US e-commerce: COVID-19 Effect on Alibaba and Amazon

Published: 29 October 2021| Version 1 | DOI: 10.17632/bcjwyrdr57.1
Contributor:
Alexey Mikhaylov

Description

The data includes total e-trade volume in the USA from 1992 to 2021, uploaded from Federal Reserve Economic Data API (FRED). The paper uses SARIMA class model and state space methods based on the theory of ecosystems. To conduct this analysis, the research resorts to the methodology of time varying regression in order to detect structural breaks that occurred in 2020. This paper proves the idea that the effect of COVID-19 on Alibaba and Amazon was weaker than on companies with smaller market capitalization. These findings suggest that the structure of e-commerce open innovation in the USA is much more complex than the simplistic view of global trade. This paper describes the correlation between COVID-19 measures and e-commerce open innovation in the USA in the last years. The current trend of online shopping is expanding and developing countries should either adjust to these changes or their financial and ecological stability will be under question in the long term.

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Categories

Economics, Time Series Modeling

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