Data for: Learning and Forgetting in the Jet Fighter Aircraft Industry


Data set for the paper entitled "Learning and forgetting in the jet fighter aircraft industry". Data set includes flayaway cost and number of procurement units for three types of aircraft: F-22A Raptor, F-35A Lighnight II, and A/F-18-E/F Super Hornet. Data set also includes military procurements deflator. Annual data. Samples periods: 2000-2009 for the Raptor, 2007-2015 for the Lighnight II, and 1997-2013 for the Super Hornet. Data set includes all information for estimating learning curves and forgotting as presented in the corresponding paper. Data set also includes procument units and flyaway cost for the EA-18G Glowler, which it is a posterior modification of the Super Hornet for electronic warfare. These data are not included in the research paper, but they can be used to check that flyaway cost is constant as production accumulated, and no learning-by-doing process is observed for this particular aircraft (as all learning was acquired during the previous production of the Super Hornet).

Abstract: A recent strategy carried out by the aircraft industry to reduce the total cost of new generation fighter has consisted in the development of a single airframe with different technical and operational specifications. This strategy has been designed to reduce costs in the Research, Design, and Development phase with the aim of reducing the final unitary price of aircraft. This is the case of the F-35 Lightning II, where three versions, with significant differences among them, are produced simultaneously based on a single airframe. Whereas this strategy seems to be useful to cut down pre-production sunk costs, remains key to study their effects on production costs. This paper shows that this strategy can imply larger costs in the production phase by reducing learning acquisition and hence, the total effect on the final unitary price of the aircraft is indeterminate. Learning curves are estimated based on the flyaway cost for the latest three fighter aircraft models: The A/F-18E/F Super Hornet, F-22A Raptor, and the F-35A Lightning II. We find that learning rates for the F-35A are significantly lower (an estimated learning rate around 9%) than for the other two models (around 14%).

Metadata Access
Creator Bongers, A.
Publisher Data Archiving and Networked Services (DANS)
Publication Year 2017
Rights info:eu-repo/semantics/openAccess;License:
Language English
Resource Type Dataset
Discipline Economics
Temporal Point 2017-06-26T11:59:59Z