Program-Target Mechanisms to Ensure the Fiscal Balance of the Federal Constituent

Alan K. Karaev, Oksana S. Gorlova, Vadim V. Ponkratov, Margarita L. Vasyunina, Andrey I. Masterov, Marina L. Sedova


The purpose of this research is to study the possible impact of program costs associated with the development of the real sector of the regional economy on the fiscal balances of the constituent entities of the Russian Federation based on the wavelet analysis method. To achieve this purpose, we conducted a correlation analysis of the time-frequency dependence between the variables of the empirical model: the shares of program costs, the shares of non-repayable receipts, and the share of business taxes in the revenues of the consolidated budgets of constituent entities of the Russian Federation such as the Republic of Mordovia, the Udmurt Republic, Trans-Baikal Territory, and Kaliningrad Region for the period from 2001 to 2021. The research results indicate a significant impact exerted by the program costs of the regional budgets on the development of the real sector to ensure fiscal balance in the Republic of Mordovia, the Udmurt Republic, and the Trans-Baikal Territory on certain time scales. The novelty of this research lies in demonstrating the wavelet analysis effectiveness applied when conducting correlation analysis in cases where the relationships between the analyzed variables follow different patterns at different time horizons, and precisely wavelet analysis makes it possible to reveal the most significant characteristics of the relationship of variables. Earlier studies based on traditional methods ignored the time-frequency dependence between the variables of the empirical model. The practical significance of the research results lies in the fact that they determine the time scale on which the most effective measures and budgetary policy instruments applied within the framework of program-target mechanisms are provided to ensure fiscal balances in the regions.


Doi: 10.28991/ESJ-2023-07-05-05

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Federal Constituent Entity Budget; Fiscal Balance; Non-repayable Receipts; Business Taxes; Correlation Analysis; Discrete Wavelet Transform.


Bellofatto, A. A., & Besfamille, M. (2018). Regional state capacity and the optimal degree of fiscal decentralization. Journal of Public Economics, 159, 225–243. doi:10.1016/j.jpubeco.2017.12.010.

Akindinova, N., Chernyavsky, A., & Chepel, A. (2016). Analysis of regional fiscal balance. Voprosy Ekonomiki, 10, 31–48. doi:10.32609/0042-8736-2016-10-31-48.

Leogrande, A., Magaletti, N., Cosoli, G., & Massaro, A. (2022). The Role of Broadband Price Index in Fostering Economic Growth and Digitization in Europe. Journal of Human, Earth, and Future, 3(1), 32-54. doi:10.28991/HEF-2022-03-01-03.

Mikhaylova, A. A., Klimanov, V. V., & Safina, A. I. (2018). The impact of intergovernmental fiscal transfers on economic growth and the structure of the regional economy. Voprosy Ekonomiki, 1, 91–103. doi:10.32609/0042-8736-2018-1-91-103.

Mikhaylova, A., & Timushev, E. (2020). Russia’s budgetary system: How much sustainable? HSE Economic Journal, 24(4), 572–597. doi:10.17323/1813-8691-2020-24-4-572-597.

Tashtamirov, M. (2022). Efficiency of Inter-budgetary Regulation of Heavily Subsidized Budgets at the Subnational Level. Finance: Theory and Practice, 26(2), 136–159. doi:10.26794/2587-5671-2022-26-2-136-159.

Sheremeta, S. V. (2020). Russian regional finances analysis and regional debt sustainability. Voprosy Ekonomiki, 2, 30–58. doi:10.32609/0042-8736-2020-2-30-58.

Yushkov, A. O., Oding, N. Y., & Savulkin, L. I. (2018). Transfer-dependent regions of Russia: Scenarious for increasing the budget revenues. Voprosy Ekonomiki, 12, 46–65. doi:10.32609/0042-8736-2018-12-46-65.

Digdowiseiso, K. (2022). Is Fiscal Decentralization Growth Enhancing? A Cross-Country Study in Developing Countries over the Period 1990–2014. Economies, 10(3), 62. doi:10.3390/economies10030062.

Jin, Y., & Rider, M. (2020). Does fiscal decentralization promote economic growth? An empirical approach to the study of China and India. Journal of Public Budgeting, Accounting and Financial Management, 34(6), 146–167. doi:10.1108/JPBAFM-11-2019-0174.

Kim, J., & Dougherty, S. (2018). Fiscal Decentralisation and Inclusive Growth. OECD Fiscal Federalism Studies, Paris, France.

