Economic tomography: the possibility to anticipate and respond to socio-economic crises

Aleksandr A. Kuklin, Gennadiy P. Bystray, Sergey A. Okhotnikov, Elena V. Vasilyeva

Abstract


The article discusses an approach based on an original hypothesis related to the peculiarities of Russia’s development (on the one hand, its scale, the Russian mentality and a certain closeness of the economy; on the other hand, a significant dominant resource and human potential, and, as a consequence, a genuine role in the global economic community), the diagnosis of which (at the level of the well-being of individuals and inhabited areas) can be used to identify crises, provide an early assessment of threats to socio-economic development of regions as well as help to evaluate the state of the region over a 3 to 5 year period. In other words, in order to ensure that executives have enough time to mount a sufficiently rapid response to the crises and administrative errors and to reduce the impact of emerging threats. The aim of this paper is to present theoretical and methodological tools for the recognition of the early stages of emerging threats, allowing fewer losses to be experienced during the crisis period.

Simulation experiments were carried out for the purpose of classifying previously occurring social and economic crises (9 possible variants were reviewed) and mathematically processed trajectories of change in the main indicators for the well-being of individuals and inhabited areas, taking the influence of various factors into account. On the basis of the authors’ proposed approach (referred to as economic tomography) an attempt is made to comprehensively assess the state of sample representative regions of Russia.


Keywords


economic tomography; welfare of individuals and inhabited areas; autocorrelation of parameter function shearing; crisis classification; system of non-linear non-homogeneous diflerential equations

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References


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DOI: https://doi.org/10.15826/recon.2015.4.017

Copyright (c) 2018 Aleksandr A. Kuklin, Gennadiy P. Bystray, Sergey A. Okhotnikov, Elena V. Vasilyeva