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 Iowa Workforce Information NetworkSeptember 1, 2014
A Look at How Iowa's Unemployment Rate is Calculated
by Ann WagnerPrinter-friendly version of this articlePrinter-friendly version
The Current Population Survey

The Local Area Unemployment Statistics Program
Labor Force Concepts
*The Current Population Survey
The LAUS Redesign
Implementation of New and Revised Labor Areas

The Current Population Survey is a survey of households conducted by the Census Bureau each month for the Bureau of Labor Statistics. The Census Bureau carries out all phases of the CPS data collection process, while BLS analyzes and publishes the data. The data from the CPS are used to produce the labor force estimates directly for the United States and indirectly for the individual states. Nationally, there are approximately 78,000 eligible households in the sample. In Iowa, the sample size is approximately 1,288 households.

The CPS household survey manages to reduce costs while collecting information about the characteristics of an entire population. There are several ways to obtain information about a group, ranging from asking one individual to asking every individual within the group. In the LAUS program, the labor force status of individuals is classified according to the concepts defined in the previous section. The most accurate way to do this would be to survey all individuals within an area to determine their labor force status.  Unfortunately, this process would be time-consuming and very expensive. Therefore, a smaller group within the larger population is interviewed. Statistical theory asserts that if the smaller group is an accurate representation of the larger group, then generalizations can be made about the larger group, using the data collected from interviews with the smaller group. This method of obtaining information saves time and money, while producing results comparable to what would be expected had the entire population been interviewed.

Households in the CPS are initially selected using a probability design. In theory, each household in Iowa has an equal chance of being chosen initially to participate in the survey. The basic rationale behind the selection process is that, within each area, strata are identified and targeted to ensure that the CPS is reflective of the area's demographic and socioeconomic characteristics.

An important feature of the CPS is that there is a "4-8-4" sample rotation methodology. Using this process, a selected household is questioned for four consecutive months, dropped from the sample for eight months, and then returned to the sample and questioned for another four months. Households are rotated in and out of the sample at different times. Seventy-five percent of the households remain the same from month to month. Fifty percent of the households remain in the sample from the prior year. Once a household permanently leaves the sample, it is replaced by its neighbor to ensure that the CPS remains reflective of the area's demographic and socioeconomic characteristics.

Two important characteristics of the CPS are changing reliability and sample overlap. The design of the CPS in regard to the states raises important questions about the reliability of the results. "Reliability" can be defined as how confident we are that our results meet a certain level of accuracy and are sensitive enough to detect real changes of a given magnitude. Due to the sample design of the CPS, there is a low reliability in these estimates. The low number of households surveyed in Iowa, given the way that the sample is conducted, causes volatile swings in the month-to-month data, thereby masking real change.

The sample overlap (4-8-4 rotation method) causes something called "autocorrelated sampling error."  Because of the way households are rotated in the CPS, periods of overestimation and underestimation of the "true" value result. The "true" value is the unobserved value that would result if the entire population were surveyed. In other words, since 75 percent of the households remain the same from month-to-month, a sample that is not representative of the entire population one month is likely to carry over into the next month. This "error" that carries over to the next month results in an extended period of time where the estimated value from the CPS diverges from the true value.

The design of a survey determines how much error the results will contain. The design of the CPS allows for high levels of error to show up in the results. Although this causes a high level of variation in CPS data, this does not necessarily mean that the results completely lack value. There is some valuable information within CPS estimates. Since this valuable information is not immediately salient, it must be extracted using statistical methods. In 1989, a time-series model was developed to provide labor force estimates for 39 small states and the District of Columbia.   In 1996, this approach was extended to the larger states as well. The reason for using the time-series modeling was to reduce the high variability in monthly CPS estimates due to small sample sizes.

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