Bootstrapping an econometric model: some empirical results
Technical Report
·
OSTI ID:5860106
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 model describing the demand for capital, labor, energy, and materials. The model is fitted by three-stage least squares. In sharp contrast with previous results, the coefficient estimates and the estimated standard errors perform very well, and the model also does well in policy analysis mode. In straight forecasting mode, however, the model's forecasts show serious bias and large random errors.
- Research Organization:
- California Univ., Berkeley (USA). Dept. of Statistics; Stanford Univ., CA (USA). Dept. of Statistics; Oak Ridge National Lab., TN (USA)
- DOE Contract Number:
- AC03-76SF00098; W-7405-ENG-26
- OSTI ID:
- 5860106
- Report Number(s):
- DOE/NBB-0045; ON: DE83017703
- Resource Relation:
- Other Information: Portions are illegible in microfiche products
- Country of Publication:
- United States
- Language:
- English
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