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The U.S. Census Bureau’s Current Population Survey is one of the oldest and largest household surveys in the United States. Since 1940, it has produced monthly statistics on labor force information. The Current Population Survey interviews about 72,000 households each month to estimate totals of persons unemployed, employed and not in the labor force, leading to the official estimate of the national unemployment rate.
The Current Population Survey applies a stratified two-stage cluster sampling design to select a representative sample of U.S. households. A housing unit selected for the sample is interviewed for four consecutive months, rotated out for eight months, and then interviewed for another four months. This approach aims to develop overall monthly estimates while also tracking monthly and annual changes among the sampled households.
To manage these design features, the survey team has long relied on cutting-edge research on sampling, weighting and variance estimation. Given several key variables that are beyond our control such as budgets, computational power and stakeholders’ needs, the survey team must be sufficiently agile to adapt to changes. This nimble approach requires a strong understanding of the underlying theory, an ability to adapt the survey quickly, and an opportunity to hone our methods under peer review.
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