fact observed in the United States that housing prices are more volatile than output. [ABSTRACT FROM AUTHOR]

The average real house price in Beijing rose by roughly 41.8% between 2012 and 2015, and the appreciation differs across low- versus high-priced homes. The rising house price might be caused by changes in the characteristics of housing units, and it might also be induced by the changing returns to housing characteristics in the underlying hedonic price functions. In this paper, we use a comprehensive housing transaction dataset and analyze the changes in the distribution of house prices over time through a decomposition approach. The result of Oaxaca-Blinder mean decomposition suggests that the proportion of the price gap between 2012 and 2015 due to altered returns over time is greater than the proportion caused by changes in housing characteristics. The quantile decomposition shows that the decomposition effects are heterogenous across the complete distribution of house prices. We also find that low-priced homeowners are exposed to a decline in house prices, while there are deteriorating housing conditions from 2012 to 2015. The high-priced homeowners experience an improvement in living conditions, but a rise in house prices. [ABSTRACT FROM AUTHOR]

This paper provides evidence that economic self-interest associated with homeownership affects voter turnout in local elections in the United States. Compared to renters, homeowners are financially invested in their communities and are less mobile. Therefore, homeowners should care more about local policies and have incentives to engage actively in local politics. The disparity in political participation between homeowners and renters, however, should diminish in presidential elections for which policy discussions are more targeted at the national-level. These hypotheses are tested using census block group-level election panel data. Fixed effects models and a control function approach are used to identify the effect of homeownership on voter turnout in off-year mayoral elections relative to presidential elections. Results show that mayoral election voter turnout increases with the local homeownership rate. This suggests that local policies may tend to cater to the tastes of homeowners over renters. [ABSTRACT FROM AUTHOR]

The two primary approaches to estimate marginal willingness-to-pay (MWTP) are hedonic (Rosen, 1974) and discrete choice (McFadden, 1974). While both approaches rely on revealed preference methods to estimate MWTP, the primitives underlying both models are different, making it difficult to compare them. This paper establishes the assumptions needed to develop a tractable framework to compare both approaches. I begin with a discrete choice model and show how to derive the gradient of the equilibrium price function implicitly. I then incorporate Rosen’s insight that the price gradient is equal to the MWTP of the marginal individual whose indifference curve is tangent to the price function in equilibrium. However, with discrete choices, some individuals may be inframarginal and their indifference curves will not be tangent to the price function. The analytical mapping I derive formalizes this intuition and shows that the price gradient depends on weighted averages of marginal utilities where higher weights are assigned to individuals whose choice probabilities indicate more uncertain choices ( marginal individuals). As this choice becomes more certain, the weights start to decrease. This result shows how choice probabilities and other moments of choice data can be used to distinguish marginal versus inframarginal individuals. [ABSTRACT FROM AUTHOR]

Peer to Peer e-commerce is increasingly characterized by trends towards the personalization of buyers and sellers in the on-line marketplace. This personalization includes buyer reviews, personal pictures and profiles, and other biographical information intended to reduce buyers’ perceived “purchase risk” or to facilitate trust in the sellers. However, this phenomenon is transforming what started as an essentially “anonymous” market to one susceptible to traditional market failures, including potential racial discrimination, in a manner similar to its brick and mortar counterparts. In this paper, we examine the effect of on-line host information (race, gender, sexual orientation, etc.) on the price of available rental listings in San Francisco on Airbnb.com. We find that on average, Asian and Hispanic hosts charge 8%-10% lower prices relative to their White counterparts on equivalent rental properties, after controlling for all renter-available information on rental unit characteristics, as well as additional information on neighborhood property values, area demographics, and occupancy rates. We do not find any differences in occupancy rates between minority and White hosts. This may suggest that minorities price lower because they are forward-looking, perhaps due to an expectation of discrimination in the online marketplace or have a preference to increase demand to either maintain their target occupancy level or to attract a larger pool of potential renters to choose from. Overall, our findings are consistent with but not conclusive of a market test of potential racial discrimination affecting Hispanic Airbnb hosts, manifested in an anticipation of disparate market demand for their rentals, and responded to by lower listing prices. [ABSTRACT FROM AUTHOR]