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Calculation of the Unemployment Rate

Map of the United States showing the unemployment rate by county in January 2013.
Figure 1: Unemployment Rate in January 2013.
Do all our readers need to know how to calculate unemployment rates? Perhaps not, but they don’t have to be government statisticians or empirical macroeconomists to want to know what’s involved in the calculation. A casual interest in current events is sufficient.

The unemployment rate is an indicator of economic vitality used in 183 nations. During an economic contraction, we look to the unemployment data released by the U.S. Bureau of Labor Statistics (BLS) at the beginning of every month for signs of recovery. The January 2013 rate of 7.9 percent has changed little since September 2012.

National unemployment rates are released following a 1-month delay. The statistics are released in both a raw form and a seasonally adjusted form, which helps separate the regular short-run seasonal fluctuations from cyclical and structural trends in unemployment. Seasonal increases in unemployment occur during the winter, after the holiday shopping season ends, and at the beginning of summer, when students enter the labor force.

Unemployment is a measure of labor underutilization. You are considered unemployed if you do not have a job, are looking for a job, and are available for work. Not having a job is not enough; you have to be actively searching for work (defined as having made at least one attempt in the past 4 weeks to find a job) and you must be available to take the job if you are hired (meaning that you must be16 years or older, a civilian, and not in an institution). Those who stop looking for work because they feel they can’t find a job in the current economy are not classified as unemployed. In today’s climate, counting these discouraged workers would raise the unemployment rate by about half a percentage point.

Map of the United States showing the change in unemployment rate by county between January 2012-January 2013.
Figure 2: Change in Unemployment Rate between January 2012-Janaury 2013.
You are employed if you have a job. That fact may seem obvious, but it is not trivial. Reducing your hours from full-time to part-time work does not change your employment status.

The labor force — that is, those active in the labor market — is defined as the sum of the unemployed and employed. The unemployment rate uses the labor force statistic as its base.

In the United States, BLS measures the unemployment rate using data collected by the U.S. Census Bureau in its monthly survey of a sample of about 60,000 households. This sample is representative of the entire U.S. population, and the final results are weighted to reflect national demographic characteristics. Weighting is critical because a number of factors can cause variation in the unemployment rate. For example, the unemployment rate is 8.5 percentage points higher for construction occupations than it is for healthcare occupations. The unemployment rate is 25 percentage points greater in the city of Yuma than in Bismarck. Single black males, on average, are unemployed at a rate 13 percentage points higher than that of married white females. Finally, as mentioned, the national estimates are adjusted for seasonal fluctuations.

Figure 1 displays unemployment rates by county for January 2013. The lightest blue signifies counties with unemployment rates of between 0 and 6.8% and the darkest blue are counties equal to or above 15%. We see concentration of unemployment in California, the East Central region, and a few clusters throughout the Southeast.

The local area unemployment statistics are released after a 2-month delay. BLS estimates employment and unemployment rates for 7,300 local areas in the United States (including states, counties, and cities). BLS’ statistical models combine current and historical data from the Current Population Survey, state unemployment insurance systems, and the decennial census. These statistics are the result of a cooperative effort of the federal and state governments.

In order to view dynamics we examine the one year change in the unemployment rate as shown in Figure 2. Greens signify a decrease or no change and yellow and brown signify an increase in the unemployment rate. Darker green is a larger decrease (less than -1.0) and brown is a larger increase (greater than +1.5%). We see that of the high unemployment areas: the situation in California is improving, and the patterns of change in the East Central and Southeast. The outlook in much of the U.S. is improving, most clearly in Florida and much of the Mountain region. Unemployment varies significantly across space. The nature of the spatial distribution is important not only for economic policy but also for social and housing policy. Although we have hinted at some disadvantages to using the unemployment rate as an indicator of economic vitality, one strong advantage is that it simplifies temporal and spatial comparisons.