Statistical analysis of mortgage housing lending in the Russian Far East

he article analyzes the trends in mortgage housing lending in the Russian Far East in the period 2006-2017. To build a model, factor signs were identified that affected the volume of mortgage lending and the essence of their relationship with lending volumes was revealed. To justify the inclusion / non-inclusion of the factor signs in the multiple regression model, a check of factors for the presence / absence of multicollinearity was carried out, according to which the factor of the Far Eastern Federal District (FEFD) population and the share of emergency housing were included in the model. A linear model of multiple regression was constructed and the significance of the relationship between the attributes based on the Fisher F-test was assessed, statistics on the significance of the multiple regression coefficients based on the Student t-test were estimated, and the average approximation error was calculated. The forecast of the volumes of mortgage lending was calculated in two ways. A linear model of the main trend in the dynamics of mortgage lending indicators was built, based on which a probable forecast of the volume of mortgage loans in the Far East for the period 2018-2020 was calculated. using the extrapolation method. Using the method of analytical equalization, models of the main tendency of indicators of average per capita incomes of the population, population, indicator of the proportion of emergency housing stock of the FEFD were built. These models were used to determine confidence intervals of the values of the studied indicators for the period up to 2020. according to the multiple regression model. Based on the positive results of assessing the statistical significance of the constructed model of multiple regression, the forecast was refined taking into account the confidence intervals of the forecast indicators for the population, average per capita income and the share of emergency housing in the Far Eastern Federal District.

Mortgage lending, preferential mortgage, Russian Far East, correlation, regression, multicollinearity of factors, modelling, regression coefficient, statistical significance, forecast, extrapolation

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