Small-Area Estimates of School-Age Children in Poverty Interim Report 2, Evaluation of Revised 1993 County Estimates for Title I Allocations (1998) / Chapter Skim
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6. FUTURE RESEARCH AND DEVELOPMENT FOR COUNTY ESTIMATES
6. FUTURE RESEARCH AND DEVELOPMENT FOR COUNTY ESTIMATES
Pages 83-92
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From page 83... ...
are the scarcity of relevant data (e.g., IRS and food stamp program data are not currently available for school districts) ; the small size of many school districts (66% of the 15,227 school districts in 1989-1990 had a 1990 census total population of less than 10,000~; the variations among states in the ways in which school districts are defined (e.g., 26% of 1989-1990 school districts included certain grade levels only, and 27% of 1989-1990 school district boundaries crossed county lines)
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From page 84... ...
Longer term research will be useful for improving the county estimates in connection with the school district estimates to be delivered in October 2000 and later. Priorities for longer term research should consider the important changes that are likely to occur in the availability of data for modeling over the 1998-2002 period and beyond, which include: iTotal population estimates are needed because the legislation includes a provision that Title allocations for school districts that have less than 20,000 total population in a state may be aggregated, and the state may then reallocate the funds to school districts on the basis of data other than the Census Bureau's estimates.
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From page 85... ...
Beginning in 2003, the ACS will sample 250,000 households each month throughout the decade, for an annual sample size of about 3 million households (see Alexander, Dahl, and Weidman, 1997~. Changes in welfare programs and the accompanying data systems (especially those resulting from the 1996 Personal Responsibility and Work Opportunity Reconciliation Act)
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From page 86... ...
. Continued research and development for measurement error and time-series models will be needed to develop effective multivariate models for small-area poverty estimates that use multiple data sources for multiple time periods.
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From page 87... ...
Generally, evaluation work should be a regular part of the development of updated county and school district estimates of poor school-age children. Generalized Variance Function Modeling of CPS County Sampling Variances The total squared error, or residual variance, for the revised county model log number (under 18)
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From page 88... ...
It should lead to improved relative weights for use in the shrinkage estimation, although this is likely to have only a modest impact on the final estimates. It may reduce, or help explain, the variance heterogeneity of the standardized residuals from the county model as a function of the poverty rate and the CPS sample size; in particular, it may address the pattern of increasing standardized residual variances with CPS sample size.
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From page 89... ...
. It is important to study more thoroughly the discrepancies between the state and county models and to try out various methods for incorporating state effects in the county model in a more integrated way, such as through a two-level nested model.4 Another part of this work could be to examine the effect of using a single year of CPS data for the state model and 3 years of CPS data for the county model.
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From page 90... ...
Multivariate Approaches to County-Level Estimation The Census Bureau proposed, as an alternative to the separate use of CPS and census county regression equations (with the census equation being used only to estimate the model error variance for the CPS model) , a bivariate county regression model, in which the two dependent variables are the CPS and census estimates of poor school-age children.
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From page 91... ...
In the future this model could also incorporate data from the American Community Survey by adding equations for the estimates from that survey.5 Investigation of Discrete Variable Models that Use Counties with No Sampled Poor School-Age Children When using a logarithmic transformation of the number or proportion of poor school-age children as the dependent variable in a regression model, all counties in the CPS sample for which none of the sampled households has poor school-age children 304 of 1,488 counties for the 1993 model have to be removed from the regression analysis (see Chapter 2~. The dropped counties are generally smaller counties with small CPS sample sizes.
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From page 92... ...
These ideas and others need to be evaluated to determine if the lag between the time period of the estimates and the year of allocation of funds can be reduced. Improvements in Small-Area Population Estimates The Census Bureau has work under way, which should continue, to improve the procedures for estimating the population by age at the county level and to develop estimates of the total population and the school-age population for school districts.
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