April 2010

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Labor Market Information


Wyoming Unemployment Rate Decreases in February

The Research & Planning section of the Wyoming Department of Employment reported today that for the first time since February 2008, the state’s seasonally adjusted1 unemployment rate decreased. Wyoming’s unemployment rate steadily increased from 2.7% in February 2008 to 7.6% in January 2010. However, it decreased to 7.5% in February 2010. Additionally, over-the-year job losses have slowed somewhat from -6.3% in October 2009 to -4.5% in February 2010.

Over the year, the number of nonagricultural wage and salary jobs in Wyoming decreased by 12,800 (-4.5%). It appears that over-the-year job losses have been slowing since October 2009 when they stood at -6.3%. Large job losses were seen in natural resources & mining (-3,200 jobs, or -11.4%), construction (-3,000 jobs, or -13.6%), leisure & hospitality (-1,600 jobs, or -5.2%), other services (-1,400 jobs, or -11.7%), and professional & business services (-1,400 jobs, or -8.2%). Employment increased modestly in educational & health services (200 jobs, or 0.8%) and government (including public schools, colleges, and hospitals; 200 jobs, or 0.3%).

From January to February, Wyoming lost 400 nonagricultural wage and salary jobs (-0.1%). This decrease is not consistent with historical seasonal patterns. On average, employment tends to increase in February by approximately 1,000 jobs (0.4%). Natural resources & mining (including oil & gas) added 300 jobs (1.2%), but construction employment fell by 1,100 jobs (-5.5%). Government employment (including public schools, colleges, and hospitals) increased by 1,300 jobs (1.8%).

Most county unemployment rates followed their normal seasonal pattern and decreased slightly from January to February. The lowest unemployment rates were found in Albany (5.4%), Sublette (5.6%), and Hot Springs (6.3%) counties. Unemployment rates were higher in February 2010 than a year earlier in all 23 counties.

1    Seasonal 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.


Last modified by Michael Moore.