Wyoming Unemployment Falls Slightly in November 2008
Wyoming’s seasonally adjusted1 unemployment rate edged downward from 3.3% in October to 3.2% in November (not a statistically significant change). The U.S. unemployment rate increased from 6.5% in October to 6.7% in November and remained much higher than its year-ago level of 4.7%. Wyoming job growth continued at a solid rate of 2.8% (8,200 jobs) while the U.S. lost 2 million jobs (-1.5%) from a year earlier.
From October to November, Wyoming lost 4,200 jobs (-1.4%). This level of decrease is consistent with normal seasonal patterns. Seasonal job losses in natural resources & mining (-400 jobs, or -1.4%), construction (-900 jobs, or -3.1%), professional & business services (-500 jobs, or -2.6%), leisure & hospitality (-2,700 jobs, or -8.0%), and government (-600 jobs, or -0.8%) were partially offset by seasonal gains in retail trade (500 jobs, or 1.5%) and educational & health services (400 jobs, or 1.6%).
Over the year Wyoming added 8,200 jobs (2.8%). Growth was seen in most sectors. The largest job gains were found in government (including public schools, colleges, and hospitals; 2,300 jobs, or 3.4%), natural resources & mining (1,900 jobs, or 7.0%), educational & health services (1,100 jobs, or 4.6%), and leisure & hospitality (800 jobs, or 2.6%). More modest gains occurred in retail trade (600 jobs, or 1.9%), professional & business services (600 jobs, or 3.3%), and other services (400 jobs, or 3.4%). Job losses continued in manufacturing (-100 jobs, or -1.0%) and employment held steady in Wyoming’s information sector.
Most county unemployment rates followed their normal seasonal pattern and increased from October to November. Teton County posted the highest unemployment rate (4.5%), followed by Platte County (4.2%) and Fremont County (4.1%). The lowest unemployment rates were found in Sublette (1.4%), Campbell (1.8%), and Albany (2.3%) counties.
1Seasonal adjustment is a statistical procedure to remove the impact of normal regularly recurring events (such as weather, major holidays, and the opening and closing of schools) from economic time series in order to obtain a better understanding of changes in economic conditions from month to month.