The study is devoted to the problems of organising a state efficiency audit in the Russian Federation, which is a key tool for assessing the utilisation of public resources and the degree of achievement of the country's socio-economic goals. Based on the analysis of foreign practices, the study of problematic aspects of the organisation and implementation of state financial control, such as the audit of the efficiency of the use of public resources, was carried out. The purpose of the study was to investigate the essence and organisational and methodological aspects of conducting such a type of financial control as a performance audit in the public sector of the Russian Federation. In the course of the study, empirical research, comparative and statistical research, synthesis of theoretical and practical material were used. Methods of grouping and classification were used in the processing and systematisation of information. The problem of efficient use of public resources is one of the most pressing issues of the budget process in the Russian Federation. In these conditions, the role of state financial bodies is more important than ever, the purpose of which is to ensure the expediency, legality, and efficiency of the generation, distribution, and use of budget resources.
The study improved budgeting efficiency at industrial enterprises with evidence from Russia, Italy, and the Middle East. In the era of contemporary globalization and technological advancement, a budgeting system holds paramount significance in the effective management of the financial operations and activities, enhancing the overall efficiency of the firm's cash management, mitigating the risk of finance misallocation, and improving the overall financial performance of the enterprise. However, despite its effectiveness, there is a lack of evidence supporting budgeting automation and its efficiency in managing industrial enterprises. More so, limited theoretical and practical relevance is found in the context of Russia, Italy, and the Middle East. This research intended to fill the existing research gap where a qualitative research design was opted. Primary data were collected from the budgeting heads of 3 pharmaceutical firms, each located in Russia, Italy, and Iran. In-depth interviews with 3 budgeting heads identified that the conventional incremental budgeting system needed amendment and replacement with a consolidated and contemporary yet flexible approach to bring radical improvements at the macro-environment level within the industrial enterprise. The key findings led to the development of a model to improve budgeting efficiency, comprising three components: information and analytical/accounting support for budgeting, production accounting information, and a combination of the regulated operation prices. The consolidation of these three components can yield budgeting efficiency. Doi: 10.28991/ESJ-2023-07-01-013 Full Text: PDF
Improving the accuracy of cash flow forecasting in the TSA is key to fulfilling government payment obligations, minimizing the cost of maintaining the cash reserve, providing the absence of outstanding debt accumulation and ensuring investment in financial instruments to obtain additional income. This study aims to improve the accuracy of traditional methods of forecasting the time series compiled from the daily remaining balances in the TSAbased on prior decomposition using a discrete wavelet transform. The paper compares the influence of selecting a mother wavelet out of 570 mother wavelet functions belonging to 10 wavelet families (Haar;Dabeshies; Symlet; Coiflet; Biorthogonal Spline; Reverse Biorthogonal Spline; Meyer; Shannon; Battle-Lemarie; and Cohen–Daubechies–Feauveau) and the decomposition level (from 1 to 8) on the forecast accuracy of time series compiled from the daily remaining balances in the TSA in comparison with the traditional forecasting method without prior timeseries decomposition. The model with prior time series decomposition based on the Reverse Biorthogonal Spline Wavelet [5.5] mother wavelet function, upon the eighth iteration, features the highest accuracy, significantly higher than that of the traditional forecasting models. The choice of the mother wavelet and the decomposition level play an important role in increasing the accuracy of forecasting the daily remaining balances in the TSA.
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