Event Title

Analysis of Homelessness in U.S. Cities as a Result of Policy Choices

Advisor(s)

Patrick Kearney; Illinois Mathematics and Science Academy

Discipline

Behavioral and Social Sciences

Start Date

21-4-2021 10:45 AM

End Date

21-4-2021 11:05 AM

Abstract

Cities across the United States face severe challenges in housing all of their residents. Hundreds of thousands of people face homelessness throughout the US. It is well known and understood that there are four main contributing factors to homelessness: lack of affordable housing, unemployment, poverty, and mental illness and substance abuse. While these causes are well known, solutions vary wildly across different cities. Different policies, or lack of policies, are in place in cities across the country in order to fix these causes of homelessness and raise people out of homelessness. This study investigates those different policies in order to determine which policies have the greatest effects upon homelessness within cities in the United States. To test these policies, a statistical analysis was run using the programming language R. This tested many different housing, education, mental health/substance abuse, etc. policies against homelessness in each city to determine which policies had the greatest effects on homelessness. The results show that certain policies worked to a greater effect in lowering the rate of homelessness in cities than others.

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Apr 21st, 10:45 AM Apr 21st, 11:05 AM

Analysis of Homelessness in U.S. Cities as a Result of Policy Choices

Cities across the United States face severe challenges in housing all of their residents. Hundreds of thousands of people face homelessness throughout the US. It is well known and understood that there are four main contributing factors to homelessness: lack of affordable housing, unemployment, poverty, and mental illness and substance abuse. While these causes are well known, solutions vary wildly across different cities. Different policies, or lack of policies, are in place in cities across the country in order to fix these causes of homelessness and raise people out of homelessness. This study investigates those different policies in order to determine which policies have the greatest effects upon homelessness within cities in the United States. To test these policies, a statistical analysis was run using the programming language R. This tested many different housing, education, mental health/substance abuse, etc. policies against homelessness in each city to determine which policies had the greatest effects on homelessness. The results show that certain policies worked to a greater effect in lowering the rate of homelessness in cities than others.