Bourassa, Steven C.; Hoesli, Martin. (2022). Hedonic, Residual, and Matching Methods for Residential Land Valuation. Journal Of Housing Economics, 58.
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Abstract
• Our first method involves a hedonic model estimated for sales of vacant lots. • Another method depreciates improvements, obtaining land value as a residual. • Our third approach matches the sales of vacant and subsequently developed lots. • This allows us to estimate a hedonic model of land leverage (the ratio of land to total property value) for improved properties. • We conclude that the third approach is the most promising of the three methods. Accurate estimates of land values on a property-by-property basis are an important requirement for the effective implementation of land-based property taxes. We compare hedonic, residual, and matching techniques for mass appraisal of residential land values, using data from Maricopa County, Arizona. The first method involves a hedonic valuation model estimated for transactions of vacant lots. The second approach subtracts the depreciated cost of improvements from the value of improved properties to obtain land value as a residual. The third approach matches the sales of vacant lots with subsequent sales of the same properties once they have been developed. For each pair, we use a land price index to inflate the land price to the time of the improved property transaction and then calculate land leverage (the ratio of land to total property value). A hedonic model is estimated and used to predict land leverage for all improved properties. We conclude that the matching approach is the most promising of the methods considered. [ABSTRACT FROM AUTHOR]; Copyright of Journal of Housing Economics is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Keywords
Hedonic Method; Land Leverage; Land Valuation; Matching Approach; Residual Approach
Acolin, Arthur; Reina, Vincent. (2022). Housing Cost Burden and Life Satisfaction. Journal Of Housing & The Built Environment, 37(4), 1789-1815.
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Abstract
The share of income that households spent on their housing has been increasing over time in a wide range of countries, particularly among lower income households. In theory, the share of income spent on housing can reflect variations in household preferences for housing consumption but for low-income household, high burdens are likely more reflective of constraints and force these households to face tradeoffs between housing and non-housing consumption that negatively affect their overall life satisfaction. This paper uses data from the 2018 European Union Statistics on Income and Living Conditions (EU-SILC) for 14 countries. We find that, controlling for household sociodemographic characteristics, households spending more than 30 percent of their income and those spending more than 50 percent of their income on housing report significantly lower levels of life satisfaction. The estimated relationship is largest for this latter heavily cost burdened group. The negative relationship between housing cost burden and reported life satisfaction is found across countries but varies in magnitude, suggesting that stronger welfare systems may mediate the negative impacts of housing cost burdens, although further research is needed to confirm both this relationship and the precise mechanisms driving it.
Keywords
Life Satisfaction; Income; Housing; Poor Communities; Subjective Well-being (psychology); Living Conditions; European Countries; Housing Cost; Subjective Wellbeing; Economic Hardship; Homeownership; Affordability; Determinants; Cost Analysis; Housing Costs; Households; Consumption; Low Income Groups; Expenditures; Welfare; Sociodemographics
Acolin, Arthur;hoek-smit, Marja;green, Richard K. (2022). Measuring the Housing Sector’s Contribution to GDP in Emerging Market Countries. International Journal Of Housing Markets And Analysis, 15(5), 977-994.
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Abstract
Purpose > This paper aims to document the economic importance of the housing sector, as measured by its contribution to gross domestic product (GDP), which is not fully recognized. In response to the joint economic and health crises caused by the COVID-19 pandemic, there is an opportunity for emerging market countries to develop and implement inclusive housing strategies that stimulate the economy and improve community health outcomes. However, so far housing does not feature prominently in the recovery plans of many emerging market countries. Design/methodology/approach > This paper uses national account data and informal housing estimates for 11 emerging market economies to estimate the contribution of housing investments and housing services to the GDP of these countries. Findings > This paper finds that the combined contribution of housing investments and housing services represents between 6.9% and 18.5% of GDP, averaging 13.1% in the countries with information about both. This puts the housing sector roughly on par with other key sectors such as manufacturing. In addition, if the informal housing sector is undercounted in the official national account figures used in this analysis by 50% or 100%, for example, then the true averages of housing investments and housing services’ contribution to GDP would increase to 14.3% or 16.1% of GDP, respectively. Research limitations/implications > Further efforts to improve data collection about housing investments and consumption, particularly imputed rent for owner occupiers and informal activity require national government to conduct regular household and housing surveys. Researcher can help make these surveys more robust and leverage new data sources such as scraped housing price and rent data to complement traditional surveys. Better data are needed in order to capture housing contribution to the economy. Practical implications > The size of the housing sector and its impact in terms of employment and community resilience indicate the potential of inclusive housing investments to both serve short-term economic stimulus and increase long-term community resilience. Originality/value > The role of housing in the economy is often limited to housing investment, despite the importance of housing services and well-documented methodologies to include them. This analysis highlights the importance of housing to the economy of emerging market countries (in addition to all the non-GDP related impact of housing on welfare) and indicate data limitation that need to be addressed to further strengthen the case for focusing on housing as part of economic recovery plans.
