Wyoming Unemployment Falls in March 2010
The Research & Planning section of the Wyoming Department of Employment has reported that the state’s seasonally adjusted1 unemployment rate decreased from 7.5% in February to 7.3% in March. It remained much higher than its March 2009 level of 5.2%, but significantly lower than the U.S. unemployment rate of 9.7%. Over-the-year job losses slowed from -6.3% in October 2009 to -3.6% in March 2010.
Over the year, employment fell by 10,300 jobs (-3.6%). As in previous months, large job losses were seen in construction (-3,200 jobs, or -14.5%), natural resources & mining (-2,600 jobs, or -9.6%), leisure & hospitality (-1,800 jobs, or -5.8%), other services (-1,500 jobs, or -12.5%), and professional & business services (-1,300 jobs, or -7.6%). Job gains occurred in government (including public schools, colleges, and hospitals; 1,000 jobs, or 1.4%), educational & health services (400 jobs, or 1.6%), and manufacturing (300 jobs, or 3.3%).
From February to March, Wyoming added 1,600 jobs (0.6%). This level of increase is consistent with normal seasonal patterns for March. Government (including public schools, colleges, and hospitals) gained 1,300 jobs (1.8%). Some of the growth in government employment may be related to hiring of temporary workers by the Census Bureau. Employment fell by 200 jobs (-0.8%) in natural resources & mining, while employment grew in retail trade (200 jobs, or 0.7%), transportation & utilities (200 jobs, or 1.4%), and professional & business services (200 jobs, or 1.3%).
Most county unemployment rates followed their normal seasonal pattern and decreased from February to March. Lincoln County posted the highest unemployment rate (10.8%) followed by Johnson (9.6%) and Fremont (9.0%) counties. Albany and Sublette counties tied for the lowest unemployment rate at 5.2%.
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.