The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 1/2024.  Publications of young authors.

Yulia D. Sokolova

research engineer at the Laboratory of the Natural Resources Policy at the Graduate School of Economics and Management, assistant and postgraduate student at the Department of Economics at the Graduate School of Economics and Management, Ural Federal University named after the first President of Russia B. N. Yeltsin, Yekaterinburg, Russia

ORCID: 0000-0002-5991-3061

THE IMPACT OF ECONOMIC ACTIVITY ON THE ENVIRONMENT: EMPIRICAL EVIDENCE FROM BRICS COUNTRIES

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Abstract

The research is devoted to the nexus between economic development and environmental pollution in the BRICS countries. Within the framework of the study, the hypothesis of the Kuznets environmental curve was not verified, but Russia and China have the greatest potential to reach the income level where economic growth is able to "take care" of the environment. Applying the advanced econometric method of Driscoll–Krayy panel data analysis, we found that GDP per capita growth, industrialization and urbanization are the factors most responsible for environmental degradation in the BRICS countries, while the inflow of foreign direct investment, developed financial sector, active integration into the global space, environmental policy and the use of alternative energy sources contribute to environmental improvement. As for the policy implications, the BRICS countries should direct their efforts to create the most favourable conditions for FDI, deepen the financial sector, intensify environmental policy and develop the alternative energy sector.

Keywords: BRICS, economic growth, environment, environmental Kuznets curve, Driscoll–Krayy.

