Our Methodology
What methodology is used to calculate Airbnb's economic impact metrics?
Our economic impact metrics are generated using the IMPLAN calculation process to estimate the economic impact of Airbnb in a specific geography. For this project, the model integrates Airbnb Host earnings and guest spending, based on a survey of guests who booked a listing through Airbnb and stayed in the specific geography in the year of the report.
The model includes direct, indirect, and induced economic contribution as defined below:
- Direct Economic Effects: Refers to the immediate effects of economic activity. In tourism, it means spending by tourists on goods and services such as accommodation, meals, transportation, groceries, and souvenirs.
- Indirect Economic Effects: Refers to the secondary effects generated by the initial spending in related industries that supply goods and services to the primary industry. These industries provide inputs or support services necessary for the functioning of the primary industry.
- Induced Economic Effects: Refers to tertiary effects from increased household spending by employees in the directly and indirectly affected industries. This includes spending of wages earned by employees in restaurants and other establishments as a result of guests' and hosts' economic activity.
- Total Economic Contribution to GDP: The contribution to GDP in terms of value added generated by Airbnb activity as a result of direct, indirect, and induced effects.
- Total Jobs Supported: Number of full-time, part-time, and seasonal jobs supported by Airbnb-generated output, including direct, indirect, and induced effects.
- Total Tax Revenue: Includes (i) total dollar value of taxes associated with hosts' income and spending and economic activity from guests visiting local businesses. These taxes are not Airbnb's liability and include Taxes on Production & Imports (TOPI), social insurance taxes, personal taxes, and corporate profit taxes; (ii) also includes tax revenue from hosting, the total dollar value of taxes directly associated with hosting as part of (net) Gross Booking Value.
Why might I see different data for related metrics throughout this site?
We believe it's important to evaluate data and research from both Airbnb and external groups to comprehensively understand how Airbnb intersects with economics, housing and other key societal areas.
We commission research groups with third-party firms like Oxford Economics, Fraunhofer Institute, Ernst & Young, and others, each of whom use individualized research methodologies. Having a third-party perspective on Airbnb data helps ensure research findings are credible, transparent, and reproducible. This level of rigor ensures this collective research is accurate, builds trust and withstands scrutiny.
What methodology is used to calculate Airbnb host and guest community metrics?
Host and guest data comes from a combination of self-reported feedback on the Airbnb platform, survey responses, and bookings on Airbnb. This data is associated with individual localities based on the location of Airbnb listings, where hosts reside, where guests reside or where guests originate from when booking a trip. The collection of metrics for each locality is curated based on the data being representative of the broader Airbnb community based on sample size (>75), margin of error (<=10.0%), and local nuances that make specific metrics particularly relevant. Some local pages offer a combination of local metrics (city or county) and broader geographic metrics (state/province or country).