Residential Real Estate Research Articles

Comparative Statistical Analysis of Changes in Average Asking Prices for Housing in the Administrative Districts of Moscow

The article presents the results of a comparative analysis of the residential real estate market in nine administrative districts of Moscow in 2016 and 2024. The paper focuses on the features of housing price formation and considers factors influencing pricing, including socio-economic conditions and transport infrastructure. The study outlines the role of housing construction and the investment attractiveness of various districts of the capital.The authors used official data from Russia's largest real estate technology service (CIAN) on asking prices for apartments for sale depending on their parameters. The article draws on such indicators as the local average price per square meter of the total area of dwellings and the number of offers of apartments for sale. It is shown that apartment prices in two administrative districts (AO) of Moscow have a stable growth trend in 2024, which was not observed in 2016. It is concluded that the real estate markets in the districts of Moscow in 2016 (exception for the Central AO) were strongly differentiated in price offers in 2024, and, therefore, it is incorrect to use the average price per square meter of Moscow residential real estate as a characteristic of housing quality in 2024.The article lists events that influenced changes in the Moscow residential real estate market without specifying the relative strength of their impact. According to the authors, each event had its causes, but their almost simultaneous appearance led to tension in the housing market for all participants.In conclusion, the significant impact of inflation and the restoration of residential premises (after renting) on the growth of residential property values and the potential for using housing as an investment object is emphasized

Forecasting residential real estate prices and energy usage in Flanders

Purpose Currently, residential forecasting literature is limited with few to no forecasting papers that consider residential prices and energy consumption for the selling and rental market within a single study. The purpose of this paper is to study the prices and energy usage for both markets by combining an explanatory model with the predictions of a predictive model, which will lead to a better understanding of the forecasting results. Design/methodology/approach This study presents an econometric comparison between 508,612 selling properties and 174,007 rental properties transacted in Flanders between January 2019 and December 2023. The authors study their prices and energy usage by combining the causal results of a hedonic price model (HPM) with the predictions of an autoregressive integrated moving average model (ARIMA). Findings The authors find that both markets are extremely sensitive to changes in related factors, whereby selling prices are primarily influenced by macroeconomic factors, but rental prices and especially energy usage are also sensitive to market standards. Policies that target energy efficiency can therefore steer its future trend. In addition, in line with previous literature, the HPM shows an increasingly strong relationship between residential prices and energy efficiency over the years, indicating that these steering energy policies also indirectly monitor residential prices. Originality/value This study underscores the importance of integrating the results of an explanatory model with a predictive model. It demonstrates that combining them provides a more comprehensive understanding which is helpful for policymakers, real estate professionals and investors during their decision-making process.

External Shocks, Asset Prices, and Credit Dynamics in Morocco: Insights from Disequilibrium Models

We investigate external shocks and asset price’s impact on the slowdown of business and household credit in Morocco using disequilibrium models. The results show that banks’ fly to quality, driven by a simultaneous decline in interest margins and borrower creditworthiness, is a key factor behind the slowdown of credit supply. On the demand side, slower growth and saturated housing demand have contributed to reduced borrowing and repayment capacity of borrowers. Furthermore, external shocks are transmitted to credit supply through foreign deposits and households’ credit demand through remittances. Additionally, stocks and residential real estate asset prices are closely tied to credit demand. These findings suggest that addressing bank credit barriers could stimulate economic growth. To do so, policymakers may consider employing unconventional monetary policy tools to effectively manage the transmission channels of external shocks and asset prices to bank credit dynamics.

Determination of outliers when building a multivariate regression model of prices in residential real estate market of the region

The paper is aimed at selecting the optimal method for identifying outliers in the initial data when building a multivariate regression model of prices in the regional residential real estate market. The study was based on offers for sale of apartments in prefab flat blocks located in Irkutsk. In this regard, a basic multiplicative multivariate regression model was built, describing the dependence of cost indicators on the pricing factors of real estate. The identified outliers were iteratively removed from the basic model. The methods for detecting outliers included calculation of standard deviation (z-score), calculation of the Mahalanobis distance, as well as a method developed in the study for bringing the prices of objects to the characteristics of the reference object. The optimal method for detecting outliers in the initial data was selected by comparing the characteristics of the final variable-based multivariate regression models obtained after removing outliers from them. The analysis of the results proved the method of bringing the prices of objects to the characteristics of the reference object to be the optimal method of identifying outliers when building a multivariate regression model of prices in the regional residential real estate market. This method significantly reduces the approximation errors of the basic multivariate regression model of the market, thereby increasing the adequacy of the results of the real estate valuation conducted on its basis.