JEL: O44, Q56, R11

EDN: WMTHDC

DOI: https://doi.org/10.52180/2073-6487_2024_1_154_176

References

1. Balyhin M., Shajlieva M., Tsypin A. Statistical analysis of the economic development of the BRICS countries // Statistics and Economics. 2020. No. 2 (17). Pp. 18–28. (In Russ.) https://doi.org/10.21686/2500-3925-2020-2-18-28
2. Tian X., Sarkis J., Geng Y., Bleischwitz R., Qian Y., Xu L., Wu R. Examining the role of BRICS countries at the global economic and environmental resources nexus // Journal of Environmental Management. 2020. Vol. 262. No 110330. https://doi.org/10.1016/j.jenvman.2020.110330
3. Chakravarty D., Mandal S. Estimating the relationship between economic growth and environmental quality for the economies – a dynamic panel data approach // The Journal of Developing Areas. 2016. No. 5 (50) Pp. 119–130. https://www.jstor.org/stable/26415567
4. Panayotou T. Empirical tests and policy analysis of environmental degradation at different stages of economic development // Working Paper. 1993. No. WP238. https://doi.org/10.1007/978-1-349-24245-0_2
5. Grossman G., Krueger A. Environmental impact of a North American Free Trade Agreement // NBER Working paper. 1991. No. 3914. https://doi.org/10.3386/w3914
6. Caglar A., Zafar M., Bekun F., Mert M. Determinants of CO2 emissions in the BRICS economies: The role of partnerships investment in energy and economic complexity // Sustainable Energy Technologies and Assessments. 2022. Vol. 51. No. 101907. https://doi.org/10.1016/j.seta.2021.101907
7. Tamazian A., Chousa J., Vadlamannati K. Does higher economic and financial development lead to environmental degradation: Evidence from BRIC countries // Energy Policy. 2009. No. 1 (37). Pp. 246–253. https://doi.org/10.1016/j.enpol.2008.08.025
8. Naseem S., Mohsin M., Zia-UR-Rehman M., Baig S., Sarfraz M. The influence of energy consumption and economic growth on environmental degradation in BRICS countries: an application of the ARDL model and decoupling index // Environmental Science and Pollution Research. 2022. Vol. 29. Pp. 13042–13055. https://doi.org/10.1007/s11356-021-16533-3
9. Ganda F. The non-linear influence of trade, foreign direct investment, financial development, energy supply and human capital on carbon emissions in the BRICS // Environmental Science and Pollution Research. 2021. Vol. 28. Pp. 57825–57841. https://doi.org/10.1007/s11356-021-14704-w
10. Aydin M., Turan Y. The influence of financial openness, trade openness, and energy intensity on ecological footprint: revisiting the environmental Kuznets curve hypothesis for BRICS countries // Environmental Science and Pollution Research. 2020. Vol. 27. Pp. 43233–43245. https://doi.org/10.1007/s11356-020-10238-9
11. Rafique M., Li Y., Larik A., Monaheng M. The effects of FDI, technological innovation, and financial development on CO2 emissions: evidence from the BRICS countries. Environmental Science and Pollution Research. 2020. Vol. 27. Pp. 23899–23912. https://doi.org/10.1007/s11356-020-08715-2
12. Azevedo V., Sartori S., Campos L. CO2 emissions: A quantitative analysis among the BRICS nations // Renewable and Sustainable Energy Reviews. 2018. Vol. 81. Pp. 107–115. https://doi.org/10.1016/j.rser.2017.07.027
13. Hussain M., Dogan E. The role of institutional quality and environment-related technologies in environmental degradation for BRICS // Journal of Cleaner Production. 2021. Vol. 304. No. 127059. https://doi.org/10.1016/j.jclepro.2021.127059
14. Li X., Ozturk I., Majeed M., Hafeez M., Ullah S. Considering the asymmetric effect of financial deepening on environmental quality in BRICS economies: Policy options for the green economy // Journal of Cleaner Production. 2022. No. 10 (331). https://doi.org/10.1016/j.jclepro.2021.129909
15. Hasan M., Wieloch J., Ali M., Zikovic S., Uddin G. A new answer to the old question of the environmental Kuznets Curve (EKC). Does it work for BRICS countries? // Resources Policy. 2023. Vol. 87. No. 104332. https://doi.org/10.1016/j.resourpol.2023.104332
16. Zhou X., Tang X., Zhang R. Impact of green finance on economic development and environmental quality: a study based on provincial panel data from China // Environmental Science and Pollution Research. 2020. Vol. 27. Pp. 19915–19932. https://doi.org/10.1007/s11356-020-08383-2
17. Chishti M., Sinha A. Do the shocks in technological and financial innovation influence the environmental quality? Evidence from BRICS economies // Technology in Society. 2022. Vol. 68. No. 101828. https://doi.org/10.1016/j.techsoc.2021.101828
18. Zakarya G., Mostefa B., Abbes S., Seghir G. Factors affecting CO2 emissions in the BRICS countries: a panel data analysis // Procedia Economics and Finance. 2015. Vol. 26. Pp. 114–125. https://doi.org/10.1016/S2212-5671(15)00890-4
19. Mariev O., Davidson N..,Emelyanova O. The impact of urbanization on carbon dioxide emissions in Russian regions // Journal of Applied Economic Research. 2020. No. 3 (19). Pp. 286–309. (In Russ.) https://doi.org/10.15826/vestnik.2020.19.3.014
