DOI: 10.33917/mic-6.119.2024.40-49

The avalanche-like flow of innovations, instability in the global political arena, sanctions policy, shortage of qualified personnel complicates the development of strategic sectoral solutions for staffing in the Russian labor market. The personnel support system, as a complex system, is formed by a set of interconnected and interacting, but structurally relatively autonomous subsystems. At the corporate level, the system of continuous training and human resource development is aimed at meeting the strategic need of the company for qualified personnel in its priority areas. The formation of training programs for the personnel reserve using foresight technologies allows you to focus the company’s resources and achieve the so-called «dynamic equilibrium» according to A. Bogdanov [1]. The transition from strategic forecasting of required qualifications in the industry to planning of demanded competencies based on foresight technologies makes it possible to increase the competitiveness of the company.

References:

1. Bogdanov A.A. Tectology. General organizational science: in 2 books. M.: Economica, 1989. 304 p.

2. Budzinskaya O.V. Personnel supply system as a mechanism for expanded reproduction of human resources: dis. Doctor of Economics: 08.00.05. M., 2022. 321 p.

3. Connor J., McDermott I. The art of systems thinking: essential knowledge about systems and a creative approach to problem solving. M.: Alpina Publisher, 2018. 256 p.

4. Martynov V.G., Budzinskaya O.V., Sheinbaum V.S. Design of a system of expanded reproduction of personnel for the fuel and energy complex in the context of the next reform of engineering education. Standard of living of the population of the regions of Russia. 2024. Vol. 20. No. 2. P. 243–257.

5. Golden hands: Russia has a total personnel shortage. Forbes. URL: https://www.forbes.ru/biznes/497478-zolotye-ruki-v-rossii-total-nyj-deficit-kadrov

6. Personnel reserve program. URL: https://rosnefteflot.rosneft.ru/Development/personnel/reserve/

7. Budzinskaya O.V. Forecasting the need for qualified personnel using the example of the oil and gas industry. Social and labor research. 2020; 40(3):81–89.

8. Budzinskaya O.V. Foresight of competence or forecasting the structure of personnel in the context of the global system of division of labor. Education. Science. Scientific personnel. 2020. No. 4. URL: https://cyberleninka.ru/article/n/forsayt-kompetentsii-ili-prognozirovanie-struktury-kadrov-v-usloviyah-mirovoi-sistemy-razdeleniya-truda

9. Mironova D.Yu., Baranov I.V., Pomazkova E.E., Rumyantseva O.N. Project management: application of foresight and industrial symbiosis in project management for sustainable development: Study guide ed. St. Petersburg: ITMO University, 2022. 95 p.

10. Rosneft: contribution to the implementation of the UN sustainable development goals. URL: https://www.rosneft.ru/Investors/Rosneft_vklad_v_realizaciju_ celej_OON/

11. Regulation of JSC RN-Moscow «Internal Labor Regulations». URL: https://edu.rosneft-azs.ru/upload/site1/edu-files/

DOI: 10.33917/es-4.196.2024.62-73

The paper reveals the content of the method of structural analysis as a basic approach in economic research, used in the study of economic changes. The purpose of the study is to demonstrate the areas of application of structural analysis and its part — macrostructural analysis, with outputs for the study of technological development and the formation of a strategy for economic policy and development. The methodology consists of empirical structural analysis, comparative method and taxonomic approach. The overall result can be considered the identified areas of application of structural analysis in the macroeconomic part of its application, the possibilities and mistakes of applying macrostructural analysis to the study of economic growth and structural transformation of the economy. Let us note that many issues of the application of macrostructural analysis in economic science have been poorly studied. Often in studies it is replaced by the general method of structural analysis, which is reduced exclusively to the assessment of “input-output”, the structure of aggregate demand and production distributed across economic sectors. In fact, structural analysis is much broader, extends to micro and mesoeconomic objects of the economy, and is suitable not only for correcting current macroeconomic policies, but also for developing strategic plans for economic development and carrying out economic changes (reforms). An interpretation of changes within the framework of the “old — new” technologies structure is given, as well as proposals for taking into account technological development as an important condition for carrying out the structural and technological modernization of Russia.

