Comparison of bootstrap estimation intervals to forecast arithmetic mean and median air passenger demand. Issue 7 (19th May 2017)

• Record Type: Journal Article
• Authors: Carmona-Benítez, Rafael Bernardo; Nieto, María Rosa
• Is Part Of: Journal of applied statistics. Volume 44:Issue 7(2017)
• Page Start: 1211
• Page End: 1224
• Publication Date: 2017-05-19
• Subjects: Air passenger demand -- forecast -- percentile method -- bias corrected -- bias corrected accelerated method -- bootstrap -- median -- arithmetic mean; 62F40; C150; Statistics -- Periodicals; 519.5
• DOI: 10.1080/02664763.2016.1201794
• Languages: English
• ISSNs: 0266-4763

Abstract

ABSTRACT: The aim of this paper is to compare passenger (pax) demand between airports based on the arithmetic mean (MPD) and the median pax demand (MePD). A three phases approach is applied. First phase, we use bootstrap procedures to estimate the distribution of the arithmetic MPD and the MePD for each block of routes distance; second phase, we use percentile, standard, bias corrected, and bias corrected accelerated methods to calculate bootstrap confidence bands for the MPD and the MePD; and third phase, we implement Monte Carlo (MC) experiments to analyse the finite sample performance of the applied bootstrap. Our results conclude that it is more meaningful to use the estimation of MePD rather than the estimation of MPD in the air transport industry. By carrying out MC experiments, we demonstrate that the bootstrap methods produce coverages close to the nominal for the MPD and the MePD.