20. Rahman H. Zaman U., Górecki J. The role of energy consumption, economic growth and globalization in environmental degradation: empirical evidence from the BRICS region // Sustainability. 2021. No. 4 (13). Pp. 1924–1944. https://doi.org/10.3390/su13041924
21. Zameer H., Yasmeen H., Zafar M., Waheed A., Sinha A. Analyzing the association between innovation, economic growth, and environment: divulging the importance of FDI and trade openness in India // Environmental Science and Pollution Research. 2020. Vol. 27. Pp. 29539–29553. https://doi.org/10.1007/s11356-020-09112-5
22. Ojekemi O., Rjoub H., Awosusi A., Agyekum E. Toward a sustainable environment and economic growth in BRICS economies: do innovation and globalization matter? // Environmental Science and Pollution Research. 2022. Vol. 29. Pp. 57740–57757. https://doi.org/10.1007/s11356-022-19742-6
23. Mariev O., Davidson N., Borzova I. Modeling the impact of urbanization on air pollution in Russian regions // Journal of Economic Theory. 2021. No. 4 (18). Pp. 627–641. (In Russ.) https://doi.org/10.31063/2073-6517/2021.18-4.11
24. Pata U. Linking renewable energy, globalization, agriculture, CO2 emissions and ecological footprint in BRIC countries: A sustainability perspective // Renewable Energy, 2021. Vol. 173. Pp. 197–208. https://doi.org/10.1016/j.renene.2021.03.125
25. Mahalik M., Mallick H., Padhan H. Do educational levels influence the environmental quality? The role of renewable and non-renewable energy demand in selected BRICS countries with a new policy perspective // Renewable Energy. 2021. Vol. 164. Pp. 419–432. https://doi.org/10.1016/j.renene.2020.09.090
26. Ahmad M., Ahmed Z., Yang X., Hussain N., Sinha A. Financial development and environmental degradation: Do human capital and institutional quality make a difference? // Gondwana Research. 2022. Vol. 105. Pp. 299–310. https://doi.org/10.1016/j.gr.2021.09.012
27. Shahbaz M., Nuta A., Mishra P., Ayad H. The impact of informality and institutional quality on environmental footprint: The case of emerging economies in a comparative approach // Journal of Environmental Management. 2023. Vol. 348. No. 119325. https://doi.org/10.1016/j.jenvman.2023.119325
28. Maksimova A., Nikolaeva N., Saliy S., Semina I. Assessing the influence of economic and institutional factors on CO2 emissions // Scientific research of the Faculty of Economics. Electronic journal. 2020. No 4 (12). Pp. 51–69. (In Russ.)
29. Dario C., Iacoviello M. Measuring geopolitical risk // American Economic Review, 2022. No. 4 (112). Pp. 1194–1225. https: //doi.org/10.1257/aer.20191823
30. Pesaran M. General diagnostic tests for cross-section dependence in panels // Journal of Econometrics. 2004. No. 7 (69). https://doi.org/10.2139/ssrn.572504
31. Pesaran M. A simple panel unit root test in the presence of cross-section dependence // Journal of Applied Econometrics. 2007. Vol. 22. Pp. 256–312. https://doi.org/10.2139/ssrn.457280
32. Driscoll J., Kraay A. Consistent covariance matrix estimation with spatially dependent panel data // The Review of Economics and Statistics. 1998. No. 4 (80). Pp. 549–560. https://doi.org/10.1162/003465398557825
33. Mozias P., Shcherbakova A. Prospects for the transition of the BRICS countries to a model of sustainable development (on the example of Brazil and China) // Russia and the world in the 21st century. 2023. Vol. 4. (In Russ.) https://doi.org/10.31249/rsm/2023.04.04.
34. KurbatskiyА.,Shakleina E. Economic growth and environmental pollution in the USA and Russia: Comparative spatial-econometric analysis. Economic and Social Changes: Facts, Trends, Forecast. 2022. No. 2 (15). Pp. 92–107. (In Russ.) https://doi.org/10.15838/esc.2022.2.80.6. (In Russ.)
35. Grigoriev L., Makarov I., Sokolova A., Pavlyushina V., Stepanov I. Climate change and inequality: potential for joint problem solving // Bulletin of International Organizations. 2020. No. 1 (15). Pp. 7–30. (In Russ.) https://doi.org/10.17323/1996-7845-2020-01-01.
36. Sukharev O. Economic growth and decarbonization policy // Problems of market economy. 2022. No. 1. Pp. 43–57. (In Russ.). https://doi.org/10.33051/2500-2325-2022-1-43-57.
37. Sohag K., Davidson N., Mariev O. Revising environmental Kuznets curve in Russian regions: role of environmental policy stringency. Environmental Science and Pollution Research. 2021. No. 38 (28). https://doi.org/10.1007/s11356-021-14515-z
38. Tcvetkov P., Andreichyk, A., Kosarev O. The impact of economic development of primary and secondary industries on national CO2 emissions: The case of Russian regions // Journal of Environmental Management. 2024. Vol. 351. No. 119881. https://doi.org/110.1016/j.jenvman.2023.119881
39. Chen L., Gozgor G., Mahalik M., Pal S., Rather K. How does geopolitical risk affect CO2 emissions? The role of natural resource rents // Resources Policy. 2023. Vol. 87. No. 104321. https://doi.org/10.1016/j.resourpol.2023.104321

