Models of multiple regression as an instrument of regional mortgage markets’ functioning effectiveness assessment
- Authors: Korosteleva T.S.1, Tselin V.E.1
-
Affiliations:
- Samara National Research University
- Issue: Vol 12, No 3 (2021)
- Pages: 164-178
- Section: MATHEMATICAL AND INSTRUMENTAL METHODS OF ECONOMICS
- URL: https://journals.ssau.ru/eco/article/view/9875
- DOI: https://doi.org/10.18287/2542-0461-2021-12-3-164-178
- ID: 9875
Cite item
Full Text
Abstract
The article is dedicated to issues related to the formation of the Russian Federation regions’ economically justified classifications by housing mortgage lending (HML) system’s stage of development, for the implementation of mortgage markets’ selective government adjustment policy. The purpose of the study is to develop the methodology of regions’ mortgage potential assessment based on the search of additional application solutions in the area of rapid assessment and forecasting of regional mortgage market’s state. To achieve the purpose, an additional version of common methodology of Russian Federation regions’ systematic ranking by HML system’s stage of development is represented, and its main steps are structured. Within the third step of new methodology, a multiple regression model of Factor 1 (F1) is developed, which was interpreted in author’s early studies as a performance indicator of regional mortgage market’s functioning effectiveness. The model’s development was based on the statistical processing’s results of 510 observations in 85 Russian Federation regions in a period from 2014 to 2019. The high accuracy of model’s approximation has been proved, as well as its statistical reliability. The application capabilities of the model are represented, particularly the results of period 2020-2021 forecasting for Samara region and Saint-Petersburg city. The ways of managing the rating of region through targeted distribution of available regional and federal resources received by the models’ predictors are outlined. The novelty of this study is contained in the results of adaptation of the new assessment methodology, which is based on the obtainment of multiple regression model for Factor 1. The methodology base of the study consists of systematic analysis methods and multivariate statistics, particularly regressive and correlation analysis methods.
About the authors
Tatyana S. Korosteleva
Samara National Research University
Author for correspondence.
Email: korosteleva75@mail.ru
ORCID iD: 0000-0002-8519-5956
Candidate of Economic Sciences, assisstant professor of the Department of Management and Organization of Production
Russian Federation, 34, Moskovskoye shosse, SamaraVladimir E. Tselin
Samara National Research University
Email: vtzelin@mail.ru
ORCID iD: 0000-0001-8657-9903
Candidate of Economic Sciences, assisstant professor of the Department of Management and Organization of Production
Russian Federation, 34, Moskovskoye shosse, SamaraReferences
- Ivanova D.G., Shevnia V. I. Regional market of mortgage lending: problems and trends. State and municipal administration. Scholarly notes, 2018, no №1, pp. 76-81. Available at: https://cyberleninka.ru/article/n/regionalnyy-rynok-ipotechnogo-zhilischnogo-kreditovaniya-problemy-i- tendentsii-razvitiya. (In Russ.)
- Volkov A.A. Influence of Socio-Economic Factors on the Development of the Home Mortgage Lending Market: The Case of the Vologda Region. Regionology = Russian Journal of Regional Studies, 2021, 29(1), pp. 37-59. DOI: https://doi.org/10.15507/2413-1407.114.029.202101.037-059. (In Russ.)
- Svobodova L., Hedvicakova M. Mortgage Loans in the Regions of the Czech Republic. Proc. of the International Scientific Conference on Region in the Development of the Society, 2016. Sbornik prispevku z mezinarodni vedecke konference: region v rozvoji spolecnosti. Czech Republic, pp. 948-957.
- Mishura A.V., Bekareva S.V., Meltenisova E.N. Concentration in the banking sector and housing lending in Russian regions. Voprosy Ekonomiki, 2020, (4), pp. 107-128. Available at: https://doi.org/10.32609/0042-8736- 2020-4-107-128. (In Russ.)
- Patatouka E. Mortgage Market and Regional Development in Greece: Peculiarities and Consequences. - CIST2014. Fronts et frontieres des sciences du territoire, College international des sciences du territoire (CIST) , pp.297-306. URL: https://hal.archives-ouvertes.fr/hal-01353415/document.
- Koblyakova A., Hutchison N., Tiwari P. Regional Differences in Mortgage Demand and Mortgage Instrument Choice in the UK. Regional Studies, 2014, 48(9), pp. 1499-1513. doi: 10.1080/00343404.2012.750426.
- Koblyakova, A., Fleishman, L., Furman, O. Accuracy of households’ dwelling valuations, housing demand and mortgage decisions: Israeli case. Journal of Real Estate Finance and Economics, 2021. URL: https://doi.org/10.1007/s11146-021-09823-7.
- Guzikova L. How do Housıng Market and Mortgage Solve. The Housıng Problem in the Regıons of Russıa? In: Bilgin M., Danis H., Demir E., Can U. (eds) Regional Studies on Economic Growth, Financial Economics and Management. Eurasian Studies in Business and Economics, 2017, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-54112-9_21.
- Aranaz M.F., Marquez J.A. Identifying Regional Differences in the Spanish Mortgage Market with Sheaf Methodology. Esic Market Economics and Business Journal, 2013, 44 (3), pp.159-177. doi: 10.7200/esicm.146.0443.4i.
