Improvement of the Budget Forecasting System in the Kyrgyz Republic
Abstract
The purpose of this study is to develop and propose measures to improve the budget forecasting system in Central Asia to enhance the accuracy, reliability, and adaptability of budget forecasts. The study involved a comprehensive analysis of data covering various aspects of budget forecasting in Central Asian countries. This analysis included the collection of extensive data, including statistical indicators, on budget forecasts, and factors influencing economic stability in the region. The research results underscored the importance of budget forecasting as a tool for strategic financial planning based on systemic analysis and the use of advanced technologies. The concept of budget forecasting was highlighted as a systematic analysis aimed at predicting the financial performance of an organization over a specific period, including assessing expected income and expenses considering various factors influencing the financial situation. The study also examined the key functions of budget forecasting, including financial resource planning, optimization, and financial stability control. Special attention was paid to analysing the impact of external factors, such as economic uncertainty, using statistical methods and scenario analysis. The study also emphasized the importance of modern technologies, including machine learning and big data analysis, in improving budget forecasting processes. Overall, the research findings present important insights for practical application and further research in the field of financial management and budget planning. The findings have the potential to be used in shaping policies and reforms aimed at sustainable development and efficient utilization of public finances in the region.
References
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[30] Krammer, Sorin, and Alfredo Jiménez. (2020). Do political connections matter for firm innovation? Evidence from emerging markets in Central Asia and Eastern Europe. Technological Forecasting and Social Change, 151: 119669.
[31] Kunnathuvalappil, Hariharan. (2020). Rethinking budgeting process in times of uncertainty. International Journal of Emerging Technologies and Innovative Research, 7(5): 1178-1185.
[32] Kusonkhum, Wuttipong, Korb Srinavin, Narong Leungbootnak, Preenithi Aksorn, and Tanayut Chaitongrat. (2022). Government construction project budget prediction using machine learning. Journal of Advances in Information Technology, 13(1): 29-35.
[33] Levytska, Svitlana, Nataliia Ostapiuk, Olena Tsiatkovska, Maryna Resler, and Olena Mykhalska. (2024). State institution non-financial asset audit strategy development. Economics of Development, 23(2): 57-68.
[34] Lusardi, Annamaria. (2019). Financial literacy and the need for financial education: Evidence and implications. Swiss Journal of Economics and Statistics, 155: 1.
[35] Mullner, Ross. (2019). Futuring: A brief overview of methods and tools. In: Healthcare Analytics. New York: Routledge.
[36] Omurgazieva, Nazira, Baktygul Tilekeeva, Aida Bekkozhaeva, Nurlan Chanachev, and Tilek Cholponkulov. (2024). Impact of tax policy on the development of agrarian enterprises and organisations. Ekonomika APK, 31(3): 34-44.
[37] Ordu, Muhammed, Demir Eren, Chris Tofallis, and Murat Gunal. (2021). A novel healthcare resource allocation decision support tool: A forecasting-simulation-optimisation approach. Journal of the Operational Research Society, 72(3): 485-500.
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[39] Ponomarenko, Volodymyr, and Oksana Pysarchuk. (2024). Analysis of the impact of the volumes of state commissioning on the economy’s availability of specialists in certain professions. Economics of Development, 23(3): 69-81.
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[43] Rhanoui, Maryem, Siham Yousfi, Mounia Mikram, and Hajar Merizak. (2019). Forecasting financial budget time series: ARIMA random walk vs LSTM neural network. International Journal of Artificial Intelligence, 8(4): 317-327.
[44] Sakkaraeva, Dzhamilia, and Murat Kumashev. (2024). Analysis of the agro-industrial sector of the Kyrgyz Republic. Ekonomika APK, 31(2): 41-50.
[45] Sualihu, Amidu Mohammed, Tov Assogbavi, and Alex Donto. (2023). Financial planning and forecasting in the oil and gas industry. In: The Economics of the Oil and Gas Industry. London: Routledge.
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[47] Trusova, Natalia V., et al. (2019). Determinants of the development venture financing of the subjects of Agrarian market of Ukraine. Asia Life Sciences, 1: 377-398.
[48] Trusova, Natalia V., Sergey V. Kalchenko, Volodymyr D. Tsap, Volodymyr A. Ternovsky, and Olga P. Levchenko. (2017). Restrictions of financing the budget deficit of Ukraine. International Journal of Economic Research, 14(14): 353-364.
[49] Trusova, Natalia V., Serhii V. Karman, Maksym A. Tereshchenko, and Yurii O. Prus. (2018). Debt burden of the financial system of Ukraine and countries of the Eurozone: Policy of regulating of the risks. Espacios, 39(39): 30.
