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dc.contributor.authorSukhanova, E. I.en
dc.contributor.authorShirnaeva, S. Y.en
dc.contributor.authorMokronosov, A. G.en
dc.coverage.spatialRSVPUen
dc.coverage.spatialSCOPUSen
dc.date.accessioned2016-11-22T08:10:41Z-
dc.date.available2016-11-22T08:10:41Z-
dc.date.issued2016-
dc.identifier.issn1306-3065-
dc.identifier.otherhttps://www.scopus.com/record/display.uri?origin=resultslist&eid=2-s2.0-84994189366scopus_url
dc.identifier.urihttps://elar.rsvpu.ru/handle/123456789/15200-
dc.description.abstractThe urgency of the research topic was stipulated by the necessity to carry out an effective controlled process by the economic system which can hardly be imagined without indices forecasting characteristic of this system. An econometric model is a safe tool of forecasting which makes it possible to take into consideration the trend of indices development in the past and their cause and effect interrelations. The aim of the article is to build econometric models for macroeconomic indices forecasting, reflecting Russia’s economy stabilization processes. In the process of research econometric modeling methods were used which allow to build, estimate and control the quality of various econometric models. In the given research the following models were built and analyzed: autoregressive integrated moving average model, vector auto-regression model, simultaneous equations system; the comparison of forecast possibilities and forecast accuracy of models built; forecast values of considered macroeconomic indices for the next periods were received. As to the results of study some preference can be given to forecasting on the basis of autoregressive models. The materials of the article can be quite useful for researchers, dealing with problems of modeling and economic processes forecasting, both in their scientific and practical activity. © 2016 Sukhanova, Shirnaeva and Mokronosov.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherIJESEen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceInternational Journal of Environmental and Science Educationen
dc.subjectAUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODELen
dc.subjectFORECASTINGen
dc.subjectMACROECONOMIC INDICESen
dc.subjectSIMULTANEOUS EQUATIONS SYSTEMen
dc.subjectVECTOR AUTO-REGRESSION MODELen
dc.titleEconometric models for forecasting of macroeconomic indicesen
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dcterms.audienceOtheren
dcterms.audienceParents and Familiesen
dcterms.audienceResearchersen
dcterms.audienceSchool Support Staffen
dcterms.audienceStudentsen
dcterms.audienceTeachersen
local.description.firstpage9191-
local.description.lastpage9205-
local.issue16-
local.volume11-
local.identifier.scopus84994189366-
local.identifier.eid2-s2.0-84994189366-
local.identifier.affiliationSamara State University of Economics, Samara, Russian Federationen
local.identifier.affiliationRussian State Vocational Pedagogical University, Ekaterinburg, Russian Federationen
local.identifier.sourceScopusen
local.identifier.otherSukhanova, E.I., Samara State University of Economics, Samara, Russian Federationen
local.identifier.otherShirnaeva, S.Y., Samara State University of Economics, Samara, Russian Federationen
local.identifier.otherMokronosov, A.G., Russian State Vocational Pedagogical University, Ekaterinburg, Russian Federationen
Располагается в коллекциях:Научные публикации, проиндексированные в SCOPUS и WoS

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