This article explores the development of an agent-based model of Kamchatka Krai. It presents structure of the model, which includes territorial structure, population, economy, education system and transport infrastructure. The population of Kamchatka Krai is represented by agents grouped into households and residing in various cities and districts. The model reflects maturation, birth, and death of agents, marriages and divorces, as well as their psychological profiles. The economy is presented by administrative units and types of economic activity, which are divided into groups: export-oriented, budget, and those focused on local demand. Dynamics of export-oriented and budget industries are determined by scenario parameters. When modeling the associated changes at the organizational level, output and supply volumes are adjusted, employee wages are indexed, and new jobs are created if necessary. As a result, demand for products from industries focused on local demand increases, which, in turn, adjust output and supply, index wages, and create new jobs. Educational system in the model includes primary, secondary, and higher education. The peninsulas transport infrastructure is represented by highways, seaports, and airports. Economic development forecasts for the region were developed for a five-year period under the baseline and export-oriented scenarios. Calculations show a stable annual increase in GRP: 4% in the baseline scenario and 6% in the export-oriented scenario. In the baseline scenario, the greatest growth is observed in construction (7.1-9.7%) and leisure activities (6.8-8%). In the export-oriented scenario, even more active development is observed in construction (15.7-38.7%), crop production and livestock farming (7.8-8.4%), trade (6.8-6.9%), and leisure activities (8.8-9.9%). Analysis of the modeling results across the administrative structure of the region shows that in the baseline scenario, the fastest rates of economic development are expected in the Tigilsky District (5.1-5.4%), and in the export-oriented scenario, in Bystrinsky District (7.9-8.4%).
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Aleksandra Mashkova
Artificial Societies
Central Economics and Mathematics Institute
Kamchatka State University named after Vitus Bering
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Aleksandra Mashkova (Thu,) studied this question.
synapsesocial.com/papers/69c37bb3b34aaaeb1a67e602 — DOI: https://doi.org/10.18254/s207751800037548-1
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