[50] Valle-Cruz, David, Vanessa Fernandez-Cortez, and J. Ramon Gil-Garcia. (2022). From E-budgeting to smart budgeting: Exploring the potential of artificial intelligence in government decision-making for resource allocation. Government Information Quarterly, 39(2): 101644.
[51] Wouters, Marc, and Frank Stadtherr. (2024). How management accountants purposefully create cash flow forecasts in capital budgeting: A field study of product development decisions. Accounting Perspectives, 23(3): 327-524.
[52] Yudina, Svitlana, Olena Lysa, Nataliia Diatlova, Andrii Drahun, and Olha Sarancha. (2022). Interaction of Enterprises with Financial Corporations: State, Problems, Mechanisms, Improvement of Relationships. Review of Economics and Finance, 20(1): 277-282.
[53] Forecast of socio-economic development of the Kyrgyz Republic. (2023). Available at: https://mineconom.gov.kg/ru/direct/3/28
[54] State budgets and loans. (2024). Available at: https://www.stat.kg/ru/opendata/category/3/
[2] Al-Thaqeb, Saud Asaad, Algharabali Barrak Ghanim, and Khaled Tareq Alabdulghafour. (2022). The pandemic and economic policy uncertainty. International Journal of Finance and Economics, 27(3): 2784-2794.
[3] Antolín-Díaz, Juan, Petrella Ivan, and Juan F. Rubio-Ramírez. (2021). Structural scenario analysis with SVARs. Journal of Monetary Economics, 117: 798-815.
[4] Arvan, Meysam, Behnam Fahimnia, Mohsen Reisi, and Enno Siemsen. (2019). Integrating human judgement into quantitative forecasting methods: A review. Omega, 86: 237-252.
[5] Bergmann, Mareike, Christian Brück, Thorsten Knauer, and Anja Schwering. (2020). Digitization of the budgeting process: Determinants of the use of business analytics and its effect on satisfaction with the budgeting process. Journal of Management Control, 31: 25-54.
[6] Cepni, Oguzhan, I. Ethem Guney, and Norman Swanson. (2020). Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors. Journal of Forecasting, 39(1): 18-36.
[7] Chornyi, Roman S. (2013). Labor potential of urban settlements: Features of forming and development. Economic Annals-XXI, 1-2(1): 41-44.
[8] Dagoumas, Athanasios, and Nikolaos Koltsaklis. (2019). Review of models for integrating renewable energy in the generation expansion planning. Applied Energy, 242: 1573-1587.
[9] Derkenbaeva, Saltanat, Chinara Adiyaeva, Nurila Ibraeva, Tinatin Sydykova, and Gulnara Oganova. (2024). Kyrgyz Republic production-resource and export potential state regulation mechanism. Scientific Horizons, 27(9): 162-176.
[10] Gkillas, Konstantinos, Jeevananthan Manickavasagam, and Sigh Visalakshmi. (2022). Effects of fundamentals, geopolitical risk and expectations factors on crude oil prices. Resources Policy, 78: 102887.
[11] Hawkins, Loraine, Elina Dale, Nurida Baizakova, and Aigul Sydykova. (2020). Budget structure reforms and their impact on health financing systems: Lessons from Kyrgyzstan. Geneva: World Health Organisation.
[12] Hysi, Arben, Jonida Avdulaj, Ermir Shahini, Irini Goga, and Elti Shahini. (2024). Role of legal regulation in the establishment and development of the public administration system with local self-government aspects. Social and Legal Studios, 7(1): 27-36.
[13] Ismayil-Zada, Matanat. (2022). The new economic theory is the main branch of the new physics. Astra Salvensis, 2022(1): 13-36.
[14] Ismayil-Zada, Matanat. (2023). Analysis of physical economic theory implementation efficiency in the economic activity of Azerbaijan. Scientific Horizons, 26(2): 112-123.
[15] Izvorski, Ivailo, Appolenia Mbowe, Bakyt Dubashov, Katharina Gassner, Michael Ferrantino, Roumeen Islam, and Tarik Sahovic. (2020). Kyrgyz Republic country economic memorandum. Washington: World Bank.
[16] Jackson, James, and Martin Weiss. (2020). Global economic effects of Covid-19: In brief. Available at: https://www.everycrsreport.com/files/20200313_R46270_14d1cbe22a876a66147960da61e6f6bc39548dc6.pdf
[17] Kaparbekov, Aibar, Olha Kambur, Svitlana Rakytska, and Olha Yevdokimova. (2024). Public finance management reform in the Kyrgyz Republic and Ukraine: Ways to increase transparency and efficiency in the use of budget funds. Scientific Bulletin of Mukachevo State University. Series “Economics”, 11(3): 73-85.
