DOI

Development of nonlinear dynamic controlled input-output models and their analysis are of interest both to mathematicians and economists. This paper discusses one of such models. The focus is on relations between phase variables (outputs) and macroeconomic parameters, and also on the consumption sphere modeling. The main objective of this work is to show how to effectively manage the profit tax rate to maximize the budget revenue while maintaining a given economy growth. This economic task is reduced to a nonlinear problem of optimal control. To solve this problem, we use the adaptive method of optimal control (Gabasov's method). The main idea is to reduce an optimal control problem to an interval problem of linear programming. We test the approach on the example of German economy. The model is determined based on the information obtained from the WIOD tables and World Bank data (Germany, period: 2013-2014). Our approach is implemented as a software package in MATLAB environment.
Original languageEnglish
Title of host publicationProceedings of the 3rd International Conference on Applications in Information Technology, ICAIT 2018
EditorsKlyuev Vitaly, Pyshkin Evgeny, Natalia Bogach
PublisherAssociation for Computing Machinery
Pages80-84
Number of pages5
ISBN (Electronic)978-1-4503-6516-1
DOIs
StatePublished - 1 Nov 2018
Event3rd International Conference on Applications in Information Technology, ICAIT 2018 - Aizu-Wakamatsu, Japan
Duration: 1 Nov 20183 Nov 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd International Conference on Applications in Information Technology, ICAIT 2018
Country/TerritoryJapan
CityAizu-Wakamatsu
Period1/11/183/11/18

    Research areas

  • Approximation, Dynamic input-output model, Identification, Nonlinear system, Optimal control

    Scopus subject areas

  • Control and Optimization
  • Applied Mathematics
  • Economics, Econometrics and Finance (miscellaneous)
  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

ID: 36313743