AGRICULTURAL LABOR MARKET: CONCEPTUAL APPROACHES TO DIAGNOSTICS, MANAGEMENT AND FORECASTING

The purpose and objectives of the study, the main results of which are presented in this article, are due to the urgency of developing a new concept for the functioning of the agricultural labor market in conditions, firstly, of structural imbalances within its borders, and secondly, of a significant shortage of personnel in the agro-industrial complex of the Russian Federation. Solving these problems is complicated not only by the lack of optimal regulatory mechanisms, but also by the fact that traditional diagnostic, management, and forecasting models based on a single theoretical paradigm are unable to adequately reflect the complexity and dynamics of the modern agricultural labor market, which is affected by technological, institutional, and behavioral factors, and therefore offer prompt ways to respond. Taking this into account, the research work undertaken is focused on the specification of a new conceptual platform based on the synthesis of theoretical approaches and maximally useful for analyzing and forecasting the development of the agricultural labor market, as well as managing this process in modern conditions. The research is based on a critical analysis of classical and modern theoretical approaches to the study of the labor market, including neoclassical, Keynesian, monetarist, institutional and behavioral approaches. The methodological tools were the methods of system analysis, synthesis, logical modeling and conceptualization. The result of scientific research is a new concept of the agrarian labor market, which includes (1) eight basic principles of functioning, (2) its refined structure, and (3) scientific hypotheses, the verification of which allows empirical confirmation of the validity of the concept. The presented conceptual design, overcoming the limitations of monomethodological models and synthesizing interdisciplinary knowledge, provides researchers and practitioners with methodological tools for in-depth analysis and scientifically based forecasting of the functioning of the agricultural labor market in the prevailing environmental conditions.