OECD. (2020). Subnational Governments in OECD Countries: Key Data. Organisation for Economic Co-operation and Development (OECD), Paris, France. Available online: (accessed on July 2023).

Onofrei, M., Oprea, F., Iaţu, C., Cojocariu, L., & Anton, S. G. (2022). Fiscal Decentralization, Good Governance and Regional Development—Empirical Evidence in the European Context. Sustainability (Switzerland), 14(12), 7093. doi:10.3390/su14127093.

Song, J., Geng, L., Fahad, S., & Liu, L. (2022). Fiscal decentralization and economic growth revisited: an empirical analysis of poverty governance. Environmental Science and Pollution Research, 29(19), 28020–28030. doi:10.1007/s11356-021-18470-7.

Pobyvaev, S. A., Eremin, V. V., Gaibov, T. S., & Zolotarev, E. V. (2022). Enhancing the Approach to Forecasting the Dynamics of Socio-Economic Development during the COVID-19 Pandemic. Emerging Science Journal, 6, 108-121. doi:10.28991/esj-2022-SPER-08.

Evgeniy Nikolaevich, T., & Anna Aleksandrovna, M. (2023). Vertical Fiscal Imbalance as a Tool for Analyzing the Debt Sustainability of Russian Regions. State and Municipal Management Scholar Notes, 1(1), 157–166. doi:10.22394/2079-1690-2023-1-1-157-166.

Harguindéguy, J. B. P., Cole, A., & Pasquier, R. (2021). The variety of decentralization indexes: A review of the literature. Regional and Federal Studies, 31(2), 185–208. doi:10.1080/13597566.2019.1566126.

Polterovich, V. M. (2020). Reform of the project activity state system, 2018-2019. Terra Economicus, 18(1), 6–27. doi:10.18522/2073-6606-2020-18-1-6-27.

Shmigol, N. S., & Kuznetsova, N. R. (2021). Trends in the development of fiscal federalism and intergovernmental relations for the socio-economic development of the regions. Financial Life, 2, 95-98.

Idrisova, V., & Freinkman, L. (2010). Impact of Federal Transfers over Regional Authorities Behavior. (137P), Gaidar Institute for Economic Policy Research Paper Series, Moscow, Russia.

Tatevosyan, G. M., Pisareva, O. M., Sedova, S. V., & Simonova, N. I. (2004). A comparative analysis of the economic indicators of the regions of Russia. Economics and Mathematical Methods, 40(4), 59-73.

Tatevosyan, G. M., Pisareva, O. M., & Sedova, S. V. (2009). Methods for Substantiating Investment Programs (The Real Sector of the Economy). CEMI RAN, Moscow, Russia.

Ermakov, V. V. (2017). Assessment of the impact of intergovernmental transfers on the socio-economic development of the region. Economy (Regional Problems), (3), 18-37.

Gagarina, G. Y., Dzyuba, E. I., Gubarev, R. V., & Fayzullin, F. S. (2017). Forecasting of Socio-Economic Development of the Russian Regions. Economy of Region, 4, 1080–1094. doi:10.17059/2017-4-9.

Gurara, D., Kpodar, K., Presbitero, A. F., & Tessema, D. (2021). On the capacity to absorb public investment: How much is too much?. World Development, 145, 105525. doi:10.1016/j.worlddev.2021.105525.

Kilic Celik, S., Kose, M. A., & Ohnsorge, F. (2023). Potential Growth Prospects: Risks, Rewards, and Policies. Policy Research Working Papers. doi:10.1596/1813-9450-10355.

Begovic, M., Kattel, R., Mazzucato, M. and Quaggiotto, G. (2021). COVID-19 and the Need for Dynamic State Capabilities: An International Comparison. UCL Institute for Innovation and Public Purpose and United Nations Development Programme, University College London, United Kingdom. Available online: /2021/apr/covid-19-and-need-dynamic-state-capabilities-international-comparison (accessed on April 2023).

Zabala-Iturriagagoitia, J. M. (2022). Fostering regional innovation, entrepreneurship and growth through public procurement. Small Business Economics, 58(2), 1205–1222. doi:10.1007/s11187-021-00466-9.

Solyannikova, S. P. (2021). Appropriate Budgetary Policy for a Changing Economy. The World of New Economy, 15(2), 6–15. doi:10.26794/2220-6469-2021-15-2-6-15.

Kutsuri, G. N. (2020). Heavily subsidized budgets: Mechanism for distributing of inter-budget transfers to regions of Russia. Bulletin of the A.A. Kadyrov Chechen State University, 39(3), 28-34.

