DeKalb County’s unemployment rate for February was 4.6%, down from 4.7% in January but well below the 5.8% rate recorded in February, 2017.
The local labor force for February was 7,790. A total of 7,430 were employed and 360 were without work.
Jobless rates for February among the fourteen counties in the Upper Cumberland region were as follows from highest to lowest:
Van Buren: 4.2%
According to the Tennessee Department of Labor and Workforce Development, the latest statistics showed improved rates for the majority of the state’s counties during the month.
Sixty-nine of Tennessee’s 95 counties saw lower unemployment rates when compared to January 2018. The rates remained the same in 21 counties and increased in five counties.
“It is great to see unemployment rates decrease in so many counties during February,” said Department of Labor and Workforce Development Commissioner Burns Phillips. “While this type of rebound in February is typical after the state usually experiences a slight uptick in unemployment after the holidays, it is not a given.”
Williamson County continued to have the state’s lowest unemployment rate. The February rate of 2.4 percent is a decrease of 0.1 of a percentage point when compared to the previous month.
At 2.6 percent, Davidson County had the state’s second lowest unemployment rate in February, which was 0.1 of a percentage point lower than January’s rate.
Houston County had the state’s highest unemployment rate in February at 6.8 percent, which is the same rate the county had in January. The latest statistic was 0.2 of a percentage point lower than the county’s February 2017 unemployment rate.
Tennessee’s statewide seasonally adjusted unemployment rate for February 2018 was 3.4 percent, a 0.1 of a percentage point increase from the revised January rate of 3.3 percent. The national unemployment rate for the month held steady at 4.1 percent.
The statewide unemployment rate is seasonally adjusted, while county rates are not. Seasonal adjustment is a statistical technique that eliminates the influences of weather, holidays, the opening and closing of schools and other recurring seasonal events from an economic time series.