Big Island Unemployment Rate Rises Slightly

Hawai‘i County’s unemployment rate for January 2019 (not seasonally adjusted) was 3.6.%, up .7% from the previous month and up a full percentage point from January 2018, the Hawai‘i State Department of Labor & Industrial Relations (DLIR) announced on March 7, 2019.

The state’s seasonally adjusted unemployment rate for January was 2.7% compared to the revised rate of 2.6% in December.

The not-seasonally-adjusted rate for the state was 2.9% in January, compared to 2.3% in December.

Statewide, 658,500 were employed and 18,000 unemployed in January for a total seasonally adjusted labor force of 676,500.

Nationally, the seasonally adjusted unemployment rate was 4% in January, compared to 3.9% in December.

Initial claims increased by 8 or .5% while weeks claims decreased by 1,191 or -14.3% for unemployment benefits compared to one year ago. Over-the-month both initial claims and weeks claims increased by 22.6% and 2.6% respectively in January 2019.

The unemployment rate figures for the State of Hawai‘i and the U.S. in this release are seasonally adjusted, in accordance with the U.S. Bureau of Labor Statistics (BLS) methodology.

Seasonal Adjustment

The seasonal fluctuations in the number of employed and unemployed persons reflect hiring and layoff patterns that accompany regular events such as the winter holiday season and the summer vacation season. These variations make it difficult to tell whether month-to-month changes in employment and unemployment are due to normal seasonal patterns or to changing economic conditions. Therefore, the BLS uses a statistical technique called seasonal adjustment to address these issues. This technique uses the history of the labor force data and the job count data to identify the seasonal movements and to calculate the size and direction of these movements. A seasonal adjustment factor is then developed and applied to the estimates to eliminate the effects of regular seasonal fluctuations on the data. Seasonally adjusted statistical series enable more meaningful data comparisons between months or with an annual average.