Handbook of Research Methods in Complexity Science
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Handbook of Research Methods in Complexity Science

Theory and Applications

Edited by Eve Mitleton-Kelly, Alexandros Paraskevas and Christopher Day

This comprehensive Handbook is aimed at both academic researchers and practitioners in the field of complexity science. The book’s 26 chapters, specially written by leading experts, provide in-depth coverage of research methods based on the sciences of complexity. The research methods presented are illustratively applied to practical cases and are readily accessible to researchers and decision makers alike.
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Chapter 19: Complex scenarios in socio-economic data: a comprehensive analytical study

Theory and Applications

Assistant Professor Sanjay Kumar Palit, Associate Professor Santo Banerjee and Assisant Professor Sayan Mukherjee

Abstract

The socio-economic scenario of a country reflects its social, economic, political, ideological, ethical, cultural, or communicative habits, making its proper analysis for different countries quite challenging. Complexity science has provided some new methods and tools for dealing with this challenge. Country-level Gross Domestic Product (GDP) and population are the two most important issues in the socio-economic context. In order to show the effectiveness of different nonlinear tools in analysing socio-economic data, the authors implemented three popular nonlinear tools: recurrence rate, mean conditional recurrence (MCR) and complex networks (CN) to analyse country level GDP and population data to validate the derived results with the standard conclusions based on general theories of economics. recurrence rate is used to show how two non-identical systems get synchronized through their phase spaces. MCR detects the driver and response system in synchronized states and CN reflects the overall scenarios of the complex systems by its various statistical measures.

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