Nowcasting of Russian manufacturing output using business survey data
https://doi.org/10.25206/2542-0488-2023-8-4-152-160
EDN: OMMHGS
Abstract
This article is devoted to checking the possibility of using business survey data surveys to nowcasting of Russian manufacturing output: analysis of business cycles and short-term forecasting (1 month ahead). The study uses data from business surveys of the Federal State Statistics Service, the Russian Union of Industrialists and Entrepreneurs and S&P Global. The results of these surveys are published promptly (20 days or more ahead of the release of official statistics) and are freely available. The study shows that the indicators of the Federal State Statistics Service (economic situation, number of employees, business confidence index, output, demand, export) allow to increase the accuracy of forecasts by 21–39 % and have a high correlation with business cycles of the manufacturing industry. In general, the use of most business survey indicators improves short-term forecasts of manufacturing output, more than half of the indicators have a correlation coefficient greater than 0,8 with the business cycles of this sector of the economy.
About the Author
R. E. Gartvich
Dostoevsky Omsk State University
Russian Federation
Russian Federation
Gartvich Roman Evgenyevich, Graduate Student of Economics and Finance Department; Lead Economist of the Omsk Region Branch of the Siberian Main Directorate of the Central Bank of the Russian Federation
AuthorID: 1015207
Omsk
References
1. Shcherbakov V. S., Kharlamova M. S., Gartvich R. E. Metody i modeli naukastinga ekonomicheskikh pokazateley s pomoshch’yu poiskovykh zaprosov [Methods and models of nowcasting of economic indicators using search queries] // Razvitiye ekonomiki regionov: prostranstvennaya transformatsiya, global’nyye vyzovy i perspektivy ekonomicheskogo rosta. Regional Economic Development: Spatial Transformation, Global Challenges and Prospects for Economic Growth / ed. by S. A. Samusenko, resp. S. A. Kozlova. Krasnoyarsk, 2022. P. 117– 127. EDN YWNMHG. (In Russ.).
2. Federal’naya sluzhba gosudarstvennoy statistiki. Natsional’nyye scheta. Proizvedennyy VVP [Federal State Statistics Service. National accounts. Produced GDP]. URL: https://rosstat.gov.ru/statistics/accounts (accessed: 07.09.2023). (In Russ.).
3. Lehmann R. The Forecasting Power of the Ifo Business Survey // CESifo Working Paper. 2020. No. 8291. 67 p. DOI: 10.2139/ssrn.3603848. (In Engl.).
4. S&P Global. Purchasing Managers’ Index (PMI). URL: https://www.spglobal.com/marketintelligence/en/mi/products/pmi.html (accessed: 08.09.2023). (In Engl.).
5. OECD. Business Tendency Surveys: A Handbook, 2003. URL: https://read.oecd-ilibrary.org/economics/businesstendency-surveys_9789264177444-en#page2 (accessed: 10.09. 2023). (In Engl.).
6. Bank Rossii. Monitoring predpriyatiy dlya tseley denezhnokreditnoy politiki: mirovoy opyt [Bank of Russia. Monitoring of enterprises for monetary policy purposes: world experience], 2022. URL: https://cbr.ru/Content/Document/File/131901/mp_we.pdf (accessed: 07.09.2023). (In Russ.).
7. Bank Rossii. Indikatory delovoy aktivnosti i inflyatsii na osnove monitoringa predpriyatiy. Analiticheskaya zapiska [Bank of Russia. Indicators of business activity and inflation based on enterprise monitoring. Analytical note], 2021. URL:http://www.cbr.ru/content/document/file/119543/analytic_note_20210322.pdf (accessed: 07.09.2023). (In Russ.).
8. Ifo Institute. Ifo Business Climate Index for Germany. URL: https://www.ifo.de/en/survey/ifo-business-climate-indexgermany (accessed: 07.09.2023). (In Engl.).
9. Sauer S., Wohlrabe K. The new ifo Business Climate Index for Germany // CESifo Forum. 2018. Vol. 19 (02). P. 59–64. (In Engl.).
10. Aprigliano V. The Relationship between the PMI and the Italian Index of Industrial Production and the Impact of the Latest Economic Crisis (September 23, 2011) // Bank of Italy Temi di Discussione (Working Paper). No. 820. DOI: 10.2139/ssrn.1960900. (In Engl.).
11. Herwadkar Snehal S., Saurabh G. Is PMI a good leading indicator of industrial production?: Evidence from India // MPRA Paper No. 97924. 2020. URL: https://mpra.ub.uni-muenchen.de/97924/ (accessed: 07.09.2023). (In Engl.).
12. Federal’naya sluzhba gosudarstvennoy statistiki. Operezhayushchiye indikatory po vidam ekonomicheskoy deyatel’nosti [Federal State Statistics Service. Leading indicators by type of economic activity]. URL: https://rosstat.gov.ru/leading_indicators (accessed: 07.09.2023). (In Russ.).
13. Ob utverzhdenii Federal’nogo plana statisticheskikh rabot: Rasporyazheniye Pravitel’stva RF ot 06.05.2008 № 671-r (red. ot 10.06.2023) [On approval of the Federal Plan of Statistical Work: Decree of the Government of the Russian Federation No. 671-r dated 06.05.2008 (ed. dated 10.06.2023)]. Available at «Consultant Plus» System. (In Russ.).
14. Rossiyskiy soyuz promyshlennikov i predprinimateley. Indeks delovoy sredy [Russian Union of Industrialists and Entrepreneurs. Business Environment index]. URL: https://rspp.ru/activity/analytics/ (accessed: 07.09.2023). (In Russ.).
15. EMISS. Federal’naya sluzhba gosudarstvennoy statistiki. Obrabatyvayushchiye proizvodstva. Indeks proizvodstva [UIISS. Federal State Statistics Service. Manufacturing industries. Production index]. URL: https://www.fedstat.ru/organizations/ (accessed: 07.09.2023). (In Russ.).
16. Stratford K. Nowcasting world GDP and trade using global indicators // Bank of England Quarterly Bulletin. 2013. Q3. P. 233–243. (In Engl.).
17. Abberger K., Nierhaus W. Ifo Geschäftsklima, Produktion und Ertragslage in der gewerblichen Wirtschaft [Ifo Business Climate, Production and Earnings Situation in the Commercial Economy] // Ifo Schnelldienst. Ifo Schnelldienst. 2011. No. 64 (03). P. 21–24. (In Germ.).
Review
For citations:
Gartvich R.E. Nowcasting of Russian manufacturing output using business survey data. Omsk Scientific Bulletin. Series Society. History. Modernity. 2023;8(4):152-160. (In Russ.) https://doi.org/10.25206/2542-0488-2023-8-4-152-160. EDN: OMMHGS
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