Airline network response to government policies: COVID-19 and Russian airspace closure

Abstract

This study examines how airlines responded to two major external shocks: the COVID-19 pandemic and Russian airspace closure. Using monthly international schedules data from 2018 to 2024 on airline networks and government stringency measures, we apply both panel regression model based on Driscoll-Kraay standard errors and panel vector autoregression (PVAR) model, to analyze the effects of these disruptions on key airline network measures, including mean distance, clustering coefficient, network diameter, and network efficiency. Our findings indicate that increased stringency exposure during the pandemic leads to a contraction in airline network structures, with reduced global connectivity and network efficiency. In contrast, the closure of Russian airspace forces airlines to adopt longer routes, leading to an increase in mean distances but an improvement in network efficiency as airlines optimized their rerouted operations. The dynamic analysis reveals persistence in airline network characteristics, with significant long-term effects resulting from these external shocks. These findings contribute to the existing literature on airline network resilience and highlight the need for strategic planning to address both public health and geopolitical disruptions. The study also presents important policy implications, suggesting that governments and industry stakeholders should develop frameworks for enhancing network adaptability and ensuring global connectivity in the face of future crises.