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.

DOI: 10.33917/mic-6.101.2021.69-77

The article notes that the development of the Northern Sea Route and the Russian Arctic area around it is a necessary condition for improving long-term competitiveness of the national economy. Negative economic trends are identified that have resulted from a decline in economic activity due to the coronavirus epidemic, which significantly affect the performance of ongoing investment projects in the field of mining in the Arctic zone. It is proposed to clarify and correct the existing forecasts for the transportation of goods along the Northern Sea Route, to ensure the most efficient use of the federal budget resources for the development of its infrastructure. Using the methods of comparative analysis and a systematic approach, the authors conclude that in the context of a decline in economic activity, the volume of cargo transportation by private companies along the Northern Sea Route by 2024 will be in the range of 47-50 million tons, and a number of planned projects in the field of production minerals will not be sold. Recommendations are given for adjusting the existing plans for the development of the infrastructure of the Northern Sea Route (including the construction of nuclear icebreakers) in order to more efficiently use the federal budget funds.

The article discusses the organization of information and network events aimed at protecting key points of political management of vital functions of the State on the basis of information and computing tools to operate the operating parameters of neural network monitoring and study the set of data on processes affecting personality. The need for the use of intelligent means of unclean logic and neural networks to support state systems of counterintelligence, surveillance and political governance with respect to subjects available for identification, digital description and analysis of their sociopathicity in relation to state institutions of political governance is justified. Neural network synthesis of digital matrices of key cognitive and psychosocial indicators of individuals and their groups is carried out to detect reactions to the package of political information of any subject using electronic communicative services. On this basis, measures are implemented to manage the metastable states of his personality and to configure cognitive and psychosocial mechanisms of interpretation of reality in conditions of dominance of unreported factors of an information nature (information stimuli).

The article provides an analysis of the possible stabilization of world GDP in the forecast period, including explanation by the systemic long-term falling of oil prices. Given that the world GDP is the value of all goods and services of final consumption, the GDP decline can be attributed to their cheapening. This price reduction can be caused by high rates of innovation and technological development of the world economy. The article presents argumentation that the decline in the world GDP has a longterm nature. Even recessionary development of the global economy is possible. But it is not disastrous. The world economy under the influence of innovation processes is reconstructed through information technology replenishment and through reducing production costs of goods and services for final consumption. The article shows at the model level that countries with a low GDP per capita may have even greater potential for transition to an information economy than countries with a high GDP per capita. This opens a window of opportunities for Russia to modernize the economy in accordance with the evolving trends of the global innovation process.