Braginsky, O. B., Tatevosyan, G. M., Sedova, S. V., & Magomedov, R. S. (2017). State Programs of Sectoral and Territorial Development: Problems of Methodology and Management Practice. CEMI RAN, Moscow, Russia.

Grebennikov, V. G., & Magomedov, R. S. (2019). Budgetary Self-Sufficiency as a Problem of the Governmental Programming of Regional Development. Economics and the Mathematical Methods, 55(4), 68. doi:10.31857/s042473880006774-0.

Grebennikov, V., Kyan, B. Y., & Magomedov, R. (2020). Governmental programming of regional budgetary self-sufficiency. Montenegrin Journal of Economics, 16(2), 219-233. doi:10.14254/1800-5845/2020.16-2.17.

Gallegati, M. (2012). A wavelet-based approach to test for financial market contagion. Computational Statistics & Data Analysis, 56(11), 3491–3497. doi:10.1016/j.csda.2010.11.003.

Rua, A. (2017). A wavelet-based multivariate multiscale approach for forecasting. International Journal of Forecasting, 33(3), 581–590. doi:10.1016/j.ijforecast.2017.01.007.

Wang, G. Y. (2023). The effect of environment on housing prices: Evidence from the Google Street View. Journal of Forecasting, 42(2), 288–311. doi:10.1002/for.2907.

Baruník, J., & Vácha, L. (2013). Contagion among Central and Eastern European stock markets during the financial crisis. Finance a Uver - Czech Journal of Economics and Finance, 63(5), 443–453. doi:10.48550/arXiv.1309.0491.

Wang, G. Y. (2022). Churn Prediction for High-Value Players in Freemium Mobile Games: Using Random Under-Sampling. Statistika, 102(4), 443–453. doi:10.54694/STAT.2022.18.

Polanco Martínez, J. M., Abadie, L. M., & Fernández-Macho, J. (2018). A multi-resolution and multivariate analysis of the dynamic relationships between crude oil and petroleum-product prices. Applied Energy, 228(С), 1550–1560. doi:10.1016/j.apenergy.2018.07.021.

Roueff, F., & Von Sachs, R. (2011). Locally stationary long memory estimation. Stochastic Processes and Their Applications, 121(4), 813–844. doi:10.1016/

Gallegati, M., & Ramsey, J. B. (2014). The forward-looking information content of equity and bond markets for aggregate investments. Journal of Economics and Business, 75(C), 1–24. doi:10.1016/j.jeconbus.2014.04.002.

Sircar, R. (2002). An introduction to wavelets and other filtering methods in finance and economics. Waves in Random Media, 12(3), 399–399. doi:10.1088/0959-7174/12/3/701.

Ramsey, J. B., Gallegati, M., Gallegati, M., & Semmler, W. (2010). Instrumental variables and wavelet decompositions. Economic Modelling, 27(6), 1498–1513. doi:10.1016/j.econmod.2010.07.011.

Percival, D. P. (1995). On estimation of the wavelet variance. Biometrika, 82(3), 619–631. doi:10.1093/biomet/82.3.619.

Percival, D. B., & Walden, A. T. (2000). Wavelet Methods for Time Series Analysis. Cambridge University Press, Cambridge, United Kingdom. doi:10.1017/cbo9780511841040.

Whitcher, B. J. (1998). Assessing nonstationary time series using wavelets. Ph.D. Thesis, University of Washington, Seattle, United States.

Whitcher, B., Guttorp, P., & Percival, D. B. (2000). Wavelet analysis of covariance with application to atmospheric time series. Journal of Geophysical Research Atmospheres, 105(D11), 14941–14962. doi:10.1029/2000JD900110.

Treasury of Russia. Consolidated budgets of constituent entities of the Russian Federation and budgets of territorial state extra-budgetary funds. Federal Treasury, Moscow, Russia. Available online: (accessed on March 2023). (In Russian).

WOLFARM. (2023). DaubechiesWavelet: Wolfram Language & System Documentation Center, Champaign, United States. Available online: (accessed on July 2023).

Karlsson, H. K., Månsson, K., & Hacker, S. (2021). Revisiting the nexus of the financial development and economic development: new international evidence using a wavelet approach. Empirical Economics, 60(5), 2323–2350. doi:10.1007/s00181-020-01885-5.

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DOI: 10.28991/ESJ-2023-07-05-05


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