The Suburbanization of Poverty: The Geography of Childhood Poverty in and around Austin

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The Suburbanization of Poverty: The Geography of Childhood Poverty in and around Austin

Categories: Projects

The following is a project summary written by Sam Tedford, a former intern, regarding her work on childhood poverty in Austin while at COH.

In recent years, Austin has settled in near the top of the list of fastest growing cities in the United States. And though we know that the city is rapidly growing, there is still much to understand about the changing demographics of Austin. Historically, racist urban planning led Austin to develop into an intensely segregated city both economically and racially with large concentrations of urban poor communities and communities of color forced into certain neighborhoods on the east side. However, in the changing social and economic environment of Austin today, the geography of poverty and race is unlike anything this city has seen before. A quickly growing city means a growing demand for housing, which has led to a major affordability crisis in the Austin housing market, and the displacement of many low income residents due to gentrification. For my study I focused on one of the most vulnerable populations directly affected by poverty and displacement: children. The study analyzes the geographic distribution of economically disadvantaged children in Austin and the surrounding areas across ten years from 2005 to 2015.

Mapping Disadvantaged Populations

Using data from Texas Education Agency performance reports from the 2004-2005 school year and the 2014-2015 school year, I initially mapped both district level and campus level economically disadvantaged rates, defined as the percentage of the student population on free and reduced lunch, while denoting Title I qualifying schools in each time period.

In the 2004-2005 school year, 12 out of 27 of the school districts surrounding Austin had over 40% of their student population on free or reduced lunch. By the 2014-2015 school year, 20 out of the 27 districts had a population comprised of over 40% economically disadvantaged kids.

School Districts











In the 2004-2005 school year, 117 out of 200 campuses in the study area qualified as Title I. In the 2014-2015 school year, 164 out of 266 campuses qualified as Title I.

School Campuses












Mapping Change over Time

Mapping Hotspots

In an attempt to find patterns in the rise of economically disadvantaged student populations, I first looked for spatial auto-correlation, or clustering, of economically disadvantaged populations in the district-level data. By calculating Moran’s I, a spatial statistic which compares each target feature to its neighbors as well as to the mean of all features, the district-level data showed statistically significant clustering with a 95% confidence interval. This initial calculation compelled me to continue exploring patterns in geographic proximity of economically disadvantaged districts and calculate the Getis-Ord Gi* statistic for the district-level data, another spatial statistic which identifies hot and cold spots, for economically disadvantaged student populations.

The results of the hot spot analysis reveals hotspots in Elgin, Bastrop, Manor, and Del Valle, meaning those school districts had a statistically significant concentration of economically disadvantaged populations. This method of analysis also reveals coldspots, here meaning statistically significant concentrations of low economically disadvantaged percentages, in five school districts: Dripping Springs, Lake Travis, Lago Vista, Eanes, and Leander.

Mapping Directional Distribution




Next, I tested for similar patterns in the campus-level data. I first calculated standard deviational ellipses (SDE) for the 2004-2005 data and for the 2014-2015 data. SDEs were calculated in order to measure directional trends in the distribution of elementary school campuses with high economically disadvantaged student populations by weighting campuses by the raw count of economically disadvantaged students. The results show an increase of 77.53 square miles in area from 2005-2015 with directional shifts to the Northeast and the South.








Again, this prompted me to continue to explore patterns in the geographic distribution of economically disadvantaged students over time, and so I again calculated statistically significant hot and cold spots using the GetisOrd
Gi* statistic. The results reveal strong hotspots in the southeastern parts of Austin with developing hotspots in the far south, San Marcos ISD. This map shows a distinct coldspot to the west of Austin and a neutral line of campuses that are likely statistically insignificant due to their extreme neighbors on either side.





Mapping Distance from Austin City Center

Finally, in an attempt to visualize the relationship between schools with high economically disadvantaged populations and the city center, I created a simple graph with the campus’s distance from the city center on the X axis and the campus’s economically disadvantaged rate on the Y axis. This graph displays the line for both 2004-2005 and 2014-2015 and reveals that the highest average percentage of economically disadvantaged students increased from 5 to 10 miles in 2004-2005 to over 30 miles away in 2014-2015.


What this data shows is that:

  1. The percentage of children living in poverty rose in the majority of the school districts in the Austin area from 2005 to 2015.
  2. The largest percentage point increases in economically disadvantaged populations from 2005 to 2015 happened in districts increasingly distant from center of Austin.
  3. The major directional shifts in childhood poverty since 2005 have been to the Northeast and to the South with a distinctive majority of childhood poverty situated in the eastern half of Austin and surrounding districts, namely Austin, Del Valle, Manor, and Bastrop.
  4. Childhood poverty in the Austin area is not randomly distributed and is distinctly clustered.

These changes in the geography of childhood poverty are important because they have an impact on how (and where) we aim to fight poverty. The methods and systems we have developed over the years to combat the effects of dense, urban poverty may not translate well to the sprawling suburbs. Austin is not alone among cities experiencing the suburbanization of poverty and shares many challenges with other cities nationwide. And though the trend is recent enough that we know little about its long-term effects, there are a some key areas that we know will be directly affected by the shifting geography of poverty. The suburbanization of poverty will have a direct impact on where we locate and how we implement health and human services, how we plan transportation systems, and who has access to job opportunities. The rise in suburban childhood poverty will have an effect on schools that have not historically supported large populations of economically disadvantaged students. And even as we seek to understand and meet the growing needs of these communities in real time, we must also be thinking upstream and questioning, what caused this?

Sam was an intern for Children’s Optimal Health and recently graduated from The University of Texas at Austin from the Department of Geography and the Environment. She is currently working as a Planner for the City of Austin Comprehensive Planning Division of the Planning and Zoning Department and keeps a weather eye on the shifting demographics of Austin and the modern and historic social injustices driving them.