- Hurst E., Keys B.J., Seru A., Vavra J. Regional Redistribution through the US Mortgage Market. American Economic Review, 2016, 106 (10), pp. 2982-3028. doi: 10.1257/aer.20151052.
- Gritsenko T.S., Peredera Zh.S., Teryaeva A.S. Identification of morgage lending development level in regions through cluster analysis and integrated assessment. Naukovedenie, 2017, vol. 9, no. 3, pp. 51–60. Available at: https://naukovedenie.ru/PDF/28EVN317.pdf. (In Russ.)
- Kuznetsova E. O. Assessment of the development of the mortgage market in the regions of Russia. Entrepreneur’s Guide, 2017, no 33, pp. 123-129. Available at: https://www.pp-mag.ru/jour/article/view/14/14. (In Russ.)
- Grezina M.A. Economic-mathematical methods for acceptance of administrative decisions in mortgage lending sphere. Izvestiya SFedU. Engineering Sciences, 2011, no. 11(124), pp. 51–60. Available at: https://www.elibrary.ru/item.asp?id=17050374. (In Russ.)
- Helbich M., Brunauer W., Hagenauer J., Leitner M. Data-Driven Regionalization of Housing Markets. Annals of the Association of American Geographers, 2013, Vol. 103, Iss. 4, pp. 871-889. doi: 10.1080/00045608.2012.707587.
- Vatansever M., Demir I., Hepsen A. Cluster and forecasting analysis of the residential market in Turkey: An autoregressive model-based fuzzy clustering approach. International Journal of Housing Markets and Analysis, 2019, Vol. 13, Iss. 4, pp. 583-600. doi: 10.1108/IJHMA-11-2019-0110.
- Wiersma S., Just T., Heinrich M. Segmenting German housing markets using principal component and cluster analyses. International Journal of Housing Markets and Analysis, 2021, Vol. ahead-of-print No. ahead-of-print. URL: https://doi.org/10.1108/IJHMA-01-2021-0006.
- Kostylеv A. V. Regional housing markets: experience of classification. Aktualnye problemy ekonomiki i prava, 2014, no. 1 (29), pp. 181–185. Available at: https://econpapers.repec.org/article/scn029045/15741725.htm. (In Russ.)
- Fliginskikh T.N., Sycheva I.I. Differentiationof regional housing markets: cluster analysis and classification.
- Belgorod State University. Scientific Bulletin. Series: Economics. Information technologies, 2012, Vol. 21, no 1–1, pp. 36-41. Available at: https://cyberleninka.ru/article/n/differentsiatsiya-regionalnyh-rynkov-zhilya- klasternyy-analiz-i-klassifikatsiya. (In Russ.)
- Korosteleva T.S., Tselin V.Y. Assessing the mortgage potential capacity of regions: A methodology and indicators. Regional Economics: Theory and Practice, 2020, vol. 18, issue 2 (473), pp. 381–396. DOI: http://doi.org/10.24891/re.18.2.381. (In Russ.)
- Tselin V.Y., Korosteleva T.S. Differential Indicator of the Level of Development of the Mortgage System of the Region. In: Education Excellence and Innovation Management: A 2025 Vision to Sustain Economic Development during Global Challenge. Proceedings of the 35th International Business Information Management Association Conference (IBIMA). Spain, April 1–2, 2020, pp. 10621–10631.
- Dobrovol'skaya T. V., Stennikov V. A. Monitoring i prognozirovanie teplopotrebleniya s pomoshch'yu regressionnykh modeley. Modeling and Forecasting Social, Ecologic and Economic Development of the Region: materials of the All-Russian Youth School-Conference with Foreign Participation. Ulan-Ude, Publishing house BNC CO RAN, 2016, pp. 126–133. (In Russ.).
- Sharashova E.E., Kholmatova K. K., Gorbatova M. A., Grjibovski A.M. Application of the multivariable linear regression analysis in healthcare using SPSS software. Science & Healthcare, 2017. no 3, pp. 5-31. Available at: https://cyberleninka.ru/article/n/primenenie-mnozhestvennogo-lineynogo-regressionnogo-analiza-v- zdravoohranenii-s-ispolzovaniem-paketa-statisticheskih-programm-spss. (In Russ.)
- Stennikov V.A., Dobrovolskaya T.V. Methods of regressive analysis in researching thermal-consumption in Russia. Vestnik of the Plekhanov Russian University of Economics, 2018, (2), pp. 142-153. Available at: https://doi.org/10.21686/2413-2829-2018-2-142-153. (In Russ.).
- Kryshtanovsky А.О. Limitations of the regression analysis method. Sociology: Methodology, Methods, Mathematical Modeling (Sociology: 4m), 2000, no 12. Available at: https://elibrary.ru/item.asp?id=18053689&. (In Russ.).
- Korosteleva T.S., Tselin V. Y. Management of Regional Imbalances in the Russian Mortgage Market Using the Principal Components Method. Journal of Economics Studies and Research, 2021, Vol. 2021 (2021). doi: 10.5171/2021.126542.