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An Analysis Of How The Housing Market Affects Impoverished Neighborhoods

1604 words - 7 pages

I. Introduction
The housing demographics of low-income communities have large effects for residents living in those areas. The objective of this report is to shed light on how the housing market in the city of Oakland affects current and future residents. In order to analyze its affects, I look at several factors within the housing market. There are several factors explaining why cities similar to Oakland are continually impoverished and deprived. Some of the factors that explain why cities like Oakland stagnate and remain impoverished are the income distribution and poverty levels of residents in Oakland over the past decade, the increase in rent and/or spending on housing, and the current condition of housing stock. Together, these factors illustrate the lack of housing available to be rented to households, despite the growing number of vacancies during the ten-year period. This may lead to further degradation to the city of Oakland and migration out of Oakland. Among many others, these factors within the housing market are important in our analysis of why impoverished communities remain poor, because the residents have little to no upward economic mobility to sustain themselves.

II. Data and Methods
The U.S. Census Bureau and American Community Survey (ACS) act as the primary datasets for this report. The U.S. Census Bureau “consists of 813 detailed tables of Census 2000 social, economic and housing characteristics compiled from a sample of approximately 19 million housing units (about 1 in 6 households) [from nine major race] that received the Census 2000 long-form questionnaire” (1) while the ACS annually conducts a sample that covers topics such as “educational attainment, income, health insurance coverage, occupation, language spoken at home, nativity, ancestry and selected monthly homeowner costs” (2). More specifically, I extracted data from the 2000 Decennial Census Summary File 3 (SF3) and the 2010 ACS 3-year estimates from American FactFinder. When juxtaposing the Decennial Census data to the ACS data, I matched the variables in both datasets so that my report remains comprehensible and accurate.
The ACS is conducted in 1-year, 3-year, and 5-year estimates. When deciding upon which dataset to use, I thought about which dataset would trump the others. Opposed to the 1-year estimates, the 3-year estimates collected 36-months worth of data and had a larger sample size than 1-year so it was more reliable. Additionally, the data was more current than the 5-year estimates so I conclusively decided to use data from the 3-year estimates, as they were more precise and more current. In the following section, I will explain the results that I observed through the juxtaposition of both datasets. Additionally, I will use tables and line graphs to support the results.

III. Results
Pulling relevant variables from the two datasets, I compiled Table 1 and Figure 2 (same results, just in visual format), which depict the demographics of the city of...

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