Essays on Housing Policy and Community Development

Doctoral Dissertation

Abstract

This dissertation contains three essays on housing policy and community development. Chapter 1 examines whether a 1992 Act that forced Fannie Mae and Freddie Mac to purchase loans from underserved populations contributed to the subprime mortgage crisis. Chapter 2 examines whether programs that provide housing assistance to homeless people can reduce chronic homelessness. Finally, chapter 3 examines whether municipal governments manipulate fiscal policy in election years. The 1992 ‘GSE Act’ mandated that a specified percentage of Fannie Mae and Freddie Mac purchases come from underserved populations. A number of prominent observers have pointed to the GSE Act as a root cause of the recent housing crisis. Chapter 1 evaluates the link between the GSE Act and relaxed mortgage market standards. Using loan application-level data from the Home Mortgage Disclosure Act, I analyze whether the GSE Act’s affordable housing goals altered mortgage lending or purchasing decisions. To identify this effect, I use a regression discontinuity design that exploits arbitrary cutoffs used to determine whether a loan satisfies the GSE Act goals. I find that the GSE Act’s affordable housing goals had little to no effect on mortgage lending or purchasing. Additionally, using census tract-level data, I find no relationship between the GSE Act’s affordable housing goals and increased foreclosures, vacancies or other housing outcomes. These results suggest that the 1992 GSE Act had a negligible effect on the recent mortgage market crisis. Chapter 2 examines whether programs that provide housing assistance to homeless people can reduce chronic homelessness. I analyze data from the Department of Housing and Urban Development for 130 communities across the U.S. over the period 2005 to 2007. Because the amount of federal money allocated to a community to combat homelessness may depend on unobserved characteristics of that community, I estimate a fixed effects model which examines the effect of new federal homeless funding on chronic homelessness. I find that increased funding for homeless programs can reduce chronic homelessness. A $1 per capita increase in federal homeless funding is associated with a 1.80 person, or 2.8%, decrease in the number of chronically homeless per 100,000 population. An analysis of new funding to specific types of homeless programs indicates that programs that provide long-term housing and services to homeless people with disabilities drives this relationship. These results indicate that the first-year cost of moving one chronically homeless person into permanent supportive housing is $55,600. Chapter 3 examines whether municipal governments manipulate fiscal policy in election years. According to the political budget cycle hypothesis, in election years government officials engage in opportunistic fiscal policy manipulation for electoral gains. This paper tests that hypothesis using data on taxes and spending for a panel of 268 US cities over the period 1970-2004. While our estimates provide no evidence of altered total expenditures or taxes in election years, we do find evidence of election-year manipulation of employment. We find a 0.7 percent increase in total municipal employment, including increases in police, education, and sanitation employment.

Attributes

Attribute NameValues
URN
  • etd-05252011-121621

Author Shawn R Moulton
Advisor William Evans
Contributor William Evans, Committee Chair
Contributor Abigail Wozniak, Committee Member
Contributor James Sullivan, Committee Member
Degree Level Doctoral Dissertation
Degree Discipline Economics
Degree Name Doctor of Philosophy
Defense Date
  • 2011-05-25

Submission Date 2011-05-25
Country
  • United States of America

Subject
  • Homelessness

  • Political Budget Cycles

  • Affordable Housing Goals

Publisher
  • University of Notre Dame

Language
  • English

Record Visibility Public
Content License
  • All rights reserved

Departments and Units

Digital Object Identifier

doi:10.7274/79407w64d8w

This DOI is the best way to cite this doctoral dissertation.

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