Models for Predicting Prices in the Moscow Residential Real Estate Market

Abstract

The paper presents the results of modeling the pricing mechanism in the residential real estate market (by using Moscow as an example). The key factors that influence the monthly and annual dynamics of real estate prices are revealed; their quantitative impact is assessed using regression analysis methods. The close dependence of the real estate price on the change in the US dollar-ruble exchange rate in a monthly model with a distributed lag is revealed. In the annual model, the best explanatory force is possessed by factors such as the dynamics of the Urals oil prices and the change in the average cost of basic materials, parts, and structures purchased by construction companies in the current year. The study also proposes a new indicator, which, is believed by the authors to approximate the change in the propensity to save in high-income groups of the population.