References:

1. Shumpeter Y.A. Teoriya ekonomicheskogo razvitiya. Kapitalizm, sotsializm i demokratiya [Theory of Economic Development. Capitalism, Socialism and Democracy]. Moscow, Eksmo, 2007, 864 s.

2. Nort D. Ponimanie protsessa ekonomicheskikh izmeneniy [Understanding the Process of Economic Change]. Moscow, Vysshaya shkola ekonomiki, 2010, 256 p.

3. Barr R. Politicheskaya ekonomiya [Political Economy]. V 2 t. Moscow, Mezhdunarodnye otnosheniya, 1996.

4. Sukharev O.S. Strukturnyy analiz ekonomiki [Structural Analysis of the Economy]. Moscow, Finansy i statistika, 2012, 216 p.

5. Dedov L.A., Botkin O.I. Indeksnyy makrostrukturnyy analiz ekonomicheskoy dinamiki. Osnovnye ponyatiya i priemy makrostrukturnogo analiza [Index Macrostructural Analysis of Economic Dynamics. Basic Concepts and Techniques of Macrostructural Analysis]. Ekaterinburg, Izd-vo UrO RAN, 2013, 111 p.

6. Sukharev O.S. Strukturnye issledovaniya sovremennoy rossiyskoy ekonomicheskoy shkoly: osnovnye podkhody i perspektivy [Structural Research of the Modern Russian Economic School: Main Approaches and Prospects]. Vestnik Permskogo universiteta, 2022, vol. 17, no 1, pp. 5–26.

7. Leont’ev V.V. Izbrannye stat’i [Featured Articles]. Saint Petersburg, Nevskoe vremya, 1994, 366 p.

DOI: 10.33917/mic-4.117.2024.27-38

The article analyzes the global economic forecasts for 2024–2025 developed by the World Bank, the IMF, and the OECD. According to the May OECD report, one of the risks to economic development may be an acceleration of inflation in developed countries. In the United States, annual inflation accelerated to 3,5% in March 2024, compared to 3,2% in February. And the US Federal Reserve is ready to postpone the interest rate cut until November 2024. The IMF forecast for Russian GDP growth in 2024 has been improved to 3,2%, but reduced to 1,8% for 2025. For the United States, GDP growth is projected to be 2,1% in 2024, and 1,7% for 2025.

References:

1. Chugunov Artem. The Economy of Developing Overheating. The World Bank Shares the Position of the Bank of Russia on the Nature of Inflation in the Russian Federation. 04/15/2024. URL: https://www.kommersant.ru/doc/6648521

2. World Bank. 2024. Global Economic Prospects. January. Washington, DC: World Bank. URL: https://openknowledge.worldbank.org/server/api/core/bitstreams/7fe97e0a-52c5-4655-9207-c176eb9fb66a/content

3. Borovikova Kristina. Developing Economies Are Becoming More Attached to Developed Ones. Monitoring the World Economy. 05.04.2024. URL: https://www.kommersant.ru/doc/6622054

4. Borovikova Kristina. The Grounds for a Global Slowdown Are Being Selected. OECD expects moderate growth in 2024. 06.02.2024. URL: https://www.kommersant.ru/doc/6493747

5. Edovina Tatyana. Global fun. The IMF has raised its forecasts for the global and Russian economies. 30.01.2024. URL: https://www.kommersant.ru/doc/6479601

6. Today’s number. Inflation in the OECD in 2023. 08.02.2024. URL: https://www.kommersant.ru/doc/6495212

7. Borovikova Kristina. The global economy has received additional growth. The OECD has cautiously improved its global GDP forecast. 02.05.2024. URL: https://www.kommersant.ru/doc/6680489

8. OECD Economic Outlook, May 2024. URL: https://www.oecd.org/economic-outlook/may-2024/

9. Elvira Nabiullina’s press conference: increase in the key rate, peak inflation. Key points. URL: https://www.kommersant.ru/doc/6760711

DOI: 10.33917/mic-1.114.2024.68-74

The scientific article graphically displays the economic essence of the method of forecast scenarios in assessing the development of competitiveness of tourism services. Target (tactical) development blocks and target development scenarios based on the theory of even subsets have been identified. A matrix of alternative strategies and corresponding tourism growth scenarios at the meso-economic level have been developed: optimistic; pessimistic (risk assessment) and optimal scenario.

