SMALL-AREA STUDENT ENROLLMENT PROJECTIONS BASED ON A MODIFIABLE SPATIAL FILTER

This paper describes a new method for making short-term (4-8 yr) stude nt enrollment projections by grade and ethnic group for small geograph ic areas. The method links an information system that contains student characteristics acid home addresses with a commonly available digital geographic database (TIGER) to create a geographic accounting table o f student residences by census blocks. Progression rates of students f rom one grade to the next are estimated for each small area by aggrega ting student residences, by grade, for a 3 yr period over a larger are a (the modifiable spatial filter) centered on the small area. The size of the filter area depends on the geographical distribution of studen ts, a user-specified student threshold value, and a maximum distance c onstraint. The progression rates are applied to the student population of each census block in a grade-cohort component projection model. Pr ojections of the number of students enrolled in each grade for any def ined geographical area are made by aggregating the projections for the census blocks in the area. We show that results using this method are consistent with those from the same model applied to school attendanc e area enrollment data, whereas results using the small-area data with out the filter are not. This result supports our conclusion that the m ethod is reliable for making grade-specific enrollment projections, fo r which past enrollment data do not exist, such as those for new schoo ls or for revised attendance areas. We describe the techniques used to link the student information system to the digital map, compute the s patial filter statistics efficiently, and make projections for new sch ool attendance areas. We have used the modifiable spatial filter metho d for projecting student populations and modifying attendance area bou ndaries in two Iowa school districts.