Bìznes Inform (Jan 2020)

Assessing the Quality of Information on Administrative Infractions and Its Statistical Processing: Indicators and Criteria

  • Hinchuk Liliia I.,
  • Bashkirov Sergey V.

DOI
https://doi.org/10.32983/2222-4459-2020-1-244-255
Journal volume & issue
Vol. 1, no. 504
pp. 244 – 255

Abstract

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Official statistical information on administrative infractions comes from many sources and is used by a large number of different users with different requirements. In this regard, there is a need to further implement a minimum standard for the quality of information on administrative infractions, the development and formation of a certain group of indicators to determine it. The research is aimed at identifying the main indicators and quality criteria for the information on administrative infractions, statistical examinations and statistical processing, using the world practice of evaluating the quality of processes "Generic Statistical Business Process Model" v. 5.1 (GSBPM). The GSBPM quality indicators have been developed by the Committee on Standards and Standardization of the High-Level Group for the Modernization of Official Statistics. For the purpose of identification, the main criteria for each of the subprocesses and the indicators that determine their compliance have been defined. These indicators were chosen taking into account both national properties and some specific properties of processing statistical information of this very type. In view of the fact that the proposed national model of statistical processing of information on administrative infractions provides for two levels of the process, the indicators of sub-processes taken together form a common system of indicators of statistical processing of information on administrative infractions. Thus, in the course of research it is found that ensuring the quality of statistical information requires not only an assessment of the appropriate quality of data on administrative infractions, but also an assessment of the quality of processing this statistical information, what can be achieved by using a process approach.

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