Texas Layoffs — September 2015
Employers in Texas recorded 24 WARN Act notices in September 2015, covering approximately 1,883 workers — marking a sharp increase from August and up 11% versus September 2014. The average filing covered 78 workers, with 0 closures among the notices.
Industry Breakdown
| Industry | Notices | Workers |
|---|---|---|
| Mining & Energy | 15 | 972 |
| Information & Technology | 3 | 522 |
| Manufacturing | 3 | 172 |
| Finance & Insurance | 1 | 105 |
| Healthcare | 1 | 65 |
| Wholesale Trade | 1 | 47 |
The Mining & Energy sector accounted for the largest share of job cuts with 972 workers across 15 notices. At the same time, Information & Technology reported 522 workers.
Geographic Hotspots
| County | Notices | Workers |
|---|---|---|
| Harris | 18 | 1,443 |
| Dallas | 1 | 105 |
| Bexar | 1 | 87 |
| Archer | 1 | 70 |
| Tarrant | 1 | 65 |
Harris felt the sharpest impact, accounting for 77% of all affected workers with 1,443 workers across 18 notices.
| City | Notices | Workers |
|---|---|---|
| Houston | 18 | 1,443 |
| Addison | 1 | 105 |
| San Antonio | 1 | 87 |
| Wichita Falls | 1 | 70 |
| Fort Worth | 1 | 65 |
Layoff Type Analysis
Layoff type classification was not available for filings in Texas this month.
Largest Layoffs
Leading the list was ABM Janitorial Services at its Houston facility, reporting 260 affected workers. AT&T-Houston followed with 201 workers.
Trend & Outlook
After a dip last month, layoff activity has ticked back up.
The filings reflect mounting pressure on the Texas labor market, with activity running above both recent and year-ago benchmarks. The Mining & Energy 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.