Texas Layoffs — October 2019
Employers in Texas reported 18 WARN Act notices in October 2019, displacing an estimated 1,728 workers — signaling an acceleration from September and up 32% versus October 2018. The average filing covered 96 workers, with 0 closures among the notices.
Industry Breakdown
| Industry | Notices | Workers |
|---|---|---|
| Transportation | 8 | 651 |
| Manufacturing | 5 | 536 |
| Healthcare | 1 | 156 |
| Professional Services | 1 | 146 |
| Accommodation & Food | 2 | 122 |
| Utilities | 1 | 117 |
The Transportation sector topped the list of affected industries with 651 workers across 8 notices. Notably, Manufacturing reported 536 workers.
Geographic Hotspots
| County | Notices | Workers |
|---|---|---|
| Travis | 3 | 527 |
| Bexar | 4 | 410 |
| Harris | 3 | 306 |
| Dallas | 4 | 293 |
| Cameron | 1 | 100 |
Travis saw the most concentrated activity, accounting for 30% of all affected workers with 527 workers across 3 notices.
| City | Notices | Workers |
|---|---|---|
| Austin | 3 | 527 |
| San Antonio | 3 | 343 |
| Houston | 3 | 306 |
| Farmers Branch | 2 | 173 |
| Garland | 1 | 119 |
Layoff Type Analysis
Layoff type classification was not available for filings in Texas this month.
Largest Layoffs
The most significant filing came from Samsung at its Austin facility, reporting 290 affected workers. Nix Specialty Health-Behavioral Facility followed with 156 workers.
Trend & Outlook
After a dip last month, layoff activity has ticked back up.
The numbers illustrate mounting pressure on the Texas labor market, with activity running above both recent and year-ago benchmarks. The Transportation sector warrants close attention heading into the next period.
This analysis is based on official WARN Act filings reported by Texas. The Worker Adjustment and Retraining Notification (WARN) Act requires employers with 100+ employees to provide 60-day advance notice of mass layoffs and plant closings. Data is updated daily by WARN Firehose. View all Texas WARN notices, browse layoffs by state, or download the full dataset.