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Empirical evidence on the topological properties of structural paths and some notes on its theoretical explanation

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  • Stijepic, Denis

Abstract

The mathematical literature has developed a large pool of topological concepts and theorems for dynamic systems analysis. The aim of our paper is to make a first step towards the application of these concepts and theorems in the analysis of (long-run) structural change (in the three-sector framework). Our approach focuses on two of the most basic topological notions, namely intersection and self-intersection of trajectories on a two-dimensional domain. We discuss the mathematical foundations of the application of these concepts in structural change analysis, use them for analyzing empirical data, and elaborate new stylized facts stating that different countries’ structural change trajectories are (non-self-)intersecting. Finally, we discuss briefly the theoretical explanations of (non-self-)intersection and a wide range of new research topics relating to (a) the topological classification and comparison of models and evidence and (b) the application of (further) topological concepts in standard branches of growth and development theory.

Suggested Citation

  • Stijepic, Denis, 2016. "Empirical evidence on the topological properties of structural paths and some notes on its theoretical explanation," MPRA Paper 82473, University Library of Munich, Germany, revised 26 Oct 2017.
    • Handle: RePEc:pra:mprapa:82473
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    References listed on IDEAS

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    1. Stijepic, Denis, 2018. "Models of Continuous Dynamics on the 2-Simplex and Applications in Economics," MPRA Paper 86341, University Library of Munich, Germany.

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    More about this item

    Keywords

    structural change; labor; allocation; savings; functional income distribution; long run; dynamics; trajectory; intersection; self-intersection; differential equations; geometry; topology;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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