UDC 51-77
DOI: 10.36871/2618-9976.2023.10.010
Authors
Ekaterina A. Zakrevskaya,
Candidate of Economic Sciences, Associate Professor, Associate Professor of the Department
of Mathematical Methods in Economics, Plekhanov Russian University of Economics, Moscow, Russia
Olga A. Sviridova,
Candidate of Economic Sciences, Associate Professor of the Department of Mathematical Methods
in Economics, Plekhanov Russian University of Economics, Associate Professor of the Department
of Data Analysis and Machine Learning, Financial University under the Government of the Russian
Federation, Moscow, Russia
Daria M. Popova,
Postgraduate Student of the Department of Mathematical Methods in Economics, Plekhanov Russian
University of Economics, Moscow, Russia
Abstract
The article conducts a cluster analysis of regions of the Russian Federation according to mortgage lending indicators to obtain a stable grouping, as well as discriminant analysis to distribute regions that are not included in a stable grouping. A classification has been obtained that divides regions into four main groups, characterized by different levels of mortgage lending conditions and development of the housing construction market.
Keywords
Cluster analysis, Mortgage lending, Discriminant analysis
