financeФинансы: теория и практика/Finance: Theory and PracticeFinance: Theory and Practice2587-56712587-7089Financial University under The Government of Russian Federation10.26794/2587-5671-2023-27-1-208-220finance-2000Research ArticleЦЕНООБРАЗОВАНИЕPRICINGАнализ факторов, влияющих на динамику цен на жилую недвижимость в РоссииAnalysis of Factors Affecting the Dynamics of Residential Real Estate Prices in Russiahttps://orcid.org/0000-0001-9342-1266НикитинаН. С.NikitinaN. S.

Наталья Сергеевна Никитина - младший научный сотрудник лаборатории математического моделирования экономических процессов, Институт прикладных экономических исследований

Москва

Natalia S. Nikitina - Jun. Researcher, Laboratory of Mathematical Modeling of Economic Processes, Department of Applied Economic Research

Moscow

nikitina-ns@ranepa.ruРоссийская академия народного хозяйства и государственной службы при Президенте Российской ФедерацииРоссияRussian Presidential Academy of National Economy and Public AdministrationRussian Federation202311032023271208220Copyright © Никитина Н.С., 20232023Никитина Н.С.Nikitina N.S.This work is licensed under a Creative Commons Attribution 4.0 License.https://financetp.fa.ru/jour/article/view/2000

В данной работе мы построили VAR модель для идентификации и оценки влияния шоков реальной процентной ставки, спроса на недвижимость, цен на нефть, неопределенности и агрегированной деловой активности на цены жилой недвижимости в России. Актуальность исследования обусловлена следующим: динамика цен на недвижимость определяет потребительское и инвестиционное поведение домохозяйств, а серьезные колебания цен на недвижимость приводят к неблагоприятным последствиям во многих сферах жизни, поэтому все больше исследователей задаются вопросами наличия пузырей на рынке недвижимости, которые могут быть опасны для стабильности экономики. К тому же резкий рост стоимости жилья в России в 2020 г. — открытый вопрос для исследователей. Наша цель - определить, из-за каких факторов происходил рост цен на недвижимость в России на временном промежутке с I квартала 2000 по II квартал 2022 г. Для оценки была использована VAR модель с разложением по Холецкому. Рассмотрены несколько спецификаций с включением реальной цены на нефть в качестве экзогенной переменной и набора эндогенных переменных: реального ВВП, реальной процентной ставки, индекса неопределенности и индекса цен на жилье. Основной вывод работы — рынок жилья чувствителен к идентифицированным макроэкономическим шокам, а снижение процентной ставки приводит к росту спроса и цен на недвижимость. Оценка долгосрочной эластичности цен жилья по ценам на нефть составила 0,35, динамика цен на нефть объясняла существенную долю вариации цен на недвижимость, однако превалирующая роль в колебаниях цен жилья отводится шокам спроса на жилье. Сами же шоки спроса на жилье в России оказывали незначительное влияние на ВВП.

In this paper, we have constructed a VAR model to identify and assess the impact of real interest rate shocks, real estate demand, oil prices, uncertainty, and aggregate business activity on residential real estate prices in Russia. The relevance of the research is due to the following: the dynamics of real estate prices determines the consumer and investment behavior of households, and serious fluctuations in real estate prices lead to adverse consequences in many areas of life, so more and more researchers are asking questions about the presence of bubbles in the real estate market, which can be dangerous to the stability of the economy. In addition, a sharp increase in the cost of housing in Russia in 2020 is an open question for researchers. Our goal is to determine what factors caused the rise in real estate prices in Russia in the time interval from the Q1 of 2000 to the Q2 of 2022. A VAR model with a Cholesky decomposition was used for the evaluation. Several specifications were considered with the inclusion of the real oil price as an exogenous variable and a set of endogenous variables: real GDP, real interest rate, uncertainty index and housing price index. The main conclusion of the paper is that the housing market is sensitive to identified macroeconomic shocks, and a decrease in the interest rate leads to an increase in demand and real estate prices. The estimate of the long-term elasticity of housing prices for oil prices was 0.35, the dynamics of oil prices explained a significant proportion of the variation in real estate prices, but the predominant role in housing price fluctuations is given to housing demand shocks. The housing demand shocks in Russia itself had a negligible impact on GDP.

индекс цен на недвижимостьрынок жильяVAR моделимакроэкономические шокишок реальной процентной ставкиисторическая декомпозиция индекса цен на недвижимостьшок спроса на недвижимостьшок цен на нефтьreal estate price indexhousing marketVAR modelsmacroeconomic shocksreal interest rate shockhistorical decomposition of the real estate price indexreal estate demand shockoil price shockАвтор выражает благодарность Андрею Полбину за обсуждение и ценные замечания. Статья подготовлена в рамках выполнения научно-исследовательской работы государственного задания РАНХиГС. Российская академия народного хозяйства и государственной службы при Президенте Российской Федерации, Москва, Россия.The author expresses gratitude to Andrey Polbin for the discussion and valuable comments. The article was written on the basis of the RANEPA state assignment research program. Russian Presidential Academy of National Economy and Public Administration, Moscow, Russia.ReferencesPoterba J. M. 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The authors declare that there are no conflicts of interest present.