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An Impact of Closeness to the Underground upon the Short-term Rental: Former USSR Cities

Student: Ivan Mishalkin

Supervisor: Konstantin Kholodilin

Faculty: St.Petersburg School of Economics and Management

Educational Programme: Economics (Bachelor)

Year of Graduation: 2018

The main aim of this study is to estimate the impact of the subway accessibility on the rents of short-term accommodation. Unlike the majority of studies focusing on the impact of subway in the advanced market economies, this paper concentrates on the cities of the former USSR. Here, we investigate the price setting in the segment of short-term accommodation - a rapidly developing market worldwide. As a data source the Airbnb.com website is chosen, which has two big advantages: wide coverage of cities and a uniform data format. Methodologically this study is conducted using spatial models (SLM, SEM and SAC) in order to take into account the spatial dependence present in real estate markets. The topic considered here can be of interest for several economic agents. First of all, the government may be interested in the most effective budget expenditures. Making decisions about building a new station in this or that place is not obvious and many s should be taken into account, including real estate price changes in nearby neighborhoods. Another stakeholders are the real estate investors. It is not obvious whether in different areas the same increase in accessibility leads to an equal increase in land and property values. The aim of this study is to find out if the impact of proximity to subway differs significantly depending on the density and configuration of the subway network. In order to do this we take advantage of a sample of big cities from the former Soviet Union having subways, which vary in terms of the size of their subway networks. In the study cities are previously clustered according to the level of metro system development. The results: significant effect of distance to metro was only detected in Moscow city case. The total effect is following: the increase in distance to metro for 1 km leads to a rent decrease by around 1.47% for Moscow, 3.1% for Kiev, 2.3% for Kazan, and 3.4% for Novosibirsk.

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