S. Juan et F. Lantz, Application of bootstrap techniques in econometrics: the example of cost estimation in the automotive industry, OIL GAS SCI, 56(4), 2001, pp. 373
Citations number
23
Categorie Soggetti
Geological Petroleum & Minig Engineering
Journal title
OIL & GAS SCIENCE AND TECHNOLOGY-REVUE DE L INSTITUT FRANCAIS DU PETROLE
Bootstrap methods applied in regression models help to approximate the dist
ributions of the coefficients and the prediction errors. In this paper, we
apply bootstrap techniques to determine prediction intervals from econometr
ic models when the regressors are known. Ve investigate problems associated
with their application: determining the number of replications, choosing t
he method to calculate the least-squares estimator (pseudo-inverse or inver
se) and sorting algorithm? of the statistic of interest. This investigation
arises from? the need in the automotive industry to predict costs in the e
arly phases of development of a new vehicle. Generally, the sample size is
small and the model's error term of the model is not Gaussian. Consequently
, bootstrap techniques strongly improve prediction intervals by reflecting
the original distribution of the data. Two examples (engine and fuel tank)
illustrate the technique.