Using Multiple Methods to Provide Prediction Bands of K-12 Enrollment Projections

Richard S. Grip () and Meghan L. Grip ()
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Richard S. Grip: Statistical Forecasting LLC
Meghan L. Grip: University of Rochester

Population Research and Policy Review, 2020, vol. 39, issue 1, No 1, 22 pages

Abstract: Abstract Often, demographers charged with projecting enrollments for school districts are asked to provide a range of future enrollments, as point estimates are not satisfactory to stakeholders. Three New Jersey school districts in varying populations sizes (small, medium, and large) were used to project enrollments 5 years into the future. Prediction bands were created using empirically-based methods, whereby confidence intervals were constructed, and by model-based methods, which utilizes stochastic forecasting. While stochastic forecasting is typically used in projecting the population of large geographies such as states or countries, it has rarely been used for a small level of geography such as a school district. The results showed that confidence intervals may have limited utility in projecting an enrollment range for larger districts, particularly in the short term (1–2 years). Prediction intervals using stochastic forecasting have limited utility in school district projections, regardless of school district size, as the prediction bands are too wide to allow for any meaningful use of the data.

Keywords: Enrollment projections; Population forecasting; Confidence intervals; Forecast accuracy; Stochastic forecasting (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11113-019-09533-2

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