MAKKAR, Sandhya, KHAN, Arif, LAL, Adit and MANOHARAN, Geetha (2022). Predicting air passenger traffic during Covid-19 & its economic impact. AIP Conference Proceedings, 2418 (1): 020032. [Article]
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Predicting Air Traffic.pdf - Accepted Version
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Predicting Air Traffic.pdf - Accepted Version
Available under License All rights reserved.
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Abstract
Most governments have implemented restrictive policies in response to the global coronavirus outbreak to curb the pandemic and reduce the number of deaths. Air traffic suspension is one of the most important restrictive policies in terms of reducing global migration for short period, though it has major and long term impact on all economies of the world.The objective of this study is to analyse the impact global air travel ban on various aviation sectors. This required authors to collect and pre-process the passengers traffic worldwide via flights. Based on historical data from 1970 till 2019 (Source- data.worldbank.org), a predictive model is prepared and implemented to get a clear picture of the losses faced by the aviation sector in terms of air passenger traffic. Further we will be comparing the forecasted values with the real time values in order to study the effect of air travel ban on aviation and its supported sectors. In addition, a study of the economic impact of the air travel bans and the cumulative impact of the Covid-19 pandemic is being conducted by looking at real GDP levels (in percentages) and future estimates, measuring them all in percentages for the world economy and various industrialized countries, developed markets, and developing nations, and a comparison being made and then further analyzing them. In the near term, some countries will be more affected than others, and most airline businesses will lose because of the travel ban. We hope that these early findings will aid in the development of informed policies and exit plans for this global crisis.
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