Employers in Mississippi recorded 3 WARN Act notices in May 2016, covering approximately 389 workers — marking a sharp increase from April and up 58% versus May 2015. The average filing covered 130 workers, with 3 closures among the notices.
| Industry | Notices | Workers |
|---|---|---|
| Manufacturing | 2 | 319 |
| Utilities | 1 | 70 |
The Manufacturing sector accounted for the largest share of job cuts with 319 workers across 2 notices. At the same time, Utilities reported 70 workers.
| County | Notices | Workers |
|---|---|---|
| Lafayette | 1 | 240 |
| Coahoma | 1 | 70 |
Lafayette bore the heaviest burden, accounting for 62% of all affected workers with 240 workers across 1 notices.
| City | Notices | Workers |
|---|---|---|
| Oxford | 1 | 240 |
| Vidalia | 1 | 79 |
| Clarksdale | 1 | 70 |
| Type | Notices | Workers |
|---|---|---|
| Closure | 3 | 389 |
The high proportion of closures (100% of affected workers) suggests structural shifts rather than temporary cutbacks in Mississippi's labor market.
| Company | City | Workers | Type | Date |
|---|---|---|---|---|
| Caterpillar | Oxford | 240 | Closure | 2016-05-04 |
| Fruit of the Loom | Vidalia | 79 | Closure | 2016-05-17 |
| Metso Minerals Industries, Inc./Stephens-Adamson | Clarksdale | 70 | Closure | 2016-05-20 |
Leading the list was Caterpillar at its Oxford facility, reporting 240 affected workers. Fruit of the Loom followed with 79 workers.
After a dip last month, layoff activity has ticked back up.
The filings reflect mounting pressure on the Mississippi labor market, with activity running above both recent and year-ago benchmarks. The Manufacturing sector warrants close attention heading into the next period.
This analysis is based on official WARN Act filings reported by Mississippi. 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 Mississippi WARN notices, browse layoffs by state, or download the full dataset.
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