Texas Layoffs — October 2019
Employers in Texas filed 18 WARN Act notices in October 2019, impacting roughly 1,728 workers — representing a notable rise over 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 led the way in workforce reductions with 651 workers across 8 notices. In a parallel development, 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 absorbed the greatest share of layoffs, 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 single largest action involved 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 data underscores 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.