Date of Graduation

5-2020

Document Type

Thesis

Degree Name

Bachelor of Science in Business Administration

Degree Level

Undergraduate

Department

Economics

Advisor/Mentor

Embaye, Abel

Committee Member/Reader

Farmer, Amy

Abstract

This paper explores the issue of homelessness within the United States and seeks to create an econometric model that identifies predicting factors of homelessness at a state level which can be used to estimate the size of homeless populations. The author analyzed the role of 16 factors including income inequality, minimum wage, unemployment, rental cost, poverty, education, veteran status, and substance abuse on the 2017 state homeless populations. Using an ordinary least squares regression, the model produced five significant variables: adjusted minimum wage, percent of income spent on rent, possession of health insurance, average winter temperature, and the unemployment rate. Through its assessment of economic, personal, and environmental factors, this model provides a foundational understanding of the types of variables which predict state homelessness.

Keywords

Homelessness, Econometrics

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