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The American Community Survey Summary of a Workshop (2001) / Chapter Skim
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2. Combination of Information Across Areas
Pages 7-11

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From page 7...
... Using the census, administrative records, other household surveys, and now the ACS, statistical models hold the promise of providing timely estimates for smaller areas and groups than would otherwise be possible. Combining information is an area in which statistics has recently made important advances (see, e.g., National Research Council, 19921.
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From page 8...
... For some large areas, direct estimates from a relevant household survey are likely to be recognized as standard values given their lack of measurement error (but possibly appreciable variance, depending on the area) , so agreement of indirect estimates incorporating ACS information with these standards would have the advantage of consistency with an accepted estimate.
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From page 9...
... Further, Bayesian methods can address nonstandard goals, which is relevant to a topic addressed in Chapter 3the use of ACS-based estimates for input into fund allocation formulas, which often have nonstandard forms and therefore implicitly nonstandard loss functions for the associated estimates, e.g., fund allocation formulas that have eligibility thresholds. Though the Bayesian approach has these and other attractive properties, due to the national importance of the ACS in providing estimates for various official purposes, its use in this context must have good frequentist properties (good objective performance)
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From page 10...
... In the particular application of small-area estimation involving the ACS, based somewhat on the experience of the small-area poverty estimates panel mentioned above, fixed-effects regression modeling combined with empirical and hierarchical Bayesian and random-effects modeling should be very effective in a wide variety of specific problems. Given that one is simply aggregating lower-level estimates to provide estimates at higher levels of aggregation, a natural concern is that the aggregate estimates will not approximately equal the direct estimates at higher levels of aggregation.
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From page 11...
... While Bayes' hierarchical modeling can be used to incorporate information from administrative records, the use of such records requires that they be comparable across regions. This can be checked by keeping track of differences in programmatic rules and methods, but it can also be checked by comparing administrative record tabulations with survey data pooled over time, a technique similar to that used in the work by the panel on small-area estimates of poverty.
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Key Terms

  • direct estimates
  • combining information
  • administrative records
  • allocation formulas
  • statistical models

  • linear models
  • fund allocation
  • household surveys
  • posterior distribution
  • combine information

  • hierarchical linear
  • measurement error
  • bayesian models
  • loss functions
  • monte carlo

  • combine estimates
  • provide estimates
  • indirect estimates
  • closely approximate
  • hierarchical modeling

  • chain monte
  • incorporate information
  • generalized linear
  • markov chain
  • component modeling

  • finest level
  • comparing administrative
  • combined using
  • appropriately reflect
  • inform users


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