Quantifying Delay Externalities in Airline Networks

We develop a framework for quantifying delay propagation in airline networks. Using a large comprehensive data set on actual delays and a model-selection algorithm (elastic net) we estimate a weighted directed graph of delay propagation for each major airline in the US. We use these estimates to decompose the airline performance into "luck" and "ability." We find that luck may explain about 38% of the performance difference between Delta and American in our data. We further use these estimates to describe how network topology and other airline network characteristics (such as aircraft fleet heterogeneity) affect the expected delays. Finally, we propose a model of aircraft scheduler who decides which flights to delay and by how much. We then use the estimated model to evaluate counterfactual scenarios of investments in airport infrastructure in terms of their impact on delays.