Анализ рынка жилой недвижимости академического района города Екатеринбург

Real estate as an economic category is a tangible asset, the value equivalent of which is determined by how effectively it is used as an economic good, commodity or source of income. The real estate market is of constant relevance, both for investors, builders, lawyers, and for ordinary citizens who need their own housing to live. The analysis of the real estate market helps to understand where the real estate market may move in the future and what awaits it, taking into account the specifics according to which it is formed. This article analyzes the secondary real estate of the Academic district of Yekaterinburg. Information on real estate objects was selected from the sites of Avito and Domclick, services for housing search and real estate sale. The existing infrastructure of the district is analyzed. To analyze the dynamics of the price per square meter of residential real estate, calculations were made for a time period of 4 months in 2023-2024 and data on the cost of a square meter were presented.

A Study on the Effect of Residential Real Estate Intrinsic Characteristics on Auction Successful Price - Focused on the Characteristics of the Tenant Rights Protection System

A Study on the Effect of Residential Real Estate Intrinsic Characteristics on Auction Successful Price - Focused on the Characteristics of the Tenant Rights Protection System

A Study on the Effect of Residential Real Estate Intrinsic Characteristics on Auction Successful Price - Focused on the Characteristics of the Tenant Rights Protection System

A Study on the Effect of Residential Real Estate Intrinsic Characteristics on Auction Successful Price - Focused on the Characteristics of the Tenant Rights Protection System

Unveiling the drivers of sustainable housing choices among millennials in emerging markets

Purpose The purpose of this study is to explore the complex interplay between technology, personal norms and emotional factors in shaping the sustainable housing choices of millennials in emerging economies. It integrates the model of goal-directed behavior, technology acceptance model and norm activation model, incorporating both self-interest and prosocial motivations. Key adaptations involve replacing perceived behavioral control with financial self-efficacy and substituting hedonic motivation for anticipated positive emotions. Moreover, it introduces location as a practical anchor. Design/methodology/approach A quantitative, cross-sectional and descriptive research design was used in this study. Data were gathered from a sample of 610 millennial residential real estate investors across Indian smart cities. A multistage stratified sampling technique was used to ensure a representative sample. For data analysis, partial least squares structural equation modeling was used. The analysis focused on hypothesis testing to examine the relationships between the constructs of interest. Bootstrap t-values and effect sizes were used to assess the significance and magnitude of these relationships, respectively. Findings One of the key findings of this study was the establishment of significant positive relationships between awareness of consequences, ascription of responsibility and personal norms with behavioral intentions. This underscored the importance of personal ethical considerations in shaping intentions. Perceived usefulness and ease of use were found to significantly influence attitudes positively, highlighting the relevance of these factors in forming favorable attitudes toward behaviors. Attitude, subjective norms, financial self-efficacy and location played significant positive roles. However, negative anticipated emotions decreased desire. This illustrated the complex role emotions play in motivational processes. The study also revealed that subjective norms did not significantly contribute to shaping personal norms. This indicated a potential decoupling of societal expectations from personal ethical obligations in the decision-making process. Practical implications This study offers actionable insights for both policymakers and real estate developers. For policymakers, the findings highlight the need to craft initiatives that go beyond mere awareness, instead fostering a deep sense of personal responsibility and environmental stewardship among potential homebuyers. For real estate developers, the emphasis on financial self-efficacy and location suggests a strategy shift toward designing sustainable homes that not only meet environmental standards but also align with buyers’ financial confidence and geographic preferences. Together, these strategies can drive a more widespread adoption of sustainable housing, making sustainability a tangible and appealing choice for millennials. Originality/value To the best of the authors’ knowledge, this empirical research study was one of the first studies that contributed to the literature by integrating the model of goal-directed behavior, technology acceptance model and norm activation model. This study thus offered a nuanced understanding of the interplay between normative influences, usability perceptions, ethical considerations and emotions in the context of behavioral intentions.

