• Ordinary Least Squares (OLS). OLS is a method
relating passenger traffic to air travel prices,
income levels and other variables, while minimising
the variance (randomness) of the estimates. The
regression analysis allows the relationship between
traffic and air travel prices to be isolated and
quantified while controlling for other factors that may
impact air travel, such as GDP, population levels, route
distance and seasonality.
• Two-Stage Least Squares (2SLS). 2SLS is often
used to improve the consistency of elasticity estimates
when explanatory variables are believed to be
correlated with the regression model’s error term.
• Autoregressive Distributed Lag (ARDL). An
autoregressive ARDL model uses similar explanatory
variables to the OLS model, but also uses lagged
values of the traffic variable. The inclusion of lagged
values accounts for the slow adjustment of supply (in
the form of capacity) to changes in the explanatory
variables.