Publication: Host Professionalization in Short-Term Rentals: An Empirical Analysis of the Parisian Airbnb Market
| datacite.rights | restricted | |
| dc.contributor.advisor | Rigobon, Daniel | |
| dc.contributor.author | Anderson, Justin | |
| dc.date.accessioned | 2026-07-22T16:39:56Z | |
| dc.date.available | 2026-07-22T16:39:56Z | |
| dc.date.issued | 2026-04-09 | |
| dc.description.abstract | This thesis examines the extent to which Airbnb activity in Paris represents a professionalized market structure, a shift from its original peer-to-peer sharing platform. Using listing-level data for June 2025, this paper analyzes the distribution of listings across hosts, the spatial concentration of activity, and the characteristics associated with professional operators. The results reveal a highly skewed distribution of supply, with a small fraction of multi-listing hosts accounting for a disproportionate share of listings; in particular, the top 1% of hosts control nearly a quarter of the market. Spatial analysis using optimized hot spot methods shows that professional listings are concentrated in central, high-demand areas of the city, while non-professional activity is more diffuse. Regression results indicate that professional hosts exhibit distinct behavioral patterns, including higher availability and pricing strategies consistent with revenue optimization. These findings suggest that Airbnb in Paris operates as a hybrid market, combining a large base of casual hosts with a significant presence of professional operators who resemble commercial firms in both scale and behavior. This has important implications for housing markets and regulatory policies, particularly in distinguishing between casual and professional participants on the platform. | |
| dc.identifier.uri | https://theses-dissertations.princeton.edu/handle/88435/dsp01pc289n59r | |
| dc.language.iso | en | |
| dc.title | Host Professionalization in Short-Term Rentals: An Empirical Analysis of the Parisian Airbnb Market | |
| dc.type | Princeton University Senior Theses | |
| dspace.entity.type | Publication | |
| dspace.workflow.startDateTime | 2026-04-09T16:37:41.436Z | |
| pu.contributor.authorid | 920320070 | |
| pu.date.classyear | 2026 | |
| pu.department | Ops Research & Financial Engr | |
| pu.minor | Statistics and Machine Learning |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Justin_Anderson_ORFE_Thesis_Final.pdf
- Size:
- 16.99 MB
- Format:
- Adobe Portable Document Format
Download
License bundle
1 - 1 of 1
Loading...
- Name:
- license.txt
- Size:
- 100 B
- Format:
- Item-specific license agreed to upon submission
- Description:
Download