{"title":"IMPACT OF SOME FACTORS ON PRICING IN THE REAL ESTATE MARKET OF RUSSIAN MEGACITIES","authors":"S. Mudrova, V. Bolonkin, A. E. Davydov","doi":"10.48137/26870703_2024_26_2_138","DOIUrl":null,"url":null,"abstract":"The authors analyze pricing in the residential real estate market in Moscow and St. Petersburg – the largest cities of the Russian Federation in the article. The issue of the cost of residential real estate is one of the most important for the residents of Russian megapolises. Megapolicies are the largest centers of migration, both from other regions and from other countries. The population of such cities is expanding at a significant rate, and the construction industry is increasing the rate of creation of new real estate objects. Under such conditions, it is crucial to realize the dependence of real estate value and key externalities.Within the framework of the study, the authors rely on the works in the field of real estate valuation and statistical methodology. The group of authors puts forward statistical hypotheses about the impact of some factors, in particular the level of cumulative inflation, the key rate set by the Central Bank of the Russian Federation, the average level of wages in the region and the weighted average rate on mortgage loans to citizens on the formation of the weighted average cost per square meter of housing in Russian cities.The statistical method of factor analysis is used to assess the significance of each of the factor variables on the resulting parameter. Regression modeling allows estimating the degree of impact of significant factors on the cost per square meter of residential real estate. The models allow to assess the trends of changes in the cost of real estate on the primary and secondary residential real estate markets in Russian megacities, as well as provide an opportunity to consider the differentiation in the impact of each factor between different types of markets in different cities.The results of the study may be useful in building industry forecasts and developing government measures to support residential construction.","PeriodicalId":517339,"journal":{"name":"Geoeconomics of Energetics","volume":"2 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoeconomics of Energetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48137/26870703_2024_26_2_138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The authors analyze pricing in the residential real estate market in Moscow and St. Petersburg – the largest cities of the Russian Federation in the article. The issue of the cost of residential real estate is one of the most important for the residents of Russian megapolises. Megapolicies are the largest centers of migration, both from other regions and from other countries. The population of such cities is expanding at a significant rate, and the construction industry is increasing the rate of creation of new real estate objects. Under such conditions, it is crucial to realize the dependence of real estate value and key externalities.Within the framework of the study, the authors rely on the works in the field of real estate valuation and statistical methodology. The group of authors puts forward statistical hypotheses about the impact of some factors, in particular the level of cumulative inflation, the key rate set by the Central Bank of the Russian Federation, the average level of wages in the region and the weighted average rate on mortgage loans to citizens on the formation of the weighted average cost per square meter of housing in Russian cities.The statistical method of factor analysis is used to assess the significance of each of the factor variables on the resulting parameter. Regression modeling allows estimating the degree of impact of significant factors on the cost per square meter of residential real estate. The models allow to assess the trends of changes in the cost of real estate on the primary and secondary residential real estate markets in Russian megacities, as well as provide an opportunity to consider the differentiation in the impact of each factor between different types of markets in different cities.The results of the study may be useful in building industry forecasts and developing government measures to support residential construction.