  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.
