Year: 2024
Type: article
Abstract: The United States faces a persistent and widening affordable housing crisis marked by severe demand-supply imbalances, regional disparities, and disproportionate socio-economic burdens on low- and moderate-income households. Traditional financing mechanisms, while foundational, have proven insufficient in scale, efficiency, and adaptability to meet contemporary housing needs. This paper presents a comprehensive examination of financial modeling innovations aimed at revitalizing affordable housing development across the U.S. It begins by establishing the contextual challenges and limitations of conventional financing tools, followed by a theoretical exploration of financial innovation principles in infrastructure and real estate contexts. The paper introduces emerging financial models—including predictive analytics, public-private finance hybrids, and blockchain-enabled platforms—highlighting their potential to optimize risk-sharing, increase transparency, and scale capital flows. Through detailed case studies, the paper illustrates real-world applications and collaborative strategies that have successfully expanded affordable housing. It concludes with policy reform proposals, strategic implementation recommendations, and forward-looking research pathways, advocating for a more adaptive, inclusive, and data-driven housing finance ecosystem.
Authors: Mark Tettey Ayumu, Tochi Chimaobi Ohakawa
Institution: Johns Hopkins University
Language: English
Topic: Housing Market and Economics
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4409694976