Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/91508
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dc.contributor.authorMyasnikov, A. A.en
dc.contributor.authorМясников, А. А.ru
dc.date.accessioned2020-10-12T09:49:22Z-
dc.date.available2020-10-12T09:49:22Z-
dc.date.issued2018-
dc.identifier.citationМясников А. А. Анализ факторов совокупной факторной производительности российских регионов / А. А. Мясников. — DOI 10.17059/2018-4-9. — Текст : электронный // Экономика региона. — 2018. — Том 14, выпуск 4. — С. 1168-1180.ru
dc.identifier.issn2411-1406online
dc.identifier.issn2072-6414print
dc.identifier.otherhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85062062558&doi=10.17059%2f2018-4-9&partnerID=40&md5=9950032000ede94bf28d2f14d17dcb81m
dc.identifier.otherWOS:000452214100009wos
dc.identifier.urihttp://elar.urfu.ru/handle/10995/91508-
dc.description.abstractThe article investigates the major determinants of total factor productivity of Russian regions, in particular, the role of spillovers and agglomeration effects. Agglomeration effects are found to be important in regions located in the European part of Russia and in regions with low shares of extraction in the gross regional product (GRP): employment density in such regions turns out to be a significant factor determining total factor productivity. At the same time, neither employment density nor the degree of urbanization affects regions’ sensitivities to spillovers of total factor productivity from other regions — instead, these sensitivities depend only on the sizes of regional capitals and on shares of credit in GRP. This suggests that firms from regions with large capitals and high shares of credit in GRP are more actively expanding into neighboring regions: through their linkages with local firms in host regions, they may create positive correlations between total factor productivities in such host regions and their home regions. The analysis is based on methods of spatial econometrics — namely, the spatial lag and spatial error models with constant and variable spatial coefficients. The estimation is performed with maximum likelihood. © 2018 Institute of Economics Ural Branch of the Russian Academy of Sciences.en
dc.description.abstractПроанализированы факторы, влияющие на совокупную факторную производительность российских регионов. Дана оценка базовой модели пространственных лагов. Представлены результаты оценивания моделей с переменным коэффициентом при пространственной матрице.ru
dc.format.mimetypeapplication/pdfen
dc.language.isoruen
dc.publisherInstitute of Economics, Ural Branch of the Russian Academy of Sciencesen
dc.publisherИнститут экономики Уральского отделения РАНru
dc.relation.ispartofЭкономика региона. 2018. Том 14, выпуск 4ru
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.subjectAGGLOMERATION EFFECTSen
dc.subjectDEGREE OF URBANIZATIONen
dc.subjectECONOMIC GROWTHen
dc.subjectEMPLOYMENT DENSITYen
dc.subjectFINANCIAL INFRASTRUCTUREen
dc.subjectGROSS REGIONAL PRODUCTen
dc.subjectREGIONAL ECONOMICSen
dc.subjectSOCIAL INFRASTRUCTUREen
dc.subjectSPATIAL ECONOMETRICSen
dc.subjectTECHNOLOGICAL SPILLOVERSen
dc.subjectTOTAL FACTOR PRODUCTIVITYen
dc.titleАнализ факторов совокупной факторной производительности российских регионовru
dc.title.alternativeAnalysis of the determinants of total factor productivity in Russian regionsen
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.17059/2018-4-9-
dc.identifier.scopus85062062558-
local.description.firstpage1168-
local.description.lastpage1180-
local.issue4-
local.volume14-
dc.identifier.wos000452214100009-
local.identifier.eid2-s2.0-85062062558-
Appears in Collections:Economy of Regions

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