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Modeling socio-economic systems under uncertainty

Digitalization, artificial intelligence, theory of change

study guide - workshop, 2nd edition / Prokopchina S. V., Shcherbakov G. A., Efimov Yu. V.; under. ed. G. A. Shcherbakova. - M .: Publishing house "SCIENTIFIC LIBRARY", 2019. - 508 p.

ISBN 978-5-907242-40-1

Modern economic systems are unique complex objects. They function and develop under the influence of various environmental factors and, in a specific way for each of these systems, change in time and space. The dynamics of their behavior is difficult to predict, and the evidence to describe it, as a rule, is not enough. These data are incomplete, inaccurate and heterogeneous, which generally determines the situation of uncertainty. At the same time, practically demanded models of economic systems should adequately reflect the properties and relationships of the modeled objects. For this reason, for their effective modeling, it is necessary to apply methods oriented to work in conditions of uncertainty. Possible solutions to the above problems are the subject of this tutorial. It is intended not only for the reader who is interested in the theory of modeling economic systems, but also is an entertaining workshop containing examples of the application of modern economic and mathematical methods in solving analytical and prognostic problems in various fields of the real economy. The main attention is paid to the regularizing Bayesian approach (BPS), which, since the 80s of the last century, has been successfully applied to solve a wide range of technical and socio-economic problems. The workshop presents both the theoretical foundations of the BPO and examples of its application for modeling economic systems under conditions of uncertainty. The manual is equipped with questions for self-training and practical tasks and can be useful both to scientists, teachers, graduate students and students of higher educational institutions, as well as specialists in the field of system modeling and management of complex national economic facilities and complexes.

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