[18] Karimli, Irshad, Reyhan Azizova, Ramal Karimov, Ilkin Bayramov, and Abdulla Jasim Al Shamsi. (2024). The Reality and Prospects of Economic Development of the South Caucasus Region: New Approaches to the Influence of Internal and External Economic Factors. WSEAS Transactions on Computer Research, 12.
[19] Karvetski, Christopher, Carolyn Meinel, Daniel Maxwell, Yunzi Lu, Barbara Mellers, and Philip Tetlock. (2022). What do forecasting rationales reveal about thinking patterns of top geopolitical forecasters? International Journal of Forecasting, 38(2): 688-704.
[20] Karymshakov, Kamalbek, and Burulcha Sulaimanova. (2019). Measuring the impact and financing of infrastructure in the Kyrgyz Republic. ADBI Working Paper Series 988. Available at: https://hdl.handle.net/10419/222755
[21] Ke, Ruihao, Meng Li, Zhejia Ling, and Yuan Zhang. (2019). Social connections within executive teams and management forecasts. Management Science, 65(1): 439-457.
[22] Kerimkhulle, Seyit, Nataliia Obrosova, Alexander Shananin, and Akylbek Tokhmetov. (2023). Young Duality for Variational Inequalities and Nonparametric Method of Demand Analysis in Input–Output Models with Inputs Substitution: Application for Kazakhstan Economy. Mathematics, 11(19): 4216.
[23] Kerimkhulle, Seyit, et al. (2022). The Use Leontief Input-Output Model to Estimate the Resource and Value Added. In: SIST 2022 - 2022 International Conference on Smart Information Systems and Technologies, Proceedings. Astana: Institute of Electrical and Electronics Engineers.
[24] Kerimkulov, Seit, Saida Teleuova, and Gulzhan Tazhbenova. (2015). Measuring chaotic and cyclic fluctuations of cass freight index: Expenditures. Actual Problems of Economics, 171(9): 434-445.
[25] Ketners, Karlis, and Mara Petersone. (2021). The personalized model for the sustainable development of human resources in customs. Intellectual Economics, 15(1): 5-14.
[26] Ketners, Karlis. (2024). Developing potential budget reform for Latvia: Shifting from conventional to contemporary budgeting. Social and Legal Studios, 7(2): 55-63.
[27] Khan, Aman. (2019). Elements of budget forecasting. In: Fundamentals of Public Budgeting and Finance, pp. 229-271. Cham: Palgrave Macmillan.
[28] Komilova, Nilufar Kh., et al. (2019). Economic and geographic problems of improvement of industrial sectors and local structure of Uzbekistan. Journal of Advanced Research in Law and Economics, 10(6): 1916-1928.
[29] Kou, Gang, Xiangrui Chao, Peng Yi, Fawaz E Alsaadi, and Enrique Herrera-Viedma. (2019). Machine learning methods for systemic risk analysis in financial sectors. Technological and Economic Development of Economy, 25(5): 716-742.
[30] Krammer, Sorin, and Alfredo Jiménez. (2020). Do political connections matter for firm innovation? Evidence from emerging markets in Central Asia and Eastern Europe. Technological Forecasting and Social Change, 151: 119669.
[31] Kunnathuvalappil, Hariharan. (2020). Rethinking budgeting process in times of uncertainty. International Journal of Emerging Technologies and Innovative Research, 7(5): 1178-1185.
[32] Kusonkhum, Wuttipong, Korb Srinavin, Narong Leungbootnak, Preenithi Aksorn, and Tanayut Chaitongrat. (2022). Government construction project budget prediction using machine learning. Journal of Advances in Information Technology, 13(1): 29-35.
[33] Levytska, Svitlana, Nataliia Ostapiuk, Olena Tsiatkovska, Maryna Resler, and Olena Mykhalska. (2024). State institution non-financial asset audit strategy development. Economics of Development, 23(2): 57-68.
[34] Lusardi, Annamaria. (2019). Financial literacy and the need for financial education: Evidence and implications. Swiss Journal of Economics and Statistics, 155: 1.
[35] Mullner, Ross. (2019). Futuring: A brief overview of methods and tools. In: Healthcare Analytics. New York: Routledge.
[36] Omurgazieva, Nazira, Baktygul Tilekeeva, Aida Bekkozhaeva, Nurlan Chanachev, and Tilek Cholponkulov. (2024). Impact of tax policy on the development of agrarian enterprises and organisations. Ekonomika APK, 31(3): 34-44.