References:

1. Galiullin I.R. Innovative competitive advantages of service sector enterprises: macro, meso-level research. I.R. Microeconomics. 2017;6:68-73. (In Russ.).

2. Zhukovskaya I.V. Systematization of scientific approaches to managing competitiveness in the service sector: economic essence, criteria. Microeconomics. 2020;2:29-37. (In Russ.).

3. Leonov E.F. Increasing the competitiveness of small and medium-sized service enterprises based on the formation of institutional space: dis. Ph.D. econ. Sciences: 08.00.05. Leonov Egor Fedorovich. St. Petersburg, 2017. 206 p. (In Russ.).

4. Fatkhutdinov R.A. Managing the competitiveness of an organization. M.: EKSMO, 2005. pp. 542-543. (In Russ.).

5. Khusaenov R.R. Development of Innovative Infrastructure Services in The Conditions of Discreteness of Its Components. International Journal of Advanced Research in Engineering and Technology. 2020;11(3):276-291.

DOI: 10.33917/es-6.192.2023.68-69

Review of the book by A.A. Frenkel and A.A. Surkov “Forecasts Merging — an Effective Tool for Increasing Forecasting Accuracy”, dedicated to the analysis of accumulated knowledge about various approaches and methods for constructing a combined forecast. The book provides a forecast for manufacturing certain types of industrial products based on the use of various private and combined forecasting methods and makes a statistical comparison of their accuracy.

DOI: 10.33917/mic-6.113.2023.76-88

Forecasts are given for 2023–2028 global demand for oil and energy, as well as real GDP growth by region of the world. The linear regression models developed by the authors and graphs of the relationship between the annual growth rate of global GDP and the annual growth rate of global oil and energy demand are presented.

According to the authors, the fight against inflation by the US Federal Reserve and the Central Bank of Europe through raising interest rates leads to a decrease in investment and a decrease in the growth rate of GDP in the US and Europe.

References: 

1. «Prospects for the development of the world economy».  World Bank report dated June 05,2023. URL:  https://www.vsemirnyjbank.org/ru/publication/global- economic-prospects

2. The Central Bank kept the key rate at 7,5%

for the fifth time in a row. KOMMERSANT dated04/28/2023. URL: https://www.kommersant.ru/doc/5955429

3. The economy is reaching a plateau. GDP monitoring. KOMMERSANT dated 08/04/2023.

URL: https://www.kommersant.ru/doc/6138316

4. EDB macro forecast 2023–2025: economic growth forecast has been improved for all countries in the region. URL: https://eabr.org/press/releases/makroprognoz-eabr-2023–2025-prognozekonomicheskogo-rosta- uluchshen-dlya-vsekhstran-regiona/

5. IEA «Oil 2023 Analysis and forecast to 2028». June 2023. URL: https://www.iea.org/reports/oil-2023

6. IEA «World Energy Outlook 2022». URL:

https://iea.blob.core.windows.net/assets/830fe099–5530–48f2-a7c1–11f35d510983/WorldEnergyOutlook2022.pdf

DOI: 10.33917/mic-5.112.2023.16-22

The article examines the regional structure of investment in the development of renewable sources of electricity and the impact of the global energy crisis on its volume. Forecasts are made for the development of renewable energy based on the current state and the impact of the global energy crisis on the plans drawn up by the world community to achieve sustainable development goals. Structural changes in the global energy transition and, in particular, in the process of developing electricity generation based on renewable energy sources in the period from 2021 to 2022 are analyzed.

