Planning and Forecasting Customs Revenues to the State Budget: A Case Study of Ukraine

Abstract

The paper aims at the studying of the planning and forecasting process, as well as the formation of a dynamic model of customs revenues to the state budget on the example of Ukraine. Design/Methodology/Approach: The methodology of the regression data analysis was used to assess the receipt of customs payments to the budget. The parameters of the regression models are selected by the Least Squares Method. To assess the significance of the regression parameters, their variances and the covariance matrix, the diagonal elements of which are the variance parameters, are calculated. Along with the linear and power model, the Brandon model is considered. The adequacy of the model for forecasting customs revenues was assessed using the coefficient of determination. Findings: Factor analysis by the method of main components allowed us to conclude that the size of tax revenues to the state budget is most influenced by two main components, monetary and macroeconomic. Multifactor regression analysis and multiple processing of statistical data resulted in finding that it is the volume of imports and the national currency that have the greatest impact on the amount of taxes and fees to the state budget. Inflationary processes are not significant, but still affect the amount of tax revenues to the state budget, which makes it possible to increase the accumulation of taxes and fees to the budget by raising prices. Practical Implications: Experiments on forecasting the receipt of taxes and fees to the budget using a dynamic model confirmed its good predictive properties and enabled us to recommend the application of the proposed dynamic model in the practice of customs and tax authorities in their planning of tax proceeds to the state budget. Originality/Value: The results of the study reflect the applicability and effectiveness of the proposed dynamic model. Consequently, the dynamic model of planning and forecasting the customs revenues to the budget may constitute an alternative to the existing models.

Budget Execution and Public Spending Quality in Regional Governments: A Systematic Literature Review

“…At the conclusion of this rigorous process, 60 primary studies were selected for qualitative and quantitative evaluation cited as [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], …”

Comparing Neural Network Autoregressive Method for Import Duty Revenue Forecasting

“…This revenue includes import taxes (value added tax, luxury tax, income tax), import duty and export tax. Conducting on the example of Ukraine, a study from European Research Studies Journal explained that the forecasting of customs revenue is influenced by two main components: monetary and macroeconomics indicators including (GDP, export volumes, import duty rates, and inflation rate (Martyniuk et al, 2021).…”