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FORECAST OF THE DYNAMICS OF WORLD IMPORT BY COMMODITY GROUPS

https://doi.org/10.21202/1993-047X.12.2018.3.502-522

EDN: UZCIBI

Abstract

Objective: to forecast the structure and volume of world imports by commodity groups.Methods: statistical processing of global trade data with Big Data methods, regression and correlation analysis.Results: the Russian economy needs to restructure exports. To solve this problem, it is important to assess and forecast the global demand for certain goods. The article presents the results of the analysis of the main trends and forecasts of the development of individual industries, as well as their place in the global trade. It is shown that in accordance with the forecasts of analysts, there are significant prospects in the coming years in the fields of pharmaceutics, automotive industry, aircraft production, telecommunications, etc.UNCTAD data with a sample of product groups for each country were used to model the forecast demand for product groups. As a result of the trends modeling, the article identifies the main product categories that will have the greatest growth in the global trade. It is established that the constructed forecasts correspond to the data of economic research and forecasts of analytical companies. The article also determines the relationship between imports of goods by country and various indicators. The indicators that are characterized by the highest level of correlation with the studied product categories are revealed. On the basis of the obtained results, the conclusions are formulated about the most promising sectors for Russian exports in order to transit to a non-resource economy.Scientific novelty: the technique is developed, which enables to make long-term forecasts of trade dynamics of large volumes of data.Practical significance: the results of the forecast should be used to determine the priorities of Russia’s industrial policy aimed at accelerated transition to a non-resource economy.

About the Authors

S. Yu. Malkov
Institute for Economics of the Russian Academy of Sciences
Russian Federation


S. E. Bilyuga
Moscow State University named after M. V. Lomonosov
Russian Federation


O. I. Davydova
Limited Liability company "iDecide Consulting"
Russian Federation


References

1. Diebold F. X. A Personal Perspective on the Origin(s) and Development of “Big Data”: The Phenomenon, the Term, and the Discipline, Second Version, PIER Working Paper Archive report, Penn Institute for Economic Research. Department of Economics, University of Pennsylvania, 2012.

2. Mashey J. Big Data and the Next Wave of InfraStress. 1998. Usenix.org

3. Jordan M. I. On Statistics, Computation and Scalability // Bernoulli. 2013. Vol. 19. Iss. 4. Pp. 1378-1390. DOI: 10.3150/12-bejsp17

4. Kleiner A., Talwalkar A., Sarkar P., Jordan M. I. A Scalable Bootstrap for Massive Data // Journal of the Royal Statistical Society: Series B (Statistical Methodology). 2014. Vol. 76. Iss. 4. Pp. 795-816. DOI: 10.1111/rssb.12050

5. Ma P., Sun X. Leveraging for Big Data Regression // WIREs Computational Statistics. 2014. Vol. 7. Iss. 1. Pp. 70-76. DOI: 10.1002/wics.1324

6. A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data / F. Liang, Y. Cheng, Q. Song, J. Park, P. Yang // Journal of the American Statistical Association. 2013. Vol. 108. Iss. 501. Pp. 325-339. DOI: 10.1080/01621459.2012.746061

7. Maclaurin D., Adams R. P. Firefly Monte Carlo: Exact MCMC with Subsets of Data. arXiv preprint arXiv:1403.5693. 2014.

8. Swanson N. Money and Output Viewed Through a Rolling Window // Journal of Monetary Economics. 1998. Vol. 41. Iss. 3. Pp. 455-474. DOI: 10.1016/s0304-3932(98)00005-1

9. Grigoryev R. A. The interdependence between stock markets of BRIC and developed countries and the impact of oil prices on this interdependence: PhD thesis. University of Portsmouth, 2010. URL: http://eprints.port.ac.uk/4143/ (дата обращения: 12.06.2018).

10. Григорьев Р. А. Оценка стабильности отклонения гипотезы при использовании метода двигающегося окна с заданными размерами // Управление финансовыми рисками. 2018. № 3 (55). С. 202-216.

11. Chen X., Xie M. G. A Split-and-Conquer Approach for Analysis of Extraordinarily Large Data // Statistica Sinica. 2014. Vol. 24. Pp. 1655-1684. DOI: 10.5705/ss.2013.088

12. Song Q., Liang F. A Split-and-merge Bayesian Variable Selection Approach for Ultrahigh Dimensional Regression // Journal of the Royal Statistical Society: Series B (Statistical Methodology). 2014. Vol. 77 (5). Pp. 947-972. DOI: 10.1111/rssb.12095

13. Обзор тенденций на глобальном и российском фармацевтическом рынке / Frost & Sullivan, Рынок инноваций и инвестиций Московской биржи, Фонд развития промышленности. 2017. C. 5. URL: https://yadi.sk/i/lTIEuNOq3ELt43 (дата обращения: 12.06.2018).

14. Крупнейшие автомобильные рынки мира в 2030 году: страны с формирующимся рынком преображают мировую автомобильную промышленность: Тематический доклад SIEMS, Институт исследования быстрорастущих рынков СКОЛКОВО. 2017. C. 2. URL: https://iems.skolkovo.ru/downloads/documents/SKOLKOVO_IEMS/Research_Reports/ SKOLKOVO_IEMS_Research_2010-05-10_ru.pdf (дата обращения: 12.06.2018).

15. Deloitte. Global aerospace and defense industry outlook: Growth prospects and trends remain upbeat. 2017. P. 5. URL: https://www2.deloitte.com/vi/en/pages/manufacturing/articles/global-a-and-d-outlook.html#2017 (дата обращения: 12.06.2018).

