The Research & Planning section of the Wyoming Department of Workforce Services reported that the state’s seasonally adjusted1 unemployment rate remained unchanged from May to June at 4.1%. Wyoming’s unemployment rate was slightly lower than its June 2014 level of 4.4% and significantly lower than the current U.S. unemployment rate of 5.3%. Seasonally adjusted employment of Wyoming residents increased slightly, rising by an estimated 955 individuals (0.3%) from May to June. This level of over-the-month employment growth is a normal change.
From May to June, unemployment rates rose slightly in 15 counties, fell in five counties and were unchanged in three counties. It is not unusual for unemployment to increase in June as the school year ends and young people start looking for jobs. The largest unemployment rate increases occurred in Albany (up from 2.6% to 3.3%), Goshen (up from 3.0% to 3.5%), and Laramie (up from 3.3% to 3.7%) counties.
From June 2014 to June 2015, unemployment rates fell in 18 counties and rose in five counties. The largest decreases occurred in Niobrara (down from 3.7% to 2.6%), Crook (down from 4.1% to 3.1%), and Teton (down from 3.5% to 2.7%) counties. Unemployment rates increased from a year earlier in Natrona (up from 4.2% to 4.7%), Sweetwater (up from 4.3% to 4.7%), Campbell (up from 3.5% to 3.8%), Converse (up from 3.3% to 3.6%), and Fremont (up from 5.0% to 5.1%) counties.
Niobrara County had the lowest unemployment rate (2.6%) in June. It was followed by Teton (2.7%), Crook (3.1%), and Weston (3.2%) counties. The highest unemployment rates were reported in Fremont (5.1%), Uinta (4.8%), Natrona (4.7%), and Sweetwater (4.7%) counties.
Total nonfarm employment (measured by place of work) fell from 301,600 in June 2014 to 301,400 in June 2015, a loss of 200 jobs (-0.1%; not a statistically significant change). This was the first decrease in nonfarm employment since April 2013.
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 to better understand changes in economic conditions from month to month.