Absolute Technical Efficiency Indices
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| author | Larbi, Montacer Ben Cheikh Belkhiria, Sina |
| author_facet | Larbi, Montacer Ben Cheikh Belkhiria, Sina |
| contents | Technical efficiency indices (TEIs) can be estimated using the traditional stochastic frontier analysis approach, which yields relative indices that do not allow self-interpretations. In this paper, we introduce a single-step estimation procedure for TEIs that eliminates the need to identify best practices and avoids imposing restrictive hypotheses on the error term. The resulting indices are absolute and allow for individual interpretation. In our model, we estimate a distance function using the inverse coefficient of resource utilization, rather than treating it as unobservable. We employ a Tobit model with a translog distance function as our econometric framework. Applying this model to a sample of 19 airline companies from 2012 to 2021, we find that: (1) Absolute technical efficiency varies considerably between companies with medium-haul European airlines being technically the most efficient, while Asian airlines are the least efficient; (2) Our estimated TEIs are consistent with the observed data with a decline in efficiency especially during the Covid-19 crisis and Brexit period; (3) All airlines contained in our sample would be able to increase their average technical efficiency by 0.209% if they reduced their average kerosene consumption by 1%; (4) Total factor productivity (TFP) growth slowed between 2013 and 2019 due to a decrease in Disembodied Technical Change (DTC) and a small effect from Scale Economies (SE). Toward the end of our study period, TFP growth seemed increasingly driven by the SE effect, with a sharp decline in 2020 followed by an equally sharp recovery in 2021 for most airlines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_04590 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Absolute Technical Efficiency Indices Larbi, Montacer Ben Cheikh Belkhiria, Sina Econometrics Technical efficiency indices (TEIs) can be estimated using the traditional stochastic frontier analysis approach, which yields relative indices that do not allow self-interpretations. In this paper, we introduce a single-step estimation procedure for TEIs that eliminates the need to identify best practices and avoids imposing restrictive hypotheses on the error term. The resulting indices are absolute and allow for individual interpretation. In our model, we estimate a distance function using the inverse coefficient of resource utilization, rather than treating it as unobservable. We employ a Tobit model with a translog distance function as our econometric framework. Applying this model to a sample of 19 airline companies from 2012 to 2021, we find that: (1) Absolute technical efficiency varies considerably between companies with medium-haul European airlines being technically the most efficient, while Asian airlines are the least efficient; (2) Our estimated TEIs are consistent with the observed data with a decline in efficiency especially during the Covid-19 crisis and Brexit period; (3) All airlines contained in our sample would be able to increase their average technical efficiency by 0.209% if they reduced their average kerosene consumption by 1%; (4) Total factor productivity (TFP) growth slowed between 2013 and 2019 due to a decrease in Disembodied Technical Change (DTC) and a small effect from Scale Economies (SE). Toward the end of our study period, TFP growth seemed increasingly driven by the SE effect, with a sharp decline in 2020 followed by an equally sharp recovery in 2021 for most airlines. |
| title | Absolute Technical Efficiency Indices |
| topic | Econometrics |
| url | https://arxiv.org/abs/2404.04590 |