RUDN Journal of EconomicsRUDN Journal of Economics2313-23292408-8986Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University)1717310.22363/2313-2329-2017-25-1-63-73Research ArticleMODEL FOR FORECASTING OF VOLUME AND STRUCTURE “GREY IMPORT”AnisimovV G<p>Doctor of Technical Sciences, Professor of the Department of Information Systems in Economics and Management, St. Petersburg Polytechnic University, Peter the Great</p>an-33@yandex.ruAnisimovE G<p>Doctor of technical sciences, Professor, Director of the Research Institute of the RTA</p>an-33@rambler.ruGapovM R<p>Candidate of Economic Sciences, Deputy Minister of Economic Development of Karachay-Cherkess Republic</p>mgapov@gmail.comSaurenkoT N<p>Doctor of Economics, Head of the Department of Customs at RUDN University</p>tanya@saurenko.ruPeter the Great St.Petersburg Polytechnic UniversityRussian customs academyMinistry of Economic Development of Karachay-Cherkess RepublicPeoples’ friendship University of Russia15122017251637324102017Copyright © 2017, Anisimov V.G., Anisimov E.G., Gapov M.R., Saurenko T.N.2017<p>The revenues of the Federal budget of the Russian Federation to a significant extent, is formed at the expense of customs payments. Hence, in the case of large amounts of gray import, the states economy can be significantly affected. The performance measures against gray import depends on the timely and adequate prediction of its structure and volumes. This forecast assumes the availability of appropriate models. However, the currently known models do not provide the timeliness and adequacy of the forecast.The article suggests a model for the current prediction of volume and structure of gray import. The model allowed stochastic representation of the gray imports, simulating the processes of its formation. This simulation allows more adequately than the commonly used regression and expert models, considering available information about the gray import and thereby improves prediction accuracy its volume and structure. The information basis of the proposed model are data of the risk management system of the Federal customs service of the Russian Federation. The application of the proposed model allows near real-time to predict the structure and volume of gray imports and on this basis to develop the necessary measures to counter it.</p>“gray import”the volumestructuremodelpredictionreaction«серый импорт»объемструктурамодельпрогнозированиепротиво-действие[Anisimov V.G., Anisimov Ye.G., Arslanov R.F., Arslanova A.P., Bogoeva Ye.M., Goloskokov V.I., Lipatova N.G., Popov V.V., Saurenko T.N., Tebekin A.V. Ekonomicheskiy i tamozhennyy risk-menenedzhment: monografiya. M.: RIO Rossiyskoy tamozhennoy akademii, 2015. 180 s. (In Russ).][Anisimov V.G., Anisimov Ye.G., Bogoeva Ye.M., Saurenko T.N., Garkushev A.Yu. Metodologicheskie osnovy postroeniya pokazateley effektivnosti kontrolnoy deyatelnosti organov gosudarstvennoy vlasti. Voprosy oboronnoy tekhniki. Seriya 16: Tekhnicheskie sredstva protivodeystviya terrorizmu. 2015. № 3-4. S. 17—20. (In Russ).][Anisimov V.G., Anisimov Ye.G., Kokhanova N.M., Malkova A.L. 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