Stochastic Modelling of Air Passenger Volume During the COVID-19 Pandemic and the Financial Impact on German Airports

Author(s): B. Wolle

The current COVID-19 pandemic has hit most sectors of the world and has led to many industries coming to a standstill. It has led to restrictions of movement and travel ban. As a result of these restrictions, transport sector especially in aviation has impacted badly. A scenario-based analysis of the impact of the pandemic on the earnings before interest, tax, depreciation, and amortization (EBITDA) for airport operators is presented. Several causal factors affecting the air traffic volume are considered, including travel restrictions, consumer confidence, lack of international cooperation, and economic situation of the aviation industry. Stochastic equations with the standard Wiener measure are applied for modelling the air passenger volume in a given time frame. Based on a correlation analysis, the dependence of the EBITDA on the air passenger volume is modelled. As an application, for the two largest German airports, Frankfurt and Munich, the EBITDA is projected for different scenarios.