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County Migration in Texas

ByBlake Decker
In our previous blog post, we looked at state-to-state migration trends, digging into the American Community Survey (ACS) migration flows data to look at in-migration, out-migration, and net migration trends across American states. We found that Texas had the second-highest net increase in the 2020 data with almost 98,000 new residents, only trailing the state of Florida’s 170K net increase. Narrowing our focus to the 254 counties in Texas, this blog post seeks to identify trends in the movement of people in and out of Texas counties. NOTE: Hovering over a county on the map changes the bar chart to show county-level data as well.
Net Migration in Texas Counties
  • Out of the almost 29-million Texans in 2020, more than 1.55 million (5.3%) residents moved from the county they resided in during the previous year. Although a relatively small percentage, this number of “on-the-move” Texans is greater than the total population of 11 states plus the District of Columbia. More than 70% (1.1 million) of these residents moved to another county in Texas, while 30% (453K) moved out-of-state.
  • As you can see from the color legend below the map, net migration for Texas counties ranged from approximately -30,000 to 26,000. The largest net gains were in Denton (25,587), Williamson (18,637), and Tarrant (12,877) counties, while the largest net losses were in El Paso (-7,881), Harris (-18,545), and Dallas (-29,659) counties.
  • For the Texans who moved to another county in Texas, more than 45% of those individuals moved to a county that was within 50 miles. This pattern is exemplified in the mobility of people within the DFW Metroplex.
    • For example, out of the estimated 81K Texans who relocated to Denton County in 2020, an estimated 41K residents moved from adjacent counties: Dallas (19K), Collin (13K), and Tarrant (8K) counties.
    • Out of the 147K residents who left Dallas County in 2020, more than 59K relocated to adjacent counties: Tarrant (21K), Denton (19.4K), and Collin (18.9K).
  • Three counties that saw relatively large net losses in migration were in deep south Texas, as Webb, Hidalgo, and Cameron counties combined for a net loss of more than 15K residents who moved within the United States. This highlights one of the challenges when working with ACS data. The data shown on the map do not include international migration data that are included in the ACS migration flows data. This is due, in part, to the ACS data only showing “in-migration” estimates aggregated at the continent level for non-residents of the United States. Because these data do not show bi-directional flow (out-migration to other countries), migration into certain Texas counties (e.g., on the Mexico border) can artificially inflate net migration rates, as the ACS data do not account for how many individuals are estimated to have moved from a Texas county to another country.
In-Migration by Texas County
The bar chart above shows a breakdown of county-level residents by geographic mobility status. Although a large number of Texans relocate every year, the vast majority of Texans did not move, or at least did not move very far.
  • Almost 85% of all Texans lived in the same residence in 2020 as they did in 2019.
  • Out of the 15% who moved, around 9% moved to a different residence in the same county.
  • For counties with populations greater than 15,000, the highest percentage of within-county relocation occurred in Brazos (15.2%), Lubbock (13.5%), Nacogdoches (12.7%) and Bell (12.6%) counties.
  • Four counties that have populations greater than 15,000 experienced double-digit in-migration from other Texas counties: Jones (19.5%), Rusk (11.4%), Liberty (11.3%), and Fannin (10.6%).

So What?

The data and observations shown above provide but a glimpse into the complexity and multifaceted nature of the geographic mobility data published by the US Census Bureau. Even with issues surrounding estimation techniques, such as unidirectional international migration along the US-Mexico border, these robust data can be incorporated into localized planning processes at the regional, county, and institutional levels. In the next few blog posts, we will explore how entities might use these data elements to inform decision-making processes moving forward.