ments, not researchers’ needs. This situation might be remedied by setting up a licensing system similar to that used by the National Center for Education Statistics (Picus 1997). Researchers’ patience and willingness to develop strong personal relationships with data-production staff are essential.One limitation on school-level data is the difficulty of comparing data across states (Picus 1997). Some researchers believe equity and effectiveness would be better served if a national system of student-level resource measures could be developed (Berne and Stiefel 1995). Others insist that a student-poverty factor be added to funding analyses (Berne 1995, Consortium 1995, Biddle 1997). Hertert (1995), addressing national equity concerns, sees the NCES and Census Bureau’s jointly developed Common Core of Data (containing standardized, comparable revenue and expenditure data for the nation’s 15,000 districts for 1989-90) as a good first step for measuring interstate disparities. HOW CAN THEY BE IMPROVED?Some research, like Crampton's study of New York schools, has isolated the types of expenditures that matter in the school-productivity equation. A good example is Harold Weglinsky's study (1997), which found that fourth- and eighth-graders' math achievement was positively associated with lower student-teacher ratios and with expenditures on instruction and school-district administration. Expenditures on facilities, recruitment of highly educated teachers, or school-level administration were not significantly related. Another kind of efficiency research explores schools' resource-allocation practices. David H. Monk (1996) examined how teacher resources are distributed and utilized at various levels of the New York State K-12 system. The study found a 55 percent increase in secondary-level special-education instructional resources between 1983 and 1992, alongside modest increases in allocations of science and math teache...
