Small-Area Estimates of School-Age Children in Poverty Interim Report 3 (1999) / Chapter Skim
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5 Future Research and Development
5 Future Research and Development
Pages 83-96
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From page 83... ...
In addition, research is needed to take account of likely future developments in the availability and characteristics of data sources that have implications for the modeling effort and to work on longer term modeling issues. Continued work to improve the county model is important not only for county estimates, but also to improve school district estimates that are developed by using the basic synthetic shares estimation procedure.
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From page 84... ...
data for use in small-area estimation models; · the income and poverty estimates for small areas that will be available from the 2000 decennial census long-form sample of about 17 million households (likely to be available in 2002 for counties but not until later for school districts) ; and · the planned introduction of the American Community Survey (ACS)
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From page 85... ...
SHORT-TERM PRIORITIES County Estimates The panel identified seven types of research that should be pursued as a priority to determine if the current estimation procedure for counties can be improved: modeling of CPS county sampling variances; estimation of model error and sampling error variance in the state model; methods to incorporate state effects in the county model; discrete variable models that include counties in the CPS sample that have no sampled households with poor school-age children; ways to reduce the time lag of the estimates; evaluation of food stamp and other input data; and large category differences and residual patterns for the state and county models. This research, much of which the Census Bureau has planned, should be conducted and the results fully evaluated well before the next delivery of updated county estimates of poor school-age children, scheduled for October 2000.
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From page 86... ...
In addition, the Census Bureau should pursue an alternative approach, which is to estimate the CPS sampling variances for counties with adequate sample size on the basis of direct calculations of these variances that take account of the clustered sample design within these counties, and then use a generalized variance function for modeling the sampling variances for all counties with CPS sampled households. With this approach, the model error variance is calculated by subtracting the total sampling variance from the total squared error.
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From page 87... ...
, suggested that state effects may be present and that further research on a random state effects model should be conducted. Discrete Variable Models that Use Counties with No Sampled Poor SchoolAge Children When using a logarithmic transformation of the number of poor school-age children as the dependent variable in the county regression model, all counties in the CPS sample for which none of the sampled households have poor school-age children (262 of 1,247 counties for the 1995 model)
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From page 88... ...
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. Evaluation of Food Stamp and Other Input Data Regular evaluation of the continued suitability of food stamp and other data for input to the state and county models is important for the Census Bureau's small-area estimation program.
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From page 89... ...
2The evaluations conducted to date of the county estimates include examination of the residual patterns from the regression model, comparisons of the model estimates for 1989 with 1990 census estimates, and comparisons of the model estimates for 1989, 1993, and 1995 with aggregate CPS estimates. Another evaluation that could help determine what portion of the errors in the county estimates is due to problems with the model-rather than measurement differences and sampling variability-is to fit the model to 1990 census data (prior to shrinkage and raking to the state model)
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From page 90... ...
Three important areas for research are: investigation of methods to reduce the variance of the 1990 census estimates of poor school-age children; use of school enrollment data to improve estimates of the total number of school-age children; and investigation of the possible use of National School Lunch Program data to improve estimates of poor school-age children. Reducing the Variance of the 1990 Census Estimates of Poor School-Age Children Because so many school districts are so small in size, the 1990 census estimates of poor school-age children, which derive from the long-form sample, are subject to high sampling variability.
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From page 91... ...
If successful, smoothing procedures might substantially improve the estimation of census school-age poverty rates in small school districts. They would add some bias because county poverty rates differ from poverty rates for school districts contained within them, but they could potentially substantially reduce variance, thereby improving mean square error.
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From page 92... ...
Nonetheless, participation in the National School Lunch Program is an indicator of low income, and it seems worthwhile to pursue for other states the research that the panel undertook for New York. The Census Bureau may be able to work through its state data centers for selected states to obtain school lunch data by district for 1989-1990 to evaluate whether within-county school lunch participation shares in 1989-1990 produce estimates of poor school-age children in 1989 that are more accurate than those produced from the 1980 census-based shares.
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From page 93... ...
For the state model, the Census Bureau has initiated work on a multivariate approach to incorporating the data from several years of the CPS, instead of just one year, into the regression equation (see Otto and Bell, 1997~. For the county model, the Census Bureau developed, 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)
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From page 94... ...
Continued research and development on 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.6 A specific research issue is to determine how best to use the 2000 census information, which will have lower sampling variance but possibly substantial measurement bias and which may be biased if the economic conditions during the census reference period differ markedly from the period for which estimates are needed. In order to learn as much as possible about the measurement differences between the census, the March CPS, and the ACS, the Census Bureau should plan now for an exact match of the 2000 census with both the March 2000 CPS and the national ACS sample of about 70,000 households that will be in the field in that year.
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From page 95... ...
With the Master Address File that will be completed for the 2000 census, it should be possible to geocode most federal tax return data to the school district level. In fact, if a high proportion of tax return addresses can be geocoded in the near future, even before the census itself is completed, that information could be used to improve the current synthetic shares estimation method.8 It may also be possible to undertake a federalstate cooperative effort to provide food stamp data that are geocoded to school districts.
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From page 96... ...
No small-area estimates should be published without full documentation. Such documentation is needed for analysts both inside and outside the Census Bureau to judge the quality of the estimates and to identify areas for research and development to improve the estimates in future years.
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