Estimating the confidence intervals for DEA efficiency scores of Asia-Pacific airlines

Thanh Ngo and Kan Wai Hong Tsui ()
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Kan Wai Hong Tsui: Massey University

Operational Research, 2022, vol. 22, issue 4, No 8, 3434 pages

Abstract: Abstract Data envelopment analysis (DEA) is a popular non-parametric approach to examine performance and productivity of airlines; however, it could not provide statistical information such as confidence intervals on the estimated efficiency scores. We combined stochastic frontier analysis and DEA into a single framework to disentangle noise and ‘pure’ inefficiency from the DEA inefficiency scores and accordingly provide confidence intervals for the estimated efficiency scores. Monte-Carlo simulation verified that our novel model is a good alternative for the conventional DEA as well as the bootstrap DEA. Empirical application using Asia-Pacific airlines’ data (2008‒2015) shows that after accounting for the ‘pure’ random errors, the sampled Asia-Pacific airlines performed well during the study period but their ‘pure’ efficiency was declining, hence, there is still room for improvement.

Keywords: Data envelopment analysis and stochastic; Confidence intervals; Monte Carlo simulation; Bootstrap DEA; Asia-Pacific airlines; Efficiency levels (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s12351-021-00667-w

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