16. Рудник И. В. Мировой рынок телекоммуникационного оборудования: драйверы конъюнктурных изменений // Российский внешнеэкономический вестник. 2016. № 2. С. 114. URL: https://cyberleninka.ru/article/v/mirovoy-rynok- telekommunikatsionnogo-oborudovaniya-drayvery-konyunkturnyh-izmeneniy (дата обращения: 12.06.2018).

17. Атлас производителей телекоммуникационного оборудования России / J'son & Partners Consulting. 2017. URL: http:// json.tv/ict_telecom_analytics_view/atlas-proizvoditeley-telekommunikatsionnogo-oborudovaniya-rossii-2017-g-20170207025322 (дата обращения: 12.06.2018).

18. Agricultural Outlook 2016-2025 / OECD-FAO. 2016. P. 1. URL: http://www.fao.org/3/a-i5851e.pdf (дата обращения: 12.06.2018).

19. The Outlook for Energy: A View to 2040 / Exxon Mobil. 2017. P. 8. URL: https://cdn.exxonmobil.com/~/media/global/files/ outlook-for-energy/2017/2017_outlook_for_energy_highlights.pdf (дата обращения: 12.06.2018).

20. Outlook 2017 edition / British Petroleum Energy. P. 6. URL: https://www.bp.com/content/dam/bp-country/de_de/PDFs/ energie-analysen/bp-energy-outlook-2017.pdf (дата обращения: 12.06.2018).

21. Merchandise trade matrix - detailed products, imports in thousands of dollars, annual, 1995-2015 / United Nations Conference on Trade and Development (UNCTAD). URL: http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=24740 (дата обращения: 12.06.2018).

22. World Oil Outlook 2040 / Organization of the Petroleum Exporting Countries. 2017. P. 10. URL: https://www.opec.org/ opec_web/flipbook/WOO2017/WOO2017/assets/common/downloads/WOO%202017.pdf (дата обращения: 12.06.2018).

23. Telecom Equipment Market Research Report - Global Forecast up to 2023 / Market Research Future. 2018. URL: https:// www.marketresearchfuture.com/reports/telecom-equipment-market-4441 (дата обращения: 12.06.2018).

24. Yager D. Electric cars won't bring down oil prices anytime soon. 2017. URL: https://www.businessinsider.com/electric- cars-oil-price-2017-7 (дата обращения: 12.06.2018).

25. World Preview 2017, Outlook to 2022 / EvaluatePharma. 2017. P. 5. URL: http://info.evaluategroup.com/rs/607-YGS-364/ images/WP17.pdf (дата обращения: 12.06.2018).

26. Global Gas & LNG Outlook to 2030 / McKinsey Energy Insights. URL: https://www.mckinseyenergyinsights.com/services/ market-intelligence/reports/global-gas-and-lng-outlook/ (дата обращения: 12.06.2018).

27. Global trends in oil & gas markets to 2025 / LUKOIL. P. 32. URL: https://www.lukoil.be/pdf/Trends_Global_Oil_ENG. pdf (дата обращения: 12.06.2018).

28. British Petroleum Energy Outlook 2017 edition. P. 96. URL: https://www.bp.com/content/dam/bp-country/de_de/PDFs/ energie-analysen/bp-energy-outlook-2017.pdf (дата обращения: 12.06.2018).

29. The Department of Industry, Innovation and Science, Resources and Energy Quarterly / Australian Government. 2018. P. 36. URL: https://publications.industry.gov.au/publications/resourcesandenergyquarterlymarch2018/documents/Resources-and-Energy- Quarterly-March-2018.pdf (дата обращения: 12.06.2018).

30. Deluce A. The Top Gold Producers in 2017: Companies and Nations. 2018. URL: http://www.goldtelegraph.com/top-gold- producers-in-2017 (дата обращения: 12.06.2018).

31. GFMS gold survey 2017 Q4 Update & Outlook / Thomson Reuters. 2018. P. 5. URL: http://images.financial-risk-solutions. thomsonreuters.info/Web/ThomsonReutersFinancialRisk/%7B206945da-ec32-4877-8faa-ce995df9c074%7D_GFMS_Gold_ Survey_2017_Q4_Update.pdf (дата обращения: 12.06.2018).

32. Global Market Forecast 2017-2036 / Airbus // Growing horizons. 2017. P. 9. URL: https://airbus-dev63.adobecqms.net/ content/dam/corporate-topics/publications/backgrounders/Airbus_Global_Market_Forecast_2017-2036_Growing_Horizons_full_ book.pdf (дата обращения: 12.06.2018).

33. Shipment forecast of laptops, desktop PCs and tablets worldwide from 2010 to 2022 // Statista. URL: https://www.statista. com/statistics/272595/global-shipments-forecast-for-tablets-laptops-and-desktop-pcs/ (дата обращения: 12.06.2018).

34. World Development Indicators // World Bank Data. URL: http://www.worldbank.org/ (дата обращения: 12.06.2018).


Review

For citations:


Malkov S.Yu., Bilyuga S.E., Davydova O.I. FORECAST OF THE DYNAMICS OF WORLD IMPORT BY COMMODITY GROUPS. Actual Problems of Economics and Law. 2018;12(3):502-522. (In Russ.) https://doi.org/10.21202/1993-047X.12.2018.3.502-522. EDN: UZCIBI

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ISSN 2782-2923 (Print)