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Classifying Non-banking Monetary Systems using Web Data

Author

Listed:
  • Ariane Tichit

    (CERDI - Centre d'Études et de Recherches sur le Développement International - UdA - Université d'Auvergne - Clermont-Ferrand I - CNRS - Centre National de la Recherche Scientifique)

  • Clément Mathonnat

    () (CERDI - Centre d'Études et de Recherches sur le Développement International - UdA - Université d'Auvergne - Clermont-Ferrand I - CNRS - Centre National de la Recherche Scientifique)

  • Diego Sébastien Landivar

    (Business School Clermont - France Business School Clermont - France Business School [France Business School])

Abstract

This paper develops a new classification of non-banking currencies projects based on a lexical analysis from web data. The advantage of this method is to derive an endogenous typology of monetary projects, based on how currencies are depicted on the internet. Therefore, it allows to by-pass issues face for now in the literature to uncover a clear classification of non-banking currencies projects from exogenous elements. Our textual corpus consists in 320 web pages, corresponding to 1210 text pages. We first applied to our data a downward hierarchical clustering, which enables us to endogenously derive five different classes, allowing us to operate distinctions not only between non-banking currencies projects, but also between these latter and the standard monetary system. Then, we resorted to a similarity analysis and according to our results; all non-banking currencies projects define themselves in relation to the standard monetary system, with the exception of Local Exchange Trading Systems (LETs).

Suggested Citation

  • Ariane Tichit & Clément Mathonnat & Diego Sébastien Landivar, 2015. "Classifying Non-banking Monetary Systems using Web Data," Working Papers halshs-01230219, HAL.
  • Handle: RePEc:hal:wpaper:halshs-01230219
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-01230219
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    References listed on IDEAS

    as
    1. Michael S Evans, 2009. "Zelizer's Theory of Money and the Case of Local Currencies," Environment and Planning A, , vol. 41(5), pages 1026-1041, May.
    2. Seyfang, Gill & Longhurst, Noel, 2013. "Growing green money? Mapping community currencies for sustainable development," Ecological Economics, Elsevier, vol. 86(C), pages 65-77.
    3. Michael S Evans, 2014. "A Computational Approach to Qualitative Analysis in Large Textual Datasets," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-10, February.
    4. Jérôme Blanc, 2011. "Classifying "CCs": Community, complementary and local currencies' types and generations," Post-Print halshs-00583587, HAL.
    5. Jérôme Blanc, 2013. "Penser la pluralité des monnaies à partir de Polanyi : un essai de typologie," Post-Print halshs-00828095, HAL.
    6. Jérôme Blanc & Marie Fare, 2012. "Chartes et comités d'agrément dans les dispositifs de monnaies citoyennes," Working Papers halshs-00758172, HAL.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Non-banking money; Text mining; Web data; Downward hierarchical clustering; Similarity analysis;

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • O35 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Social Innovation

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