Econometric modeling of the demand for short-term rental housing: The case of Airbnb in Moscow

Ev. Bobrovskaya and Andrey Polbin
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Ev. Bobrovskaya: Russian Presidential Academy of National Economy and Public Administration (RANEPA), Moscow, Russia

Journal of the New Economic Association, 2023, vol. 59, issue 2, 64-84

Abstract: The article analyzes demand determinants for short-term rental housing on the online platform Airbnb in Moscow. The study used a cross-sectional sample of listings that were active between March 2021 and February 2022. Spatial models were estimated to account for spatial autocorrelation. Spatial Durbin model was found to be the best for the available data. Direct, indirect and general effects were calculated for a correct interpretation of the results. Based on the results of the study, both the own price elasticity of demand (-0.68) and the cross-price elasticity (0.42) were determined. In addition, the article identified the main characteristics of apartments that affect demand. Characteristics related to the area of housing (maximum capacity and number of bathrooms), the availability of various amenities in the apartment and related indicators (paid parking, self-check-in, number of photos and instant booking, superhost status, response rate) have positive demand influence. The distance to the city center and the minimum rental period negatively affect demand. The results of the study were tested for robustness using various spatial weight matrices and alternative variables as rental price.

Keywords: Airbnb; short-term rental housing; spatial econometrics; spatial Durbin model; demand determinants; demand elasticity (search for similar items in EconPapers)
JEL-codes: C21 R31 Z39 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nea:journl:y:2023:i:59:p:64-84

DOI: 10.31737/22212264_2023_2_64-84

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