"Labor Market Information (LMI) is an applied science; it is the systematic collection and analysis of data which describes and predicts the relationship between labor demand and supply." The States' Labor Market Information Review, ICESA, 1995, p. 7.
by: David Bullard, Senior Economist
The Research & Planning section of the Wyoming Department of Workforce Services reported that the state’s seasonally adjusted1 unemployment rate remained unchanged from July to August at 3.0%. Wyoming’s unemployment rate is somewhat lower than its August 2025 level of 3.3% and much lower than the current U.S. rate of 4.1%.
From July to August, most county jobless rates rose slightly. The largest increases were found in Niobrara (up from 3.1% to 4.0%), Platte (up from 3.0% to 3.5%), Carbon (up from 2.5% to 2.9%), and Hot Springs (up from 2.5% to 2.9%) counties. Fremont County’s unemployment rate fell from 3.5% to 3.4%, and unemployment rates held steady in Sweetwater (3.4%), Converse (2.4%), and Albany (2.2%) counties.
Compared to a year earlier, unemployment rates rose in eight counties, fell in 14 counties and remained unchanged in Crook County. The largest increases occurred in Johnson (up from 2.2% to 2.5%) and Teton (up from 1.5% to 1.8%) counties. The largest decreases were seen in Goshen (down from 3.4% to 2.8%), Big Horn (down from 3.8% to 3.2%), and Uinta (down from 3.3% to 2.8%) counties.
In August, the lowest unemployment rates were reported in Teton County at 1.8% and Albany County at 2.2%. The highest unemployment rates were found in Niobrara County at 4.0% and Platte County at 3.5%.
Current Employment Statistics (CES) estimates show that total nonfarm employment in Wyoming (not seasonally adjusted and measured by place of work) rose from 300,100 in August 2025 to 300,600 in August 2026, an increase of 500 jobs, or 0.2%.
R&P's most recent monthly news release is available at https://doe.state.wy.us/LMI/news.htm.
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.
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