Hedonic Price Indices for Moscow Short-Term Rental Housing

Abstract

This paper analyses the dynamics of prices in the short-term rental housing market in Moscow based on data from the online Airbnb and sutochno.ru platforms for the period from 2015 to 2023. We build the simplest price indices based on average and median prices and create hedonic indices using alternative methods. The analysis conducted demonstrates that it is relevant to take the quality of housing into account in the analysis of rental price dynamics. The time-dummy method turns out to be quite robust to adding additional observations to the sample, while the results of the imputation method, on the contrary, change greatly depending on the choice of the base period. We believe that the adjacent period method is the best method for constructing an index. This method allows changes in the market structure and the preferences of tenants to be considered. The construction of indices for individual Moscow districts provides additional information about the situation on the rental market which may be useful to various economic agents.