References: 

1. Energy Institute. Statistical Review of World Energy, 2023. URL: https://www.energyinst.org/statistical-review
2. Includes data from Cedigaz. FGE MENAgas service. URL: https://data.subak.org/dataset/gas-trade-in-bcm
3. Novak A. The global energy crisis: who is to blame and what to do? //Energy policy. 2022;2(168):4-11. (In Russ.).
4. IRENA. Renewable energy statistics 2023. URL: https://www.irena.org/Publications/2023/Jul/Renewable-energy-statistics-2023
5. Miles S., Collins G., Mikulska A. US Needs LNG to Fight a Two-Front Gas War, 2022. URL: https://www.bakerinstitute.org/research/us-needs-lng-fight-two-front-gas-war-0
6. Statistical Review of World Energy 2022. BP, 2022. URL: https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2022-full-report.pdf?ysclid=ln797a4qkg508696584
7. International Renewable Energy Agency IRENA. Renewable power generation costs in 2020. – eBook Partnership, 2022. URL: https://www.irena.org/publications/2021/Jun/Renewable-Power-Costs-in-2020
8. International Renewable Energy Agency IRENA. Renewable power generation costs in 2022. URL: https://www.irena.org/Publications/2023/Aug/Renewable-Power-Generation-Costs-in-2022
9. IEA. World Energy Investment 2023. URL: https://www.iea.org/reports/world-energy-investment-2023
10. Berezkin M.Yu., Degtyarev K.S., Sinyugin O.A. Structural and dynamic characteristics of the investment process in the global renewable energy in the post-crisis period //Plumbing, heating, air conditioning. 2017;1:82-85.
11. Climate Policy Initiative et al. Global Landscape of Renewable Energy Finance 2023. URL: https://www.irena.org/Publications/2023/Feb/Global-landscape-of-renewable-energy-finance-2023
12. BloombergNEF. Energy Transition Investment Trends 2023. URL: https://www.bloomberg.com/professional/blog/webinar/energy-transition-investment-trends-2023/
13. REN21. Renewables 2022 Global Status Report. URL: https://www.unep.org/resources/report/renewables-2022-global-status-report

DOI: 10.33917/es-3.189.2023.6-15

Key parameters of attacks directions on the Russian economy and forecasts of the expected results, which previously have inspired confidence in Western states that political regime would inevitability fall, which stimulated the US and EU sanctions activity, were developed by a number of authoritative Western expert structures. Western strategies for collapsing the Russian economy in 2022–2023 with the help of sanctions, formed on the basis of these forecasts, did not bring the desired result. At the same time, alternative forecasts of a group of Russian scientists from the CEMI RAS and their Chinese colleagues on stability of the economies of Russia and China in the event of a friendly policy in the context of trade wars with the US and the EU, made in 2019, were fully confirmed. At the core of these forecasts there are analytical tools based on agent modeling.

References:

1. Ageev A.I., Loginov E.L. Mirovoe soobshchestvo v usloviyakh sverkhkriticheskoi bifurkatsii Upravlenie slozhnymi organizatsionnymi i tekhnicheskimi sistemami v usloviyakh sverkhkriticheskikh situatsii: Materialy mezhdunarodnoi nauchno-prakticheskoi konferentsii [World Community in Conditions of Supercritical Bifurcation: Management of Complex Organizational and Technical Systems in Conditions of Supercritical Situations: Proceedings of the international scientific and practical conference]. Moscow, INES, 2022, pp. 9–12.

2. Ageev A.I., Loginov E.L. Novaya bol’shaya voina: khroniki khorosho zabytogo budushchego [New Large-Scale War: Chronicles of Well Forgotten Future]. Ekonomicheskie strategii, 2014, vol. 16, no 6–7(122–123), pp. 16–33.

3. Makarov V.L., Vu Ts., Vu Z., Khabriev B.R., Bakhtizin A.R. Mirovye torgovye voiny: stsenarnye raschety posledstvii [World Trade Wars: Scenario Calculations of Consequences]. Vestnik Rossiiskoi akademii nauk, 2020, vol. 90, no 2, pp. 169–179.

