Airbnb Economic Loss Due to COVID-19 in 50 Non-Metropolitan Cities: A Vector Autoregression Analysis

Loading...
Thumbnail Image

Degree type

Discipline

Subject

airbnb
autoregression
covid-19
market analysis
sharing economy
Business
Business Analytics

Funder

Grant number

License

Copyright date

Distributor

Related resources

Contributor

Abstract

Prior to the COVID-19 pandemic, Airbnb achieved tremendous growth in rural America in fostering the democratization of accessible travel to areas without hospitality infrastructure. Due to COVID-19 lockdowns and restrictions, the travel industry sustained more significant supply and demand shocks than the overall economy. Using a vector autoregression analysis of Airbnb data in 50 selected non-metropolitan cities in the Midwest and South from July 2017 to June 2020, we first evaluated Airbnb revenue growth in 2019 and forecasted its continued growth in each city for the first half of 2020. This modeling of Airbnb growth enabled an estimate of Airbnb revenue loss in the first half of 2020 due to the disruption by the COVID-19 pandemic. Prior to the COVID-19 pandemic, these emerging Airbnb markets, characterized by small to medium sized cities, exhibited a high year-over-year revenue growth of 61% in 2019 and were forecasted to accelerate the growth in 2020 to 89%. Unfortunately, the pandemic halted the growth and led to a quite uniform 24% loss based on the forecasted revenue. There was little to no correlation between the forecasted economic loss percentages and state differences, city- specific characteristics used in this study, or known COVID-19 cases. This study has provided a comprehensive report of Airbnb growth across a variety of emerging markets both pre-COVID- 19 and post-COVID-19 and assessed the economic impact of the pandemic.

Date Range for Data Collection (Start Date)

Date Range for Data Collection (End Date)

Digital Object Identifier

Series name and number

Publication date

2020-01-01

Volume number

Issue number

Publisher

Publisher DOI

Journal Issues

Comments

Recommended citation

Collection