New Mexico Layoffs — August 2020
Employers in New Mexico submitted 4 WARN Act notices in August 2020, putting at risk an estimated 491 workers — up substantially from July and up 327% versus August 2019. The average filing covered 123 workers, with 0 closures among the notices.
Industry Breakdown
| Industry | Notices | Workers |
|---|---|---|
| Mining & Energy | 1 | 290 |
| Information & Technology | 2 | 129 |
The Mining & Energy sector emerged as the hardest-hit sector with 290 workers across 1 notice. Separately, Information & Technology reported 129 workers.
Geographic Hotspots
| County | Notices | Workers |
|---|---|---|
| McKinley | 1 | 290 |
| Bernalillo | 2 | 136 |
| Eddie | 1 | 65 |
McKinley bore the heaviest burden, accounting for 59% of all affected workers with 290 workers across 1 notices.
| City | Notices | Workers |
|---|---|---|
| Albuquerque | 2 | 129 |
Layoff Type Analysis
Layoff type classification was not available for filings in New Mexico this month.
Largest Layoffs
| Company | City | Workers | Type | Date |
|---|---|---|---|---|
| Marathon Petroleum | 290 | |||
| CTS Electronic Components | 72 | |||
| Albuquerque Publishing | Albuquerque | 65 | ||
| Albuquerque Publishing | Albuquerque | 64 |
Topping the list was Marathon Petroleum at its New Mexico facility, reporting 290 affected workers. CTS Electronic Components followed with 72 workers.
Trend & Outlook
This marks the third consecutive month of rising layoff activity.
These figures highlight mounting pressure on the New Mexico 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 New Mexico. 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 New Mexico WARN notices, browse layoffs by state, or download the full dataset.