Aggregate Versus Disaggregate Data in Measuring School Quality |
| |
Authors: | Francisca G-C Richter B Wade Brorsen |
| |
Institution: | (1) Department of Economics, Cleveland State University, Rhodes Tower Room No. 1704, Cleveland, OH 44115, USA;(2) Department of Agricultural Economics, Oklahoma State University, 414 Ag Hall, Stillwater, OK 74078-6026, USA |
| |
Abstract: | This article develops a measure of efficiency to use with aggregated data. Unlike the most commonly used efficiency measures,
our estimator adjusts for the heteroskedasticity created by aggregation. Our estimator is compared to estimators currently
used to measure school efficiency. Theoretical results are supported by a Monte Carlo experiment. Results show that for samples
containing small schools (sample average may be about 100 students per school but sample includes several schools with about
30 or less students), the proposed aggregate data estimator performs better than the commonly used OLS and only slightly worse
than the multilevel estimator. Thus, when school officials are unable to gather multilevel or disaggregate data, the aggregate
data estimator proposed here should be used. When disaggregate data are available, standardizing the value-added estimator
should be used when ranking schools. |
| |
Keywords: | Data aggregation Error components School quality |
本文献已被 SpringerLink 等数据库收录! |
|