APPLICATION OF ORDINAL STATISTICS TO DETERMINE THE OPTIMAL NUMBER OF PERIODS WHEN EVALUATING SOCIO-ECONOMIC SYSTEMS

К. О. Ломанов, Т. П. Рибальченко

Abstract


When evaluating any objects of qualimetry, information methods are used, which can be divided into methods of mathematical physics and methods of mathematical statistics. To evaluate socio-economic systems, methods of mathematical statistics are used, which are classified as parametric and non-parametric. An approach to evaluating socio-economic systems under conditions of limited statistical information is proposed, based on the use of ordinal statistics. The authors draw attention to the need to determine the minimum number of observation periods necessary for a reliable assessment of the state of socio-economic systems, in particular when collecting data annually. It is noted that parametric estimation methods, unlike non-parametric ones, allow reducing the amount of necessary information, provided that information about the distribution law of a random variable is available. In this regard, a method for identifying the distribution law based on ordinal statistics has been developed. According to this methodology, the mathematical expectations of ordered samples are compared with tabulated values for normal, uniform and triangular distributions. The method has been tested on the example of socio-economic development indicators of European Union countries. Data for Austria was used to test the methodology. The results showed that the indicators have a normal distribution. Further comparison of the variances of normalised random variables with tabulated values makes it possible to determine the minimum number of periods for reliable estimation. In the example considered, it was determined that the minimum required period is seven years. The results obtained can be used to optimise the processes of monitoring and analysing the functioning of socio-economic systems using information and analytical management systems. The proposed approach provides a balance between the accuracy of the assessment and the minimisation of the amount of statistical information required. The methodology can be adapted to other types of systems where it is important to ensure the validity of conclusions with limited data collection resources.


Keywords


ordinal statistics; distribution law; socio-economic systems; law identification; information and communication technologies

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DOI: https://doi.org/10.32620/oikit.2025.104.16

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