The Impact of the Opportunity Zone Program on Residential Real Estate

Problem definition: Opportunity zones (OZs) are designated census tracts in which real estate investments can gain tax benefits. Introduced by the U.S. Tax Cuts and Jobs Act of 2017, the goal of the OZ program is to foster economic development in distressed neighborhoods. In this paper, we investigate and optimize the OZ selection process and examine the impact of OZs by exploiting two data sets: a proprietary real estate data set that includes 36.1 million residential transactions spanning all 50 U.S. states and census-tract demographics data between 2010 and 2019. Methodology/results: We show that census tracts with higher poverty and unemployment rates were more likely to be selected. Counterintuitively, however, tracts with a higher average real estate price were also more likely to be selected. We then apply difference-in-differences, synthetic control, and matching techniques to rigorously assess the impact of the OZ program on two key real estate metrics: price and transaction volume. We find that the OZ program increased real estate prices by 4.03%–6.13% but do not observe a significant effect on the transaction volume. We also find that investors primarily targeted the high-end real estate market, namely, exhibiting a cherry-picking behavior. To better fulfill its intended societal and economic goals, we propose an optimization framework with fairness considerations for OZ assignment decisions. We show that the OZs assigned from our fairness-aware optimization formulation can better serve distressed communities and mitigate investors’ cherry-picking behavior. Managerial implications: Our paper underscores the importance of incorporating fairness in OZ designation to achieve a desirable real estate market reaction. Our large-scale empirical analysis provides a comprehensive assessment of the current government OZ assignment, and our fairness-aware optimization framework provides concrete recommendations for policy makers. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2024.0746 .

ANALYSIS AND PROSPECTS FOR THE DEVELOPMENT OF RENTAL RESIDENTIAL REAL ESTATE IN THE UDMURT REPUBLIC

This study, using the example of the Udmurt Republic and some Russian regions, examines the development of rental residential real estate. An analysis of the rental housing market was carried out, on the basis of which prospects were identified and ways of development of this area were outlined. The study examined state and federal programs and subprograms implemented in Russian regions aimed at providing affordable, comfortable housing, as well as utility services to citizens of the Russian Federation, and analyzed the main indicators. The purpose of the study is to determine the main ways of development of rental residential real estate in the Udmurt Republic. For this purpose, an analysis of scientific sources was carried out, the authors of which study issues related to the problem of residential real estate development in our country. In the process of working on the article, the authors reviewed the “Rented Houses” program, aimed at helping to improve the living conditions of citizens, which is being implemented in the city of St. Petersburg. An assessment of this program is given and the conclusion is made that, under certain conditions, this program can be applied in the Udmurt Republic. Also, during this study, the authors studied statistical data reflecting the current situation in the rental housing market and conducted a sociological survey. The development of a rental housing stock involves the careful development of certain mechanisms for the construction of residential space for that category of citizens who need rent to improve their living conditions. It has been revealed that government support, attraction of funds from citizens, as well as long-term installment payments contribute to the development of the rental housing market with the right to purchase. Thus, the authors of the article concluded that at the state level it is necessary to ensure regulation between the leasing parties, since this form of financial services is of interest to all social categories of citizens who need rental housing at market prices.

The role of speculation on housing price disparities

This paper explores the impact of speculation on disparities in home purchase prices within neighborhoods. Using administrative data on residential real estate transactions in Singapore's private housing market, our analysis reveals that housing unit prices increase over time within a neighborhood in the presence of speculators. However, this pattern remains stable after the implementation of macroprudential policies aimed at deterring speculation. Our mechanism analysis indicates that while speculative sales contribute to the increase in the price of neighboring units over time, speculative purchases have negligible effects. These findings underscore the potential of macroprudential policies in mitigating speculation and promoting housing affordability.