Keywords
Pandemics; Economic Importance; Investments; Housing; Sanitation; Recovery; International Organizations; Covid-19; Economic Growth; Data Collection; Economic Indicators; Economics; Housing Conditions; Economic Policy; Economic Conditions; Market Economies; Resilience; Low Income Groups; Economic Activity; Consumption; Emerging Markets; Earthquakes; Surveys; Gross Domestic Product--gdp; Coronaviruses; Affordable Housing; Economic Development; Informal Economy; Households; Recovery Plans; Disease Transmission; Africa; South Africa; India
Ruoniu (Vince) Wang is an Assistant Professor in the Runstad Department of Real Estate in the College of Built Environments at the University of Washington. He studies spatial justice and inclusive communities, including their impacts reflected in the built environment, human behaviors, and policy interventions. Vince joined the University of Washington after serving six years as the research manager and director in a national non-profit organization Grounded Solutions Network. He has designed and conducted a U.S. Census of inclusionary housing policies, a U.S. census of community land trusts, and a national performance evaluation of shared equity homeownership programs. His research expands to policy evaluation for the two largest federal assisted housing rental programs in the U.S.: the Low-Income Housing Tax Credit program and the Housing Choice Voucher program. Vince grounds his research with applied tools to democratize data for low-income communities.
The College of Built Environments launched a funding opportunity for those whose research has been affected by the ongoing pandemic. The Research Restart Fund, with awards up to $5,000, has awarded 4 grants in its first of two cycles. A grant was awarded to Real Estate faculty member Arthur Acolin, who is partnering with the City of Seattle’s Office of Planning and Community Development to understand barriers that homeowners, particularly those with lower incomes, face to building Accessory Dwelling Units…
El-Anwar, Omar; El-Rayes, Khaled; Elnashai, Amr. (2010). Maximizing Temporary Housing Safety after Natural Disasters. Journal Of Infrastructure Systems, 16(2), 138 – 148.
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Abstract
In the aftermath of large-scale natural disasters, emergency management organizations are expected to provide safe temporary housing for a large number of displaced families and to ensure that these housing arrangements are not located in hazardous areas. Potential postdisaster hazards can take many forms such as earthquake aftershocks, landslides, postearthquake soil liquefaction, flooding, hazardous material releases, etc. This paper presents the development of a multiobjective optimization methodology to support decision-makers in emergency management organizations in optimizing postdisaster temporary housing arrangements. The developed methodology incorporates (1) a safety model to measure and quantify temporary housing safety in the presence of multiple potential postdisaster hazards; (2) a cost model to minimize total public expenditures on temporary housing; and (3) a multiobjective optimization model to simultaneously maximize temporary housing safety and minimize public expenditures on temporary housing. An application to a large region is presented to illustrate the use of the models and demonstrate their capabilities in optimizing postdisaster temporary housing arrangements.
Keywords
Earthquake; Landslides; Optimization; Temporary Housing; Postdisaster Hazards; Housing Safety; Postdisaster Recovery
Hong, Jinhyun; Shen, Qing. (2013). Residential Density and Transportation Emissions: Examining the Connection by Addressing Spatial Autocorrelation and Self-Selection. Transportation Research Part D-transport And Environment, 22, 75 – 79.
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Abstract
This paper examines the effect of residential density on CO2 equivalent from automobile using more specific emission factors based on vehicle and trip characteristics, and by addressing problems of spatial autocorrelation and self-selection. Drawing on the 2006 Puget Sound Regional Council Household Activity Survey data, the 2005 parcel and building database, the 2000 US Census data, and emission factors estimated using the Motor Vehicle Emission Simulator, we analyze the influence of residential density on road-based transportation emissions. In addition, a Bayesian multilevel model with spatial random effects and instrumental variables is employed to control for spatial autocorrelation and self-selection. The results indicate that the effect of residential density on transportation emissions is influenced by spatial correlation and self-selection. Our results still show, however, that increasing residential density leads to a significant reduction in transportation emissions. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords
Urban Form; Travel; Transportation Emissions; Residential Density; Confounding By Location; Self-selection
Acolin, Arthur. (2019). Housing Trajectories of Immigrants and Their Children in France: Between Integration and Stratification. Urban Studies (sage Publications, Ltd.), 56(10), 2021 – 2039.
