October 2010

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Labor Market Information


Wyoming Unemployment Rate Rises Slightly in August 2010

The Research & Planning section of the Wyoming Department of Employment has reported that the state's seasonally adjusted1 unemployment rate rose from 6.7% in July to 6.8% in August (not a statistically significant increase). Despite this increase, Wyoming's unemployment rate was significantly lower than the U.S. unemployment rate of 9.6%. Employment growth continued as the state added 1,400 jobs (0.5%) from August 2009.

Over the year, Wyoming added 1,400 nonagricultural wage and salary jobs (0.5%). Natural resources & mining (including oil & gas) posted the largest job gains (2,000 jobs, or 8.2%), followed by government (including public schools, colleges, & hospitals; 1,100 jobs, or 1.7%). More modest gains were seen in wholesale trade (500 jobs, or 5.8%), educational & health services (500 jobs, or 2.0%), transportation & utilities (300 jobs, or 2.1%), and manufacturing (300 jobs, or 3.3%). Job losses occurred in construction (-1,600 jobs, or -6.2%), retail trade (-900 jobs, or -2.9%), other services (-700 jobs, or -5.9%), and financial activities (-400 jobs, or -3.5%).

From July to August, Wyoming wage and salary employment fell by 400 jobs (-0.1%). This level of decrease is consistent with normal seasonal patterns. Seasonal job gains in construction (1,000 jobs, or 4.3%) and natural resources & mining (200 jobs, or 0.8%) were more than offset by seasonal job losses in government (-600 jobs, or -0.9%), leisure & hospitality (-500 jobs, or -1.3%), retail trade (-300 jobs, or -1.0%), and professional & business services (-300 jobs, or -1.6%).

Most county unemployment rates were stable or rose slightly from July to August. Natrona County posted the largest increase (up from 6.7% to 7.2%). Unemployment rates also increased in Platte (up from 6.6% to 7.0%), Laramie (up from 6.9% to 7.2%), and Goshen (up from 6.0% to 6.3%) 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.



Last modified by Michael Moore.