Abstract
The article describes a regressive mathematical model of passenger turnover in the air transport of the Russian Federation. The following are used as independent variables: the average flight costin the economy class of an aircraft per 1,000 km, the average monthly nominal accrued wages of employees in a full range of organizations, the average fare for travel in a second-class carriage of an express unbranded long-distance train per 100 km of track, the working population. Model parameters are identified using two alternative methods of regression analysis: mixed estimation and maximum consistency between the calculated and actual values of the output variable. The constructed versions of the model fully correspond to the content meaning of the independent variables included in their composition and have high accuracy. To solve the problems, the researcher should select one of them according to their features, namely, either the tendency to minimize the disrepancies between the predicted and actual values of passenger traffic in the future or the desire to identify future trends in the indicator's dynamics, possibly, with the greater accuracy.
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