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Abstract
Immigrants have been found to exhibit different housing tenure patterns from the rest of the population in a number of contexts. This article tests whether observed differences in tenure in France can be explained by differences in socio-demographic characteristics or whether unexplained differences might result from housing market mechanisms that affect immigrants differentially from the rest of the population, and extends this to the second generation. The article relies on data from TeO, a survey of 21,761 persons designed to oversample and identify immigrants and their children, providing information about the outcomes of children of immigrants that is otherwise lacking in French statistics. The results indicate that while immigrants are significantly less likely to be homeowners, even after controlling for compositional difference, the gap in homeownership between the second generation and the rest of the population is smaller and not statistically significant. This suggests a progressive integration in the housing market over time and over generations rather than overall stratified housing trajectories. Differences in terms of the share of social housing residents, the level of residential crowding, and housing and neighbourhood characteristics also decline across generations. However, children of immigrants from some non-European origins are experiencing higher levels of stratification than other groups, with continued significant differences in tenure.
Keywords
Immigrants; Housing; Home Ownership; Children Of Immigrants; Housing Market; Social Stratification; France; Homeownership; Housing Trajectories; Tenure; Segmented Assimilation; Location Choices; Wealth; 2nd-generation; Discrimination; Segregation; Inequality; Quality; Markets; Demographics; Homeowners; Neighborhoods; Crowding; Statistical Analysis; Residential Patterns; Children; Trajectories; Residents; Residential Areas; Integration; Statistics; European Cultural Groups; Sociodemographics; Stratification; Demographic Aspects; Second Generation; Property; Public Housing; Noncitizens
Hess, Chris; Colburn, Gregg; Crowder, Kyle; Allen, Ryan. (2020). Racial Disparity in Exposure to Housing Cost Burden in the United States: 1980-2017. Housing Studies.
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Abstract
This article uses the Panel Study of Income Dynamics to analyse Black-White differences in housing cost burden exposure among renter households in the USA from 1980 to 2017, expanding understanding of this phenomenon in two respects. Specifically, we document how much this racial disparity changed among renters over almost four decades and identify how much factors associated with income or housing costs explain Black-White inequality in exposure to housing cost burden. For White households, the net contribution of household, neighbourhood and metropolitan covariates accounts for much of the change in the probability of housing cost burden over time. For Black households, however, the probability of experiencing housing cost burden continued to rise throughout the period of this study, even after controlling for household, neighbourhood and metropolitan covariates. This suggests that unobserved variables like racial discrimination, social networks or employment quality might explain the increasing disparity in cost burden among for Black and White households in the USA.
Keywords
Cost Burden; Housing Cost; Racial Inequality; Income Inequality; Rent Burden; Affordability; Neighborhoods; Segregation; Dynamics; Hardship; Prices; Market; Poor
El-Anwar, Omar; El-Rayes, Khaled; Elnashai, Amr. (2010). Minimization of Socioeconomic Disruption for Displaced Populations Following Disasters. Disasters, 34(3), 865 – 883.
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Abstract
In the aftermath of catastrophic natural disasters such as hurricanes, tsunamis and earthquakes, emergency management agencies come under intense pressure to provide temporary housing to address the large-scale displacement of the vulnerable population. Temporary housing is essential to enable displaced families to reestablish their normal daily activities until permanent housing solutions can be provided. Temporary housing decisions, however, have often been criticized for their failure to fulfil the socioeconomic needs of the displaced families within acceptable budgets. This paper presents the development of (1) socioeconomic disruption metrics that are capable of quantifying the socioeconomic impacts of temporary housing decisions on displaced populations; and (2) a robust multi-objective optimization model for temporary housing that is capable of simultaneously minimizing socioeconomic disruptions and public expenditures in an effective and efficient manner. A large-scale application example is optimized to illustrate the use of the model and demonstrate its capabilities ingenerating optimal plans for realistic temporary housing problems.
Keywords
Natural Disasters; Hurricanes; Disaster Relief; Temporary Housing; Tsunamis; Multi-objective Optimization; Post-disaster Recovery; Social Welfare; Socioeconomic Disruption