Wyoming Job Losses Slow in May 2010
The Research & Planning section of the Wyoming Department of Employment has reported that over-the-year job losses have slowed from 6.3% in October 2009 to 1.8% in May 2010. The state's seasonally adjusted1 unemployment rate decreased from 7.1% in April to 7.0% in May. It remained somewhat higher than its May 2009 level of 6.1%, but significantly lower than the current U.S. unemployment rate of 9.7%.
Over the year, employment decreased by 5,200 jobs (-1.8%). Large job losses were seen in construction (-3,100 jobs, or -12.4%), other services (-1,500 jobs, or -12.3%), and leisure & hospitality (-1,400 jobs, or -4.3%). Employment also decreased in financial activities (-400 jobs, or -3.5%), professional & business services (-300 jobs, or -1.7%), natural resources & mining (-200 jobs, or -0.8%), retail trade (-100 jobs, or -0.3%), and information (-100 jobs, or -2.5%). Job growth occurred in wholesale trade (100 jobs, or 1.1%), educational & health services (300 jobs, or 1.2%), manufacturing (500 jobs, or 5.6%), and government (including public schools, colleges, and hospitals; 1,000 jobs, or 1.3%).
From April to May, Wyoming gained 8,200 jobs (3.0%). This level of increase is consistent with normal seasonal patterns. Government employment increased by 2,700 jobs (3.7%) partly because of seasonal hiring by the U.S. Census Bureau. Seasonal job gains were also seen in leisure & hospitality (2,400 jobs, or 8.4%), professional & business services (800 jobs, or 4.9%), retail trade (800 jobs, or 2.7%), construction (500 jobs, or 2.3%), and natural resources & mining (400 jobs, or 1.6%).
County unemployment rates decreased or held steady from April to May. The lowest unemployment rates were found in Sublette (4.4%), Albany (4.7%), and Niobrara (4.8%) counties. Although unemployment rates were higher than a year earlier in most counties, decreases were seen in Big Horn, Hot Springs, Niobrara, and Sublette 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.