Small Area Income & Poverty EstimatesModel-based Estimates for States, Counties, & School Districts |
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Intercensal population estimates and administrative tax return data are used as predictor variables in the models. The population estimates cover all residents, while the tax data cover people with filing requirements. The tax data omit two groups, the non-compliant and those without filing requirements. The non-compliant are not easily described by age or income class, but those without filing requirements are. People with low income and the elderly are less likely to have income that exceeds tax filing thresholds.
In the state-level models, the dependent variable, the variable predicted for each state, is the ratio of numbers of people in poverty to population as measured in the American Community Survey (ACS). To transform these ratios into estimated numbers of people in poverty, we multiply each estimated ratio by a demographic estimate of the population as covered by the ACS. The 2005 ACS universe does not include group quarters populations, such as residents of nursing homes, college dormitories, correctional institutions, and other group quarters populations. Accordingly, household population estimates from the Population Estimates Program, which also exclude group quarters populations, are used to transform the poverty ratios.
Finally, we use estimates of the poverty universe at both the state and county levels to compute the percentages of people in poverty shown in the tables of SAIPE estimates. We form poverty universe estimates from the household population estimates by adjusting them to exclude other population subgroups (e.g., foster children under age 15) and to limit the estimates of the number of children to related children. We describe these adjustments in more detail in the section on Denominators for State and County Poverty Rates.
For information on population estimates used before 2005, see Intercensal Estimates of the Population: 1993 - 2004.
More on the Population Estimates Program.