Manuscript submission date: 22.01.2024

For citation:

Sokolova Y.D. The impact of economic activity on the environment: empirical evidence from BRICS countries // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2024. № 1. Pp. 154-176. (In Russ.). https://doi.org/10.52180/2073-6487_2024_1_154_176 EDN: WMTHDC

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The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 5/2023.  Publications of young authors.

Anastasia M. Matevosova

student of the Faculty of Economics of Moscow State University named after M.V. Lomonosov, senior laboratory assistant at the Institute of Economics of the Russian Academy of Sciences, Moscow, Russia

RUSSIANS’ INFLATION EXPECTATIONS UNDER SANCTIONS: BIG DATA RESEARCH

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Abstract

In 2022, Russian economy faced unprecedented sanctions pressure from the Western countries. Against this background, the government and the Central Bank need to constantly monitor the economic situation in the Russian Federation in order to take timely and effective measures. A high-frequency indicator of inflation expectations based on big data can help in solving this problem. The author identifies significant shortcomings of the existing approaches to the assessment of inflation expectations that make the possibility of their application under sanctions questionable. Based on the developed high-frequency indicators of inflation expectations, sanctions concern and the frequency of sanctions mentioning in the context of inflation expectations, she analyzes the impact of sanctions on the inflation expectations of the Russian population. The method of assessing inflation expectations based on big data has proved effective under sanctions and demonstrated the impact of sanctions on forming inflation expectations of the Russian population.

Keywords: sanctions, inflation expectations, high-frequency indicator, inflation.

JEL: F51, E31, D84, C55, C82

EDN: ZBJKRC

DOI: https://doi.org/10.52180/2073-6487_2023_5_181_200

References

1. Goloshchapova I.O. Development of a methodology for constructing high-frequency indicators of economic expectations of the population based on big data (on the example of inflation expectations) // Autoref. diss…. candidate of Economic Sciences. M., 2018. (In Russ.)
2. Goloshchapova I., Andreev M. Measuring inflation expectations of the Russian population with the help of machine learning // Voprosy Ekonomiki. 2017. № 6. Р. 71–93. (In Russ.).
3. Zhemkov M., Kuznetsova O. Measuring inflation expectations in Russia using stock market data // Voprosy Ekonomiki. 2017. № 10. Р. 111–122. (In Russ.)
4. Evstigneeva A., Karpov D. The Impact of Negative News on Public Perception of Inflation // Bank of Russia Working Paper Series. 2023. No. 111. (In Russ.)
5. Angelico C., Marucci J., Miccoli M., Quarta F. Can we measure inflation expectations using Twitter? // Journal of Econometrics.2022. Vol. 228. Iss. 2. Рp. 259–277.
6. Aromí J.D., Llada M. Forecasting inflation with twitter // Asociación Argentina de Economía Política. 2020. № 43080.
7. Askitas, N., Zimmerman, K. Google econometrics and unemployment forecasting // Applied Economics Quarterly.2009. Vol. 55. Iss. 2. Рp. 107–120.
8. Bauer M.D. Inflation Expectations and the News // International Journal of Central Banking. 2015.Vol. 11. Iss. 2. Рp.1–40.
9. Berk J.M. Measuring inflation expectations: a survey data approach //Applied Economics. 1999. Vol. 31. Iss. 11 Рp. 1467–1 480.
10. Bernanke B. What policymakers can learn from asset prices // Speech before the Investment Analyst Society of Chicago.2004. April 15.
11. Caroll C.D. Macroeconomic Expectations of Households and Professional Forecasters // Quarterly Journal of Economics. 2003. Vol. 118. Iss. 1. Рр. 269–298.
12. Choi, H., Varian, H. Predicting the present with Google Trends // Technical Report, Google Inc, 2009.
13. D’Amuri F. Predicting unemployment in short samples with internet job search query data // MPRA Paper 18403, 2009.
14. Guzman G. Internet Search Behavior as an Economic Forecasting Tool: The Case of Inflation Expectations // The Journal of Economic and Social Measurement. 2011. Vol. 36. No. 3.
15. Larsen V.H., Thorsrud L. A., Zhulanova J. News-driven Inflation Expectations and Information Rigidities // Journal of Monetary Economics. 2020. Vol. 117. Рp. 507–520.

Manuscript submission date: 30.06.2023

For citation:

Matevosova A.M. Russians’ Inflation Expectations Under Sanctions: Big Data Research // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2023. № 5. Pp. 181-200. (In Russ.). https://doi.org/10.52180/2073-6487_2023_5_181_200 EDN: ZBJKRC

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The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 6/2023.  Publications of young authors.

