THE SMALL AREA INCOME AND POVERTY ESTIMATION MODEL

The SAIPE project is an ongoing Census Bureau program to estimate numbers of low-income school-age children by state, county, and ultimately school district, based on data from the CPS, tax information, the Food Stamp Program, and the latest decennial census. SAIPE has a long history. It has been the subject of extensive development at the Census Bureau and evaluation by a previous National Research Council panel. The SAIPE approach to county-level estimates was developed in response to legislation in 1994 (National Research Council, 2000, p. 3) calling for the Census Bureau to supply “updated estimates” of county-level child poverty for use in allocating Title I education funds to counties in 1997-1998 and 1998-1999, and thereafter to provide estimates at the school district level.

William Bell pointed out at the workshop that the SAIPE was designed to respond to the prototypical small-area estimation problem that although some surveys produce reliable estimates at national level, subnational (e.g., state or county) estimates are desired, and the sample is not large enough to support the small-area estimates. The idea is to apply a statistical model to “borrow information” across areas and from other data sources to improve estimates. The key features in a successful model are the other data sources used, the form and underlying assumptions of the model, and diagnostics that can be used to check model assumptions.

The SAIPE model follows this form, using as data sources sample surveys, administrative records, and census data. Except for a complete enumeration from the census, all of these sources have errors of one of three types: (1) sampling error, that is, the difference between the estimate from the sample and what is obtained from a complete enumeration done in the same way; (2) nonsampling error, that is, the difference between what is obtained from a complete enumeration and a population characteristic of interest (“desired target”); and (3) target error, that is, the difference between what a data source is estimating (its target) and the desired target. As an example of target error, Bell pointed out that the model uses food stamp participants to measure poverty, but Food Stamp Program participant data are only an approximation of the desired target.

Bell summarized the strengths and weaknesses of the main data sources for SAIPE purposes. The CPS, the primary national survey measuring population and poverty each year, provides the SAIPE program with national county-level child poverty estimates, through sample-weighted estimates of the numbers and the proportion of poor children among children aged 5-17 related to the primary householder (poor related school-age children). Since 2005, these data have been obtained from the ACS. Both the CPS and the newer ACS produce direct poverty estimates that are up to date but that have large sampling errors for



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