Взаимодействие стейкхолдеров при формировании и управлении децентрализованными фондами капитального ремонта жилищно-коммунального хозяйства

Introduction. The purpose of this study is a systematic analysis of the stakeholder relations on the issue of the formation and management of decentralized capital repair funds. The high social significance of capital repairs of residential real estate, coupled with a high degree of wear and tear, determines the need for coordinated and effective stakeholder interaction, the involvement of public authorities in co-financing expenses and the development of effective mechanisms for the rational allocation of funds from decentralized capital repair funds formed in special accounts in banking organizations and protecting them from inflationary processes.Materials and methods. The authors explore institutional factors in the implementation of major renovations of apartment buildings, identify the key stakeholders of these processes, their interests and risks, and reveal the presence of an agency problem. Based on statistical data and regulations, the authors conduct economic modeling of the formation of a decentralized capital repair fund using the example of an existing homeowners' association, and calculate target indicators for the efficiency of capital repair fund management.Results. The conducted research revealed inconsistency of the current management approaches and the impossibility of forming major overhaul funds in sufficient size to replace elevator equipment after the shelf life expiry without external financing. The authors conduct a study of the agency problem that arises when managing funds placed in special accounts for major overhaul, and identify the presence of informal institutional factors that prevent the formation of a "mature real estate owner".Discussion. Based on the results of the study, the authors proposed regulatory measures that could positively affect the effectiveness of relations on the issue of formation and management of decentralized capital repair funds. In addition to regulatory measures, the authors consider it necessary to involve municipal deputies in awareness-raising activities aimed at creating a “mature property owner.” The scientific novelty of this study consists in the development of management and regulation methods for the formation of decentralized capital repair funds on the basis of the synthesis of stakeholder and institutional approaches.

Соціальні та економічні ефекти розвитку ринку іпотечного кредитування в умовах дії правового режиму воєнного стану

The article reveals the peculiarities of the development of the mortgage lending market in Ukraine and its impact on the socio-economic development of society. Housing mortgage lending allows the optimal combination of the interests of various parties as one of the most reliable ways of attracting private investment through the capitalization of residential real estate, – construction companies, financial and credit institutions, citizens, and the state. The mortgage lending system changes the needs of different social strata of the population, affecting the behavior strategy and adaptation to market conditions. Providing good living conditions contributes to improving the nation’s health, increasing life expectancy, and increasing the working capacity of the population, which are essential components of the country’s social capital. An assessment of the possibilities of stimulating this influence in the conditions of war and post-war recovery was carried out, and the necessary tools for strengthening the social orientation of mortgages were determined. The processes of implementing the state program «eOselia» as a vital tool for restoring mortgage lending to provide affordable housing for the population have been analyzed. The conclusions regarding the possibilities of developing mortgage lending in modern challenges and the need to implement strategic measures to stabilize and expand the housing market in Ukraine are substantiated. The development of the real estate market and mortgage lending is quite tricky due to the instability of the economic situation in the country, the war, and the population’s growing demand for the improvement of housing conditions. Therefore, the proper development of the mortgage lending market will contribute not only to the economy but also to the social development of the state. Thanks to reforms, state support programs, and technological innovations, Ukraine can create a more accessible and stable mortgage market, which will contribute to the improvement of the living conditions of citizens and general economic development. Keywords: mortgage, mortgage lending, mortgage lending market, state lending program.

Modeling of the effect of transportation system accessibility on residential real estate prices: The case of Washington metropolitan area, USA

Deep learning accurate predictions of house prices are essential for prospective homeowners, investors, appraisers, and insurers. However, some studies lack accuracy as they overlook critical factors like accessibility and economic attributes that influence house prices. This paper aims to predict house prices by considering structural, locational, accessibility, and economic attributes, while also exploring the effect of accessibility on housing prices. The dataset contains 2,019,663 real estate transaction records from 1975 to 2018 in the Washington metropolitan area, obtained from the Zillow website. In this study, the accessibility index is calculated using Distance, Cumulative Opportunities, and Gravity measures, with the gravity measure surpassing others due to its consideration of both land use and transportation aspects. Economic attributes are then utilized to predict the average monthly house price using deep learning algorithms such as LSTM, GRU, and Simple RNN, with the Simple RNN demonstrating superior performance. Following the amalgamation of structural and locational attributes with the accessibility index and average house prices, various machine learning algorithms—including Linear Regression, Lasso, Ridge, Random Forest, GBM, LightGBM, XGBoost, Decision Tree, AdaBoost, Artificial Neural Network, and Stacked Generalization—are employed for prediction. Subsequent evaluation reveals that Stacked Generalization (ANN + LightGBM) provides the best performance, with an R-squared value of 0.96 and RMSE of $23,290. Moreover, this paper identifies accessibility index thresholds (80,003 for large buildings and 160,103 for small buildings) and demonstrates that a higher accessibility index leads to lower housing prices, attributed to noise pollution, decreased privacy, and increased supply responses.

