Dynamic pricing and revenues of Airbnb listings: estimating heterogeneous causal effects

Veronica Leoni (veronica.leoni@uib.es) and Jan Olof William Nilsson (william.nilsson@uib.es)
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Veronica Leoni: Universitat de les Illes Balears, Postal: Edifici Jovellanos, Crta Valldemossa, km 7,5 07122 Palma de Mallorca (Spain), https://sites.google.com/view/veronicaleoni
Jan Olof William Nilsson: Universitat de les Illes Balears, Postal: Edifici Jovellanos, Crta Valldemossa, km 7,5 07122 Palma de Mallorca (Spain)

No 92, DEA Working Papers from Universitat de les Illes Balears, Departament d'Economía Aplicada

Abstract: This paper investigates the extent to which the implementation of intertemporal price discrimination affects Airbnb listings’ revenue. We found that on average, a price surge (i.e., increasing the price as we approach the date of service consumption) has an adverse effect on revenue. However, the magnitude of such effect exhibits significant heterogeneity among listings. Through the application of generalized random forests, a causal machine learning technique, we identify exacerbating and moderating treatment modifiers and shed light on the listing dimensions that cause price surges to be particularly detrimental for hosts’ revenues.

Keywords: Airbnb; dynamic pricing; heterogeneous causal effects; generalized random forest. (search for similar items in EconPapers)
JEL-codes: C21 C26 Z30 Z31 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-big and nep-tur
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Persistent link: https://EconPapers.repec.org/RePEc:ubi:deawps:92

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