Alexey A. Matyukhin

postgraduate student at the Institute of Economics, Management and Finance, Russian New University; state customs inspector at the Customs Value Control Department of the Central Excise Customs, Moscow, Russia

ORCID: 0000-0002-1986-3864

LOGISTICS OF PARALLEL IMPORT UNDER ECONOMIC SANCTIONS

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Abstract

The article is devoted to analyzing the logistics of parallel imports, which has become one of the most relevant and popular ways of Russia's foreign trade activity in the current geopolitical situation, after the introduction of economic sanctions by Western countries in the spring of 2022. In the article, the author considers 4 types of schemes that allow participants in foreign economic activity to reduce logistics costs, and also analyzes the trade turnover and relations of the Russian Federation with the countries through which parallel imports are carried out, such as Turkey, China and India, as well as possible prospects for cooperation with them in the future. The author analyzes the mechanism of parallel imports in the automotive sector, thanks to which little-known Chinese brands began to appear on the Russian market. An actual logistics route in the scheme of parallel imports between Russia and India is the International North-South Transport Corridor (INSTC), which will reduce not only costs, but also the delivery time of goods. In conclusion, the author offers recommendations that can help not only strengthen the country's economy, but also develop relations with friendly states.

Keywords: parallel import, economic sanctions, logistics of parallel import, regional economy, trade turnover.

JEL: F19

EDN: ZJFNLO

DOI: https://doi.org/10.52180/2073-6487_2023_6_172_185

References

1. Matyuhin A.A., Rustamova I.T. Advantages and disadvantages of parallel imports in the context of economic sanctions // Economics in theory and in practice Economics in theory and in practice: current issues and modern aspects: Collection of articles of the XV International Scientific and Practical Conference. 2023. Рp. 74–78. EDN: RJSFVG. (In Russ.).
2. Matyuhin A.A., Ostashevskiy V.D. Economic sanctions as a new reality of modern Russia: the emergence, impact and methods of combating them // Science, innovation, education: current issues and modern aspects: monograph. 2023. Рp. 7–17. EDN: MHORNN. (In Russ.).
3. Reznik E.A. Certification and declaration of parallel imports in modern conditions // Economic development of Russia. 2023. Vol. 30. № 2. Рp. 16–22. EDN: FYYJQW. (In Russ.).
4. Golubchik A. M., Pak E. V. Parallel imports to Russia: certain aspects of logistics // Russian Foreign Economic Bulletin. 2022. № 10. Рp. 27–37. DOI: 10.24412/2072-8042-2022-10-27-37. EDN: CZHQIV. (In Russ.).
5. Markina A.S., Frolov V.D. Trade and economic relations between Russia and Turkey // Economy and Business: Theory and Practice. 2023. Vol. 1–2 (95). Рp. 9–11. DOI: 10.24412/2411-0450-2023-1-2-9-11. EDN: UQVMQL. (In Russ.).
6. Lukonin S.A., Vakhrushin I.V. Russian–Chinese trade and economic cooperation amid anti-Russian sanctions // Russia and the Asia-Pacific region. 2023. № 1. Рp. 160–180. DOI: 10.24412/1026-8804-2023-1-160-180. EDN: FXLZTC. (In Russ.).
7. Klunko N.S., Egorova L.V. Russia’s Industrial Transformation against the background of a special military operation: sanctions and Parallel imports // Interactive Science. 2023. № 3 (79). Рp. 72–77. EDN: FQEUYT. (In Russ.).
8. Semedov S.A., Shilova A.V. The ITC project «North – South»: problems and development under the sanctions // Scientific and analytical journal – Observer. 2023. № 2 (397). Рp. 52–61. DOI: 10.48137/2074-2975_2023_2_52. EDN: ECEQLR. (In Russ.).
9. Khaidarova Jamila Kh. The role of the «North-South» International Transport Corridor in India’s foreign policy // Oriental Journal of History, Politics and Law. 2022. Рp. 331–339. DOI: 10.37547/supsci-ojhpl-02-02-43. (In Russ.).

Manuscript submission date: 25.10.2023

For citation:

Matyukhin A.A. Logistics of parallel import under economic sanctions // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2023. № 6. Pp. 172-185. (In Russ.). https://doi.org/10.52180/2073-6487_2023_6_172_185 EDN: ZJFNLO

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The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 4/2023.  Publications of young authors.