HOUSING PRICES AS PAYMENT FOR ECOSYSTEM SERVICES OF URBAN GREEN SPACES: CASE STUDY IN KYIV

The purpose of the study is to analyze the impact of the availability of urban green spaces (UGS) and air quality on the cost of residential real estate in Kyiv. Additionally, it seeks to identify the level of awareness among city residents regarding the advantages of living close to UGSs in areas with relatively clean air and their willingness to pay a higher price for such housing. The QGIS software was employed to assess the pedestrian and time accessibility levels of recreational green spaces, and the results are depicted on the corresponding map. The least accessible for everyday recreation is the UGS in the central districts of the city, which traditionally have the highest population density and the most expensive residential real estate. The article analyzes the priority criteria for determining the housing cost, depending on the spatial localization relative to the city center and the comfort class of real estate. The distribution of housing across different tiers and the price range for the apartments in new constructions in Kyiv during 2015–2021 were also examined. To identify the correlation between the cost of residential real estate in the capital’s new buildings and the availability of green spaces nearby, we investigated the spatial distribution of prices in the largest residential complexes in the city. The results of spatial visualization obtained through Voronoi diagrams or Delaunay triangulation indicate significant disparities in the cost of housing located in the center of Kyiv or on the periphery. Logically, residential complexes with the highest apartment prices are located in the central districts of Kyiv and near the metro stations. However, most of these locations lack accessible green areas suitable for everyday recreation. Therefore, there is no positive correlation between housing prices and the presence of UGSs nearby. To achieve the research goal, we also conducted a sociological survey among Kyiv residents in various districts of the city. The survey results indicate that most Kyiv residents do not have the desire or are not currently willing to pay a higher price for the opportunity to live near a park or forest and breathe clean air, i.e., to enjoy the ecosystem services provided by UGSs fully. The scientific novelty of the research lies in determining the pedestrian and time accessibility of recreational green spaces in Kyiv, identifying trends in spatial clustering of the most expensive residential real estate in central city areas, and demonstrating the lack of a positive impact of the availability of green areas on the per square meter cost of housing in new developments. Additionally, the study reveals a remarkably low willingness of the city residents to pay a higher price for the opportunity to receive ecosystem services from available UGSs.

The relation of spatial configuration in residential real estate towards its conduciveness security level

As a part of an area, residential real estate has various spatial configuration patterns, which are part of the elements that form its environment. Depending on the context of certain places, spatial configuration and security reinforcement become a concern regarding the issue of crime prevention, which promotes a safe neighbourhood that avoids the risk of crime. A phenomenon took place where there are several preventive actions were carried out at the basic stage of planning and designing residential real estate, but these efforts later brought various methods and priorities that determine spatial configuration or security reinforcement to serve either as the main reference or adjustment at the initial step. This research dissects the relationship between spatial configuration patterns and security systems applied using the Crime Prevention Through Environmental Design (CPTED) approach to obtain the most optimal solution in preventing crime and reducing crime rates. This research used descriptive analytical methods in a comparative way to derive the final synthesis of three residential real estates in Bintaro Jaya as study objects. The results of this research discovered the most conducive type of residential real estate in terms of its security level. These findings can enrich the development of studies on similar topics and contribute to the consideration of design criteria related to spatial configuration and security reinforcement of residential real estate in anticipating potential crimes.

Approaches to sustainable development of production systems in the sphere of housing construction on the basis of application of “green” standards