4. Makarov V.L., Vu Ts., Vu Z., Khabriev B.R., Bakhtizin A.R. Sovremennye instrumenty otsenki posledstvii mirovykh torgovykh voin [Modern Tools for Assessing the Effects of World Trade Wars]. Vestnik Rossiiskoi akademii nauk, 2019, vol. 89, no 7, pp. 745–754.

5. Tsigas M., McDaniel C., Schropp S., Mahlstein K. Potential economic effects of sanctions on Russia: An Allied trade embargo. Voxeu.org, 2022, available at: https://voxeu.org/article/potential-economic-effects-allied-trade-embargo-russia.

6. Mahlstein K., McDaniel C., Schropp S., Tsigas M. Estimating the economic effects of sanctions on Russia: An Allied trade embargo. The World Economy, 2022, no 45, pp. 3344–3383, available at: https://doi.org/10.1111/twec.13311.

7. Bryan R., Johnson G., Sytsma T., Priebe M. Does the U.S. Economy Benefit from U.S. Alliances and Forward Military Presence? Santa Monica, CA: RAND Corporation, 2022, available at: https://www.rand.org/pubs/research_reports/RRA739-5.

8. Bolhuis A. Marijn, Jiaqian Chen, Benjamin Kett. Fragmentation in Global Trade: Accounting for Commodities. IMF Working Paper. 2023. No. WP 23/73.

DOI: 10.33917/es-1.187.2023.16-25

Forecasting the ruble exchange dynamics appears objectively necessary for shaping both the medium-term financial strategy of industry corporations and the general strategic course for occupying leading positions in sectors of business interest, including through the use of new financial instruments, new markets and, in general, a system of strategic planning of socio-economic development of Russia. However, in today’s realities, according to most experts, with whom we cannot but agree, the task of forecasting seems extremely difficult and appears complicated by the fact that the launched crises are unpredictable and are characterized by a diverse nature (pandemic and geopolitical crises, expansion of trade wars and sanctions). In such conditions, when uncertainty grows excessively, it is important to turn to the accumulated experience: to analyze to what extent the available models can be suitable for prospective assessments in the current environment.

References:

16. Ageev A.I., Glaz’ev S.Yu., Mityaev D.A., Zolotareva O.A., Pereslegin S.B. Postroenie modeli prognoza kursa valyut na dolgosrochnom i kratkosrochnom gorizontakh [Building a Model for Forecasting the Exchange Rate on the Long-term and Short-term Horizons]. Ekonomicheskie strategii, 2022, no 6 (186), pp. 16–25, available at: DOI: https://doi.org/10.33917/es-6.186.2022.16-25.

17. Dubrova T.A. Analiz vremennykh dannykh [Time Data Analysis]. Analiz dannykh. Moscow, Yurait, 2019, pp. 397–459.

18. Boks Dzh, Dzhenkins G. Analiz vremennyh ryadov [Time Series Analysis]. Prognozirovanie i upravlenie. Moscow, Mir, 1974, 406 p.

19. Alzheev A.V., Kochkarov R.A. Sravnitel’nyi analiz prognoznykh modelei ARIMA i LSTM na primere aktsii rossiiskikh kompanii [Comparative Analysis of ARIMA and LSTM Forecasting Models on the Example of Russian Companies’ Stocks]. Finansy: teoriya i praktika, 2020, no 24(1), pp. 14–23,
DOI: 10.26794/2587-5671-2020-24-1-14-23.

20. Mhitaryan S.V., Danchenok L.A. Prognozirovanie prodazh s pomoshch’yu adaptivnyh statisticheskih metodov [Sales Forecasting with the Help of Adaptive Statistical Methods]. Fundamental’nye issledovaniya, 2014, no 9-4, pp. 818–822.

21. Pilyugina A.V., Bojko A.A. Ispol’zovanie modelej ARIMA dlya prognozirovaniya valyutnogo kursa [Using ARIMA Models for Exchange Rate Forecasting]. Prikaspijskij zhurnal: upravlenie i vysokie tekhnologii, 2015, no 4, pp. 249-267.

