STATISTICAL BOUNDARIES AND THE STRUCTURE OF THE IT INDUSTRY IN THE ECONOMIC ANALYSIS OF HUMAN CAPITAL: NATIONAL AND INTERNATIONAL APPROACHES

Анотація

The article aims to define the statistical boundaries and structural composition of the IT industry as a key environment for human capital development, taking into account national and international classifications of economic activities and occupational employment. The methodological framework is based on general scientific methods of analysis, comparison, and structural-logical reasoning, complemented by a systems approach and data visualization techniques. A comparative analysis of national statistical classifications (KVED 2010 and NACE 2.1-UA) and the international market-oriented classification system – the Global Industry Classification Standard (GICS) – is conducted to examine how diff erent classification systems represent the structure of the IT industry across their hierarchical levels. The results reveal significant inconsistencies in defining the statistical boundaries of the IT industry, which aff ect the measurement of its scale, employment patterns, and the characteristics of human capital development. To address these discrepancies, the paper proposes an integrated approach that combines statistical and market-oriented classifications. The proposed model distinguishes the core of the IT industry, comprising activities directly related to the development and maintenance of digital technologies, and adjacent segments that support the functioning of the digital economy. The practical significance of the results lies in improving the quality of economic and statistical assessments of the IT sector, enabling a more accurate analysis of occupational structures, evaluating the sector’s contribution to national and regional economies, identifying productivity gaps within the industry, and supporting evidence-based human capital and IT development policies in Ukraine. Keywords: IT industry; human capital; economic activity classification; GICS; NACE; economic analysis, occupational structure; digital economy

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