Wyoming Unemployment Rate Falls to 5.5% in January 2012
The Research & Planning section of the Wyoming Department of Workforce Services has reported that the state's seasonally adjusted1 unemployment rate fell from 5.6% in December 2011 (as revised) to 5.5% in January 2012. Wyoming's jobless rate has decreased for five consecutive months and it remained much lower than the U.S. rate (8.3%). Seasonally adjusted employment of Wyoming residents increased by an estimated 862 individuals (0.3%) from December to January.
Most county unemployment rates followed their normal seasonal pattern and increased from December to January. With colder weather and the end of the holiday season, employment tends to decrease from December to January in construction, retail trade, professional & business services, leisure & hospitality, and government. The largest over-the-month increases in unemployment occurred in rural areas of the state. Johnson County's unemployment rate rose from 6.6% in December to 8.0% in January, Washakie County's rate rose from 5.2% to 6.6%, and Hot Springs County's rate rose from 4.6% to 5.9%.
The highest county jobless rates were found in Lincoln (9.1%), Johnson (8.0%), and Fremont (7.9%) counties. Sublette County posted the lowest unemployment rate in January (3.4%). The next lowest unemployment rates occurred in Campbell (4.7%), Albany (4.9%), and Niobrara (5.0%) counties.
When compared to a year earlier, jobless rates decreased in 22 of the state's 23 counties. Goshen County was the exception. Its unemployment rate edged up from 6.1% in January 2011 to 6.2% in January 2012. Large decreases in unemployment were seen in Big Horn (down from 9.0% to 7.0%), Natrona (down from 7.4% to 5.8%), and Washakie (down from 8.0% to 6.6%) counties.
Total nonfarm employment (measured by place of work) rose from 273,900 in January 2011 to 277,200 in January 2012, an increase of 3,300 jobs (1.2%).
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.