22. Ruppert D., Matteson D.S. Statistics and Data Analysis for Financial Engineering. Springer, 2015, available at: https://link.springer.com/book/10.1007%2F978-1-4939-2614-5.

23. Garcia F., Guijarro F., Moya I., Oliver J. Estimating returns and conditional volatility: A comparison between the ARMA-GARCH-M models and the backpropagation neural network. International Journal of Complex Systems in Science, 2012, no 1(2), pp. 21–26.

24. Maniatis P. Forecasting the Exchange Rate Between Euro And USD: Probabilistic Approach Versus ARIMA And Exponential Smoothing Techniques. Journal of Applied Business Research (JABR), 2012, no 28(2), pp. 171–192, available at: https://doi.org/10.19030/jabr.v28i2.6840.

DOI: https://doi.org/10.33917/es-6.186.2022.16-25

Forecasting the ruble exchange dynamics appears objectively necessary for shaping both the medium-term financial strategy of industry corporations and the general strategic course for occupying leading positions in sectors of business interest, including through the use of new financial instruments, new markets and, in general, a system of strategic planning of socio-economic development of Russia. However, in today’s realities, according to most experts, with whom we cannot but agree, the task of forecasting seems extremely difficult and appears complicated by the fact that the launched crises are unpredictable and are characterized by a diverse nature (pandemic and geopolitical crises, expansion of trade wars and sanctions). In such conditions, when uncertainty grows excessively, it is important to turn to the accumulated experience: to analyze to what extent the available models can be suitable for prospective assessments in the current environment.

References:

1. Kuranov G.O. Metodicheskie voprosy kratkosrochnoi otsenki i prognoza makroekonomicheskikh pokazatelei [Methodological Issues of Short-Term Assessment and Forecast of Macroeconomic Indicators]. Voprosy statistiki, 2018, no 25(2), pp. 3–24.

2. Frenkel’ A.A., Volkova N.N., Surkov A.A., Romanyuk E.I. Sravnitel’nyi analiz modifitsirovannykh metodov Greindzhera — Ramanatkhana i Beitsa — Greindzhera dlya postroeniya ob”edinennogo prognoza dinamiki ekonomicheskikh pokazatelei [Comparative Analysis of Modified Granger-Ramanathan and Bates-Granger Methods for Developing a Combined Forecast of Economic Indicators Dynamics]. Voprosy statistiki, 2019, no 26(8), pp. 14–27.

3. Shirov A.A. Makrostrukturnyi analiz i prognozirovanie v sovremennykh usloviyakh razvitiya ekonomiki [Macrostructural Analysis and Forecasting under Current Conditions of Economic Development]. Problemy prognozirovaniya, 2022, no 5, pp. 43–57.

4. Dmitrieva M.V., Suetin S.N. Modelirovanie dinamiki ravnovesnykh valyutnykh kursov [Simulating the Dynamics of Equilibrium Exchange Rates]. Vestnik KIGIT, 2012, no 12–2(30), pp. 061–064.

5. Linkevich E.F. Mirovaya valyutnaya sistema: poliinstrumental’nyi standart [World Monetary System: Polyinstrumental Standard]. Krasnodar, 2014, pp. 82–91.

6. Ageev A.I., Loginov E.L. Izmenenie strategii operirovaniya dollarom: zapusk SShA novogo kreditno-investitsionnogo tsikla vo vzaimosvyazi s valyutnymi voinami [Changing the Strategy of Dollar Handling: US Launch of New Credit-Investment Cycle in Association with the Currency Wars]. Ekonomicheskie strategii, 2015, no 3(129), pp. 20–35.

7. Fedorova E.A., Lazarev M.P. Vliyanie tseny na neft’ na finansovyi rynok Rossii v krizisnyi period [Impact of Oil Prices on the Financial Market of Russia During the Crisis]. Finansy i kredit, 2014, № 20(596), pp. 14–22.

8. Kuz’min A.Yu. Valyutnye kursy: v poiskakh strategicheskogo ravnovesiya [Exchange Rates: in Search of Strategic Equilibrium]. Ekonomicheskie strategii, 2018, no 1, pp. 82–91.