amples. Long-form-sample estimates enter indirectly into the allocation of funds under Title I of the No Child Left Behind Act (estimated $12.7 billion obligated in fiscal 2005). This program allocates funds to school districts to meet the needs of educationally disadvantaged children by formulas that include estimates of poor school-age children. In the past these estimates were obtained from the most recent census long-form sample; currently, more up-to-date estimates are obtained from statistical models developed by the Census Bureau in its Small Area Income and Poverty Estimates (SAIPE) program.3

The SAIPE state- and county-level models include long-form-sample poverty estimates as one input together with more up-to-date information from administrative records to predict school-age poverty from a 3-year average of data from the Current Population Survey Annual Social and Economic Supplement (CPS ASEC). The school district-level model uses the previous census long-form-sample estimates of within-county school district shares of poor school-age children to apply to the updated county model estimates of the number of poor school-age children. The SAIPE program produces annual estimates with a 2-year lag between release and the estimates’ income reference year; the lag is due to delays in acquiring administrative records that are required for the modeling.

Using ACS Estimates in Formulas

Because the 2010 census will not include a long-form sample, policy makers and program managers must develop strategies for introducing ACS estimates into funding program allocation formulas that previously used long-form-sample estimates and decide whether such a change will require legislation or can be handled by regulation. The primary benefits of using ACS estimates are that they will be more timely and up-to-date and probably of higher quality than estimates from the long-form sample, so that the resulting fund allocations will more accurately reflect the distribution of needs among eligible areas.4 Still, the ACS estimates will have higher sampling error than long-form-sample estimates.

Role of Policy Makers The role that policy makers and program managers play in decisions about the use of ACS estimates in allocation formulas


See National Research Council, 2000a;


This discussion does not address whether the variables in a formula (in the absence of data quality concerns) produce the most equitable fund distributions in light of a program’s original goals (see National Research Council, 2003a). The need to replace long-form-sample estimates with ACS estimates could trigger reconsideration of the variables and other features in a formula, but that is outside the panel’s charge.

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