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Using the bootstrap to evaluate forecasting equations
Author(s) -
Peters Stephen C.,
Freedman David A.
Publication year - 1985
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980040302
Subject(s) - monte carlo method , econometrics , parametric statistics , computer science , econometric model , standard error , statistics , mathematics
The bootstrap, like the jack‐knife, is a technique for estimating standard errors. The idea is to use Monte Carlo simulation, based on a non‐parametric estimate of the underlying error distribution. The bootstrap will be applied to an econometric equation describing the demand for energy by industry, to determine multi‐period forecasting error and choose among competing specifications. The delta method for estimating forecast errors turns out to be too optimistic by a factor of 2.