STATISTIKAL ASSESSMENT OF INDIVIDUAL QUALIFICATIONS OF CUSTOMS INSPECTORS IN THE PROCESSING CUSTOMS DECLARATIONS BASED ON THE HARINGTON DESIRABILITY FUNCTION - Lebid, V. V.; Meish, Yu. A.; Kopiak, N. V. (Systems and Technologies, 2024)
This study utilizes statistical data on processed customs documents to develop an econometric model of the number of processed customs documents using correlation-regression analysis methods and Microsoft Excel tools. This study will be useful for customs affairs considering that modeling is a necessary tool which assists in identifying and analyzing the essential characteristics for a country’s foreign trade. Modeling is a crucial tool in customs affairs, as it helps to identify and analyze essential characteristics for the country’s foreign trade. Modeling is particularly important for the State Customs Service of Ukraine, as it allows to study the foreign trade processes without direct experimentation. Today the main aim of Ukraine’s state policy in the field of customs affairs is supporting and developing the national economy and integrating it into the global economy. To protect the national interests of Ukraine, it is necessary to continuously monitor and regulate foreign trade operations. The Cabinet of Ministers of Ukraine has approved a list of documents required for customs control and clearance of goods and vehicles crossing the customs border of Ukraine. The State Customs Service of Ukraine constantly collects, stores, processes, analyzes, protects, and disseminates official statistical information on goods moving across the customs border of Ukraine which are used in this article to conduct research. Key elements of high-quality analysis and forecasting include proper problem formulation, the appropriate selection and application of mathematical apparatus, and adherence to the methodology of conducting statistical research. During this study the special attention was given to determining the reliability of the obtained results and validating the adequacy of the constructed regression model. This, in turn, allows more accurate forecasting of the volume of processed customs documents in the upcoming year. The results obtained serve as an important tool for managing customs policy and planning the volume of Ukraine’s internal and external trade for the next period. This enables more efficient resource allocation, development of growth strategies, and optimization of customs procedures, which will facilitate Ukraine’s further integration into the global economic system.