[37] Ordu, Muhammed, Demir Eren, Chris Tofallis, and Murat Gunal. (2021). A novel healthcare resource allocation decision support tool: A forecasting-simulation-optimisation approach. Journal of the Operational Research Society, 72(3): 485-500.
[38] Ozili, Peterson, and Thankom Arun. (2020). Spillover of COVID-19: Impact on the global economy. DOI:10.2139/ssrn.3562570
[39] Ponomarenko, Volodymyr, and Oksana Pysarchuk. (2024). Analysis of the impact of the volumes of state commissioning on the economy’s availability of specialists in certain professions. Economics of Development, 23(3): 69-81.
[40] Qawaqzeh, Mohamed Zaidan, Andrzej Szafraniec, Serhii Halko, Oleksandr Miroshnyk, and Anton Zharkov. (2020). Modelling of a household electricity supply system based on a wind power plant. Przeglad Elektrotechniczny, 96(11): 36-40.
[41] Rexha, Bahri, Fadil Osmani, and Artan Nimani. (2024). Importance of proper management of public finances in economic development. Scientific Bulletin of Mukachevo State University. Series “Economics”, 11(2): 65-78.
[42] Rezaei, Maede, S. Kamal Chaharsooghi, A. Husseinzadeh Kashan, and Reza Babazadeh. (2020). A new approach based on scenario planning and prediction methods for the estimation of gasoil consumption. International Journal of Environmental Science and Technology, 17: 3241-3250.
[43] Rhanoui, Maryem, Siham Yousfi, Mounia Mikram, and Hajar Merizak. (2019). Forecasting financial budget time series: ARIMA random walk vs LSTM neural network. International Journal of Artificial Intelligence, 8(4): 317-327.
[44] Sakkaraeva, Dzhamilia, and Murat Kumashev. (2024). Analysis of the agro-industrial sector of the Kyrgyz Republic. Ekonomika APK, 31(2): 41-50.
[45] Sualihu, Amidu Mohammed, Tov Assogbavi, and Alex Donto. (2023). Financial planning and forecasting in the oil and gas industry. In: The Economics of the Oil and Gas Industry. London: Routledge.
[46] Torres, José, Dalil Hadjout, Abderrazak Sebaa, Francisco Martínez-Álvarez, and Alicia Troncoso. (2021). Deep learning for time series forecasting: A survey. Big Data, 9(1): 3-21.
[47] Trusova, Natalia V., et al. (2019). Determinants of the development venture financing of the subjects of Agrarian market of Ukraine. Asia Life Sciences, 1: 377-398.
[48] Trusova, Natalia V., Sergey V. Kalchenko, Volodymyr D. Tsap, Volodymyr A. Ternovsky, and Olga P. Levchenko. (2017). Restrictions of financing the budget deficit of Ukraine. International Journal of Economic Research, 14(14): 353-364.
[49] Trusova, Natalia V., Serhii V. Karman, Maksym A. Tereshchenko, and Yurii O. Prus. (2018). Debt burden of the financial system of Ukraine and countries of the Eurozone: Policy of regulating of the risks. Espacios, 39(39): 30.
[50] Valle-Cruz, David, Vanessa Fernandez-Cortez, and J. Ramon Gil-Garcia. (2022). From E-budgeting to smart budgeting: Exploring the potential of artificial intelligence in government decision-making for resource allocation. Government Information Quarterly, 39(2): 101644.
[51] Wouters, Marc, and Frank Stadtherr. (2024). How management accountants purposefully create cash flow forecasts in capital budgeting: A field study of product development decisions. Accounting Perspectives, 23(3): 327-524.
[52] Yudina, Svitlana, Olena Lysa, Nataliia Diatlova, Andrii Drahun, and Olha Sarancha. (2022). Interaction of Enterprises with Financial Corporations: State, Problems, Mechanisms, Improvement of Relationships. Review of Economics and Finance, 20(1): 277-282.
[53] Forecast of socio-economic development of the Kyrgyz Republic. (2023). Available at: https://mineconom.gov.kg/ru/direct/3/28
[54] State budgets and loans. (2024). Available at: https://www.stat.kg/ru/opendata/category/3/
Published
2024-12-30
How to Cite
AMANBAEVA, Chynara et al.
Improvement of the Budget Forecasting System in the Kyrgyz Republic.
Theoretical and Practical Research in Economic Fields, [S.l.], v. 15, n. 4, p. 970 - 982, dec. 2024.
ISSN 2068-7710.
Available at: <https://journals.aserspublishing.eu/tpref/article/view/8687>. Date accessed: 06 jan. 2025.
doi: https://doi.org/10.14505/tpref.v15.4(32).14.
Section
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