Untangling Housing Cost and Transportation Interactions: The Location Affordability Index Model—Version 2 (LAIM2)

Haas, P.; Newmark, Gregory L.; Morrison, Thomas L.

doi:10.1080/10511482.2016.1158199

Cited by 34 publications

(28 citation statements)

References 4 publications

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“…Finally, several scholars who have used the LAI in research note concern regarding the margin of error (MOE) in American Community Survey (ACS) data, especially at the block group level (AcevedoGarcia et al, 2016;Haas, Newmark, & Morrison, 2016;Tighe & Ganning, 2016;Walter & Wang, 2016). With the exception of Haas et al (2016), external review of the LAI on the grounds of statistical reliability or validity has gone no further than this.…”

Section: Background and Reviewmentioning

confidence: 99%

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It’s Good but Is It Right? An Under-the-Hood View of the Location Affordability Index

Ganning

2017

Housing Policy Debate

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In 2012, the U.S. Department of Housing and Urban Development (HUD) released the Location Affordability Index (LAI) as an online portal and downloadable data set. The LAI has elevated the U.S. conversation on affordability to include transportation and access to opportunities, and has been used in state and federal programming, by researchers, and by private households. However, although some researchers have noted concerns with and potential limitations of the data, none has provided practitioners and researchers with an under-the-hood view of the data, analysis of its reliability or validity, or its conceptual limitations. This article recommends methodological improvements dealing with issues of variable construction, aggregation, and modeling. A recreation of the LAI at the census-tract level suggests the LAI overestimates both costs and cost burden, but especially among renters, and especially in metropolitan areas. On the transportation side, model recreation requires partnership and resourcing to both gain access to restricted data and to develop a reliable database on transit supply and use.In 2012, the U.S. Department of Housing and Urban Development (HUD) released the Location Affordability Index (LAI) as an online portal and downloadable data set. HUD adopted and revised the LAI from its origin as the Center for Neighborhood Technology's Housing and Transportation (H+T) Affordability Index. This database seeks to inform households and public agencies of the costs of living in various places, changing the discussion about affordability from one focused solely on housing to one inclusive of transportation costs. Numerous scholars have analyzed the LAI estimates, resulting in a special issue of Housing Policy Debate as well as other publications. These publications have addressed housing subsidies, mortgage risk, and racial disparities in costs, among other things. However, these publications have not provided practitioners and researchers with an under-the-hood view of the data, analysis of its reliability or validity, or its conceptual limitations. As this article shows, some elements of the LAI introduce either considerable error or the potential for considerable error. Many of those issues, based in variable construction, aggregation, and modeling decisions, can be fixed. Others-notably, data on transit use-are more problematic. If left unchecked, such error could misinform decisions regarding household location or public policy issues in housing or transportation-potentially costing private households or public agencies considerably. This article uses data from across the state of Ohio, intending it as an illustrative case study of the national implications of the conceptual and technical bounds of the LAI. ARTICLE HISTORY

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Section: Background and Reviewmentioning

confidence: 99%

“…With the exception of Haas et al (2016), external review of the LAI on the grounds of statistical reliability or validity has gone no further than this. As this article shows, although MOE does present a considerable challenge for the LAI as a whole, other considerations warrant discussion as well.…”

Section: Background and Reviewmentioning

confidence: 99%

It’s Good but Is It Right? An Under-the-Hood View of the Location Affordability Index

Ganning

2017

Housing Policy Debate

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“…Finally, several scholars who have used the LAI in research note concern regarding the margin of error (MOE) in American Community Survey (ACS) data, especially at the block group level (Acevedo-Garcia et al, 2016;Haas, Newmark, & Morrison, 2016;Tighe & Ganning, 2016;Walter & Wang, 2016). With the exception of Haas et al (2016), external review of the LAI on the grounds of statistical reliability or validity has gone no further than this.…”

Section: Literature Reviewmentioning

confidence: 99%

“…With the exception of Haas et al (2016), external review of the LAI on the grounds of statistical reliability or validity has gone no further than this. As this manuscript shows, though MOE does present a considerable challenge for the LAI as a whole, other considerations warrant discussion as well.…”

Section: Literature Reviewmentioning

confidence: 99%

What Do We Know About Location Affordability in U.S. Shrinking Cities?

Ganning¹,

Tighe²

2017

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In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing and transportation at the block group level, and calculates "H + T Affordability," the percent of household income spent on these items. In our previous research, we analyzed 81 shrinking cities to determine how location affordability differs across various neighborhoods. Our results suggest that households in declining neighborhoods, as compared to stable or redeveloping neighborhoods, face the greatest H + T affordability challenges in shrinking cities. Furthermore, in declining neighborhoods, virtually all of the additional affordability challenges encountered can be accounted for by differences in transportation affordability rather than housing. Since there is virtually no research to either validate or suggest bias in the LAI data, and a declining neighborhood in a shrinking city presents both a relatively common yet entirely dissimilar context to the norm, we feel that this data should be carefully calibrated to, and tested for, this setting to ensure that appropriate and efficient policy follow.In this report, we present the results of two research phases: a strictly quantitative first stage in which the LAI is disassembled and reassembled, taking stock of assumptions, methods, and accuracy. This work finds that the LAI generally over-estimates housing costs, but more for renters and more in metropolitan areas. Estimations of transportation cost burdens are built largely from unreliable data and using models which cannot be replicated, leading us to conclude that these cost burden estimates may not be reliable. In the second research phase, which is survey-based, we gather household-level data from 12 Census tracts in Cleveland, Ohio, to estimate household housing and transportation costs and cost burdens and gain a clearer sense of budget trade-offs where costs are unaffordable. The survey results support the first research stage. The LAI over-estimates housing costs for these neighborhoods by approximately 17% and transportation costs by approximately 126%, meaning the LAI estimates for transportation are not reliable. By and large, households trade essentials, investing, and paying bills (at all or in full) to cover their costs in housing and transportation.17.

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“…Adding up all the variables will then give the mean transportation expenditure. The method to compute a simplified location housing affordability as refer to Haas et al (2016) is as per equation below:…”

Section: Subang Bestari Putra Heightmentioning

confidence: 99%

Locatıon Housıng Affordabılıty as an Indıcator for Qualıty of Lıfe in Malaysıa

Hassan

Hamdan

Abdullah

et al. 2017

E-BPJ

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To have a quality of life is the ability to own a house. Housing affordability affects the quality of life concerning household well-being and economic security. The research sets to evaluate the location housing affordability for the low-income group base on housing and transportation expenditures in urban areas. 148 respondents have interviewed and by using an integrated Location Housing Affordability, it had indicated that location does influence housing affordability. The findings showed the urban area for the low-income group is seriously unaffordable. -Location" should be part of affordable housing because it affects housing affordability thus concerning the quality of life.

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Untangling Housing Cost and Transportation Interactions: The Location Affordability Index Model—Version 2 (LAIM2)

Cited by 34 publications

References 4 publications

It’s Good but Is It Right? An Under-the-Hood View of the Location Affordability Index

It’s Good but Is It Right? An Under-the-Hood View of the Location Affordability Index

What Do We Know About Location Affordability in U.S. Shrinking Cities?

Locatıon Housıng Affordabılıty as an Indıcator for Qualıty of Lıfe in Malaysıa

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