ORCID Identifier(s)

ORCID 0000-0002-6197-4605

Graduation Semester and Year

Fall 2025

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Urban Planning and Public Policy

Department

Urban and Public Affairs

First Advisor

Jianling Li

Second Advisor

Qisheng Pan

Third Advisor

Jiwon Suh

Abstract

Housing affordability remains a persistent challenge in the United States, driven by rising housing costs, limited supply, income inequality, and transportation costs. Acute in the Dallas–Fort Worth (DFW) metropolitan area, where auto dependence, sprawling development, and uneven transit access intensify affordability disparities. This study examines the multidimensional drivers of housing affordability across the DFW metropolitan area using Ordinary Least Squares (OLS) regression, Random Forest modeling, and independent t-tests. The dependent variable, Owner Cost Burden (OCB), captures monthly owner costs as a percentage of household income across six domains: housing, transportation, climate and resilience, neighborhood context, demographics and geography, and transit accessibility. Results show low-income households, multi-unit housing, small households, rising housing values, households with associate-level education, households with ownership of two or more vehicles, and Asian households are consistently associated with higher OCB. In contrast, upper-income households, shorter commutes, and older populations are associated with lower OCB. Variable contribution analyses identify income categories, vehicle ownership, and housing value as the most influential predictors. The study also evaluates the Center for Neighborhood Technology’s (CNT) Housing + Transportation (H+T) Index and develops a localized, tenure-specific version for DFW. Unlike CNT’s single “Regional Typical Household,” the adapted index differentiates renters and owners with and without mortgages at the block-group level. Local estimates reveal greater spatial and tenure-based variation. CNT substantially underestimates transportation costs, particularly auto ownership and vehicle miles traveled (VMT), and masks major differences between renters and homeowners. Locally derived VMT identifies high-cost areas in outer auto-dependent communities and near major job centers, contrasting CNT’s modeled patterns. T-tests show CNT underestimates renter burden by nearly 14 percentage points and overstates costs for owners without mortgages. Overall, tenure-specific H+T estimates provide a more accurate and equitable assessment of affordability, demonstrating the need for localized, data-driven housing and transportation policy frameworks.

Keywords

Housing Affordability, Owner Cost Burden, Transportation Costs, Housing + Transportation (H+T) Index, Methodological Gaps, Random Forest Modeling, Dallas–Fort Worth Metropolitan Area, Urban–Rural Divide, Spatial Inequality

Disciplines

Human Geography | Public Administration | Public Affairs | Public Policy | Spatial Science | Transportation | Urban Studies | Urban Studies and Planning

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Available for download on Friday, December 10, 2027

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