The Russian government’s decision to lower mortgage rates in the spring of 2020 was announced as a measure to support the population during the spread of coronavirus infection. However, is this decision optimal and strategically correct in terms of improving the availability of housing for Russian citizens in the future? In the context of rising real estate prices, this issue in domestic economic research is insufficiently addressed. The relevance of the research is additionally conditioned by the evaluation necessity of the “bubble” formation probability on the primary housing market due to the “double boom”. In this paper, we present the study results of availability of housing dynamics for the period from 2000 to 2020. We identified the regions with the lowest and the highest availability of housing. We have studied the current state of the mortgage lending market in Russia and constructed a multiple regression factor model for residential real estate prices on the new housing market. The scientific novelty of the presented research consists in the determination of the reasons of the rash growth of real estate prices in the spring of 2020 on the Russian housing market and their forecast for the medium term period. It is recognized that in modern conditions the key factor contributing to the increase in primary housing prices is the reduction in mortgage interest rates on loans. The decision to sharply reduce the interest rate has caused an increased demand for housing and the subsequent excessive growth of prices, which ultimately did not contribute to the availability of housing. We substantiate the absence of a “bubble” and the reasons for lower prices on the Russian residential real estate market in the short term. We have implemented the forecasting of primary housing prices through a combination of traditional economic tools and neural networks. The persistence of significant price levels on the Russian market of new buildings in the medium term can be explained by the negative trends in the development of key influencing factors and other macroeconomic indicators characterizing the socio-economic development of the country. We have proposed managerial measures aimed at expanding the availability of housing for Russian citizens
Keywords
neural network modeling, Availability of housing, preferential mortgage lending, primary housing market, real estate price growth factors