Aim. To determine the problematics of the application of “green” standards in the field of housing construction and its impact on the management of sustainable development of production systems based on the application of “green” standards in the marketing sphere, as well as to propose options for solutions to problematic issues and directions for further research.Objectives. To analyze statistical information, as well as regulatory documentation in the field of “green” certification of residential real estate; to identify the problems of applied standards; to offer possible solutions to problematic issues in the aspect of application of “green” standards in the marketing sphere; to determine the necessary measures to implement the principles of sustainable development of production systems in general and adaptation of “green” standards in the assortment policy, marketing sphere of production systems in particular; to determine the directions for further research.Methods. When conducting the research, general scientific methods such as general analysis, expert assessments and generalization, document analysis, abstraction, comparison were used.Results. In the course of the study, the research revealed consolidated groups of problems, including “green” certification in the sphere of individual housing construction in conditions of non-systemic control of the process and results of activity in the marketing sphere of production systems (defined as a goal of further research); the problems of application of the approved and implemented in 2022 “green” state standard in the field of apartment building were revealed. During the analysis of regulatory documentation (GOST R 70346-2022. “Green” standards. Buildings of multifamily residential “green”. Evaluation methods and criteria for design, construction and operation) methodological problems of applying the criteria of group No. 6 “Materials and resource efficiency” are studied, possible solutions are proposed, directions for further research are outlined, the impact of these issues on the complex of management of sustainable development of production systems based on the application of “green” standards in the marketing sphere is shown. In addition, the classification of building evaluation stages in terms of construction stages is given.Conclusions. Approaches to the sustainable development of production systems in the sphere of housing construction, production and application of building materials have a special significance in public policy. An example is the “green” state standard, which is adopted in 2022, its popularization including through “Dom.RF”. However, the current certification mechanism, with all its advantages and merits, has a number of limitations in its application: lack of information from the developer, especially about completed objects, lack of comprehensive systems and registers of “green” solutions and materials, insufficient regulatory mechanisms in case of conflict between environmental friendliness and economic efficiency. These limitations are analyzed in the context of the block of criteria № 6 “Materials and resource efficiency”, and possible solutions are proposed, including the development of a comprehensive system and register of solutions and materials that meet the principles of sustainable development; accumulation of optional but necessary data on the certification of materials and solutions by the developer; proportional reduction of the tax base to compensate for the additional costs arising from the use of more expensive but more environmentally friendly materials and solutions; introduction of a new system and registry of “green” solutions and materials that meet the principles of sustainable development. The authors also identify directions for future research.

A DSGE Model of the Russian Residential Real Estate Market

The paper develops a dynamic stochastic general equilibrium (DSGE) model of the Russian economy based on an endogenous housing sector and three categories of homeowners – patient, impatient and non-Ricardian. The DSGE model is applied from the first quarter of 2010 to the fourth quarter of 2019 using a Bayesian method for minimizing the discrepancy between theoretical and empirical impulse responses to a shock due to modified terms of trade. The model is then employed to provide a quantitative assessment of how macro variables respond to shocks generated by the housing market, interest rates, mortgage subsidies, financial liberalization, and altered terms of trade. At the same time, the impact of shocks on a number of economic indicators is largely determined by the functional form of household utility, as demonstrated by the robustness test. The results obtained based on the model also do not demonstrate a strong inertial effect in the economy due to the revival of the residential real estate construction sector, and they contradict a number of studies and expert estimates based primarily on the input-output model. One reason for this discrepancy may be the analysis, which is based on a horizontal supply curve, resulting in an overestimation of the impact of the construction sector on the economy. This DSGE model can serve as a starting point for scenario-based projections of the dynamics of the residential real estate market and the associated mortgage market, for testing the impact of various policy measures on the housing sector, and for assessing their effects on various categories of households.

Modeling Nairobi Residential Real Estate Prices using ARIMA

The residential real estate market is big and affords investors investment opportunities. The price changes are key in determining the overall return. Structural and atheoretical models are the two main approaches to modeling real estate prices. Structural models link prices to fundamental factors such as economic indicators and property supply, amongst others. Atheoretical models attempt to predict prices by leveraging on the statistical properties of time series data and may be extended to augment fundamental factors. This study focused on time series modeling using ARIMA. The objective of the paper was to identify a suitable ARIMA model that is efficient in predicting house prices in Nairobi. The training data was for the period 2010Q3 to 2019Q2. The out of sample test data was for six quarters: 2019Q3 to 2020Q4. The Box-Jenkins methodology was adopted. Seven ARIMA models and six AR models were identified, estimated, and used in predicting prices using out of sample data. The study found out that AR models outperformed ARIMA models. The paper contributes to knowledge being among the first to apply ARIMA in Nairobi house market using hedonic house prices. The paper may inform investment strategy and portfolio management by investors. It may inform policy since house price forecasts may have social and economic effects.

IMPACT OF SOME FACTORS ON PRICING IN THE REAL ESTATE MARKET OF RUSSIAN MEGACITIES

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.