Examines the use of stochastic frontier estimation of constant elasticity of substitution (CES) cost function to measure differences in efficiency among British universities. (Contains 28 references.) (PKP)

Explores whether flexible nonlinear models (including neural networks and genetic algorithms) can reveal otherwise unexpected patterns of relationship in typical school-productivity data. Applying three types of algorithms alongside regression modeling to school-level data in 183 elementary schools proves the hypothesis and reveals new directions…

Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…

With over 260 schools and 200,000 students, Houston has one of the nation's largest school systems. Population growth, geographic population shifts, and historic policies have all contributed to an undesirable distribution of students within the district. This paper describes an algorithm's use in evaluating competing school capacity plans and…