Denis A. Sudarev

Post-Graduate Student of the Economics Faculty of the M.V. Lomonosov Moscow State University,

Senior Lecturer of the Economics Faculty of the Institute of Economics, Mathematics and Information Technology of the Russian Presidential Academy of National Economy and Public Administration under the President of the Russian Federation, Moscow, Russia

ORCID: 0000-0002-7812-7461

ASSESSMENT OF THE IMPACT OF POLITICAL FACTORS ON FEDERAL BUDGET REVENUE FORECAST ACCURACY IN RUSSIA

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Abstract

The purpose of the study is assessment of impact of political factors, such as electoral cycles and ideological range of parliament on systematic deviations of actual revenues of the Russian federal budget from its planned values. The study consists of two stages. On the first stage the quality of federal budget revenue forecast on the period from 2000 to 2022 is made (actual value of revenue is compared with planned one in the first version of the budget law). It is shown that official federal revenue forecasts are characterized with statistically significant under-prediction. The second stage is the empirical assessment of potential factors impact on pessimism in revenue forecasting. The following results of the conducted evaluation are proposed: federal electoral cycles are not statistically significant and ideological structure of the parliament is weakly significant factors of revenue forecasts quality. The result of the study gives the motivation for further investigation of key actors’ incentives during budget forecasting.

Keywords: budget process, fiscal forecasting, budget revenue, forecast accuracy, electoral cycles, partisan fragmentation, ideology.

JEL: H68, P16

EDN: ZOCLTM

DOI: https://doi.org/10.52180/2073-6487_2023_4_197_216

References

1. Balaev A.I. Factoral analysis of budget system revenues in Russia // Economic policy. 2017.Vol. 12. No. 3. Pp. 8–37.
2. Vilkov A.A. The «left» segment of the partisan system in modern Russia: problems and perspectives // Bulletin of Saratov University. The New Series. Sociology and Political science. 2019. Vol. 19. Iss. 2. Pp. 196–202.
3. Gurvich E.T. How accurate budget and macroeconomic forecasts are? // Economic Issues. 2006. No.9. Pp. 4–20.
4. Annett A. Enforcement and the Stability and Growth Pact: how fiscal policy did and did not change under Europe’s fiscal framework // Working Paper. 2006. IMF. No. 06/116.
5. Alesina A., Perotti R. The Political Economy of Budget Deficits // IMF Staff Papers. 1995. 42. No. 1. Pp. 1–31.
6. Artis M., Marcellino M. Fiscal forecasting: The track record of the IMF, OECD and EC // The Econometrics Journal. 2001. Vol. 4. No.1. Pp. S20–S36.
7. Auerbach A. On the Performance and Use of Government Revenue Forecasts // National Tax Journal. 1999. Vol. 52. No. 4. Pp. 767–782.
8. Bruck T., Stephan A. Do eurozone countries cheat with their budget deficit forecasts? // Kyklos. 2006. Vol. 59. Iss. 1. Pp. 3–15.
9. Croushore D., van Norden S. Fiscal Policy: Ex Ante and Ex Post // Research Department, Federal Reserve Bank of Philadelphia. Working Paper. 2014. No. 14–22.
10. Herwartz H., Theilen B. Ideology and redistribution through public spending // European Journal of Political Economy. 2017. Vol. 46. Pp. 74–90.
11. Jochimsen B, Lehmann R. On the political economy of national tax revenue forecasts: evidence from OECD countries // Public Choice. 2017. Vol. 170. Pp. 211–230.
12. Jonung L., Larch M. Improving fiscal policy in the EU: the case for independent forecasts. Economic Policy. 2006.Vol. 21. No. 47. Pp. 491–534.
13. Oller L., Barot B. The accuracy of European growth and inflation forecasts // International Journal of Forecasting. 2000. Vol. 16. Pp. 293–315.
14. Perotti R., Kontopoulos Y. Fragmented fiscal policy // Journal of Public Economics. 2002. 86. Pp. 191–222.
15. Pina A.M., Venes N.M. The political economy of EDP fiscal forecasts: an empirical assessment // European Journal of Political Economy. 2011. Vol. 27. Pp. 534–546.
16. Strauch R., Hallerberg M., von Hagen J. Budgetary forecasts in Europe – the track record of stability and convergence programmes // European Central Bank. Working Paper 2004. No. 307.
17. von Hagen J. Sticking to fiscal plans: the role of institutions // Public Choice, 2010. Vol. 144. Pp. 487–503.

Manuscript submission date: 18.06.2023

For citation:

Sudarev D.A. Assessment of the impact of political factors on federal budget revenue forecast accuracy in Russia // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2023. № 4. Pp. 197-216. (In Russ.). https://doi.org/10.52180/2073-6487_2023_4_197_216 EDN: ZOCLTM

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