Анализ и моделирование влияния макроэкономических факторов на ввод в эксплуатацию жилой недвижимости в России
On the part of the population, residential real estate is considered from the point of view of improving the standard of living, as well as an object of profitable investment. The Russian residential real estate market attracts the attention of not only the population, but also researchers. Its structure and the multifactorial nature of development dynamics provide ample opportunities for statistical analysis.
Considering the real estate market of a particular city or subject of the Russian Federation, researchers focus on the features of the economic and social development of the region, its geographical location, etc. Also, the level of development of the real estate market, as a financially intensive industry, in the region depends on the volume of subsidies from the state.
In the article, the authors present the results of a study of the primary residential real estate market in Russia, as the most dynamically developing segment. An analysis of the dynamics and structure of the market in terms of its main indicators for Russia as a whole and its subjects was carried out. Leaders among developer companies have been identified and the level of competition and market concentration has been assessed. The pricing policy in the primary residential real estate market is presented throughout the country, taking into account changes in the income level of the population.
The study of the results of studies of past years made it possible to form a system of statistical indicators for further modeling.
The information sources were official data from the Federal State Statistics Service (Rosstat), the Unified Interdepartmental Information and Statistical System (EMISS), the Central Bank of the Russian Federation (CBR), and the Unified Housing Construction Information System (UIIS).
Based on quarterly data for the period 2010-2021 the indicator of the volume of commissioning of residential real estate was modeled under the influence of macroeconomic indicators and the seasonal component. As a result of the regression analysis of time series, models with the best explanatory properties were identified.
The results of the study presented in the article may be of interest to analytical agencies, developers, banking professionals, financiers, economists, analysts of the real estate market or related areas, as well as authorities for strategic planning of the development of the real estate market.