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Econometrics as a Con Art

Author

Listed:
  • Imad A. Moosa

Abstract

Imad Moosa challenges convention with this comprehensive and compelling critique of econometrics, condemning the common practices of misapplied statistical methods in both economics and finance.

Individual chapters are listed in the "Chapters" tab

Suggested Citation

  • Imad A. Moosa, 2017. "Econometrics as a Con Art," Books, Edward Elgar Publishing, number 17257.
    • Handle: RePEc:elg:eebook:17257
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    File URL: https://www.elgaronline.com/view/9781785369940/9781785369940.xml
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    Citations

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    Cited by:

    1. Iva Bulatović & Ana Stranjančević & Darko Lacmanović & Andrej Raspor, 2017. "Casino Business in the Context of Tourism Development (Case: Montenegro)," Social Sciences, MDPI, vol. 6(4), pages 1-16, November.
    2. Jae H. Kim & In Choi, 2021. "Choosing the Level of Significance: A Decision‐theoretic Approach," Abacus, Accounting Foundation, University of Sydney, vol. 57(1), pages 27-71, March.
    3. Jae H. Kim & Kamran Ahmed & Philip Inyeob Ji, 2018. "Significance Testing in Accounting Research: A Critical Evaluation Based on Evidence," Abacus, Accounting Foundation, University of Sydney, vol. 54(4), pages 524-546, December.
    4. Imad A. Moosa, 2020. "The bitcoin: a sparkling bubble or price discovery?," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 93-113, March.
    5. G. Filatrella & N. De Liso, 2019. "Predicting one type of technological motion? A nonlinear map to study the 'sailing-ship' effect," Papers 1912.11250, arXiv.org.
    6. Bichler, Shimshon & Nitzan, Jonathan, 2021. "The 1-2-3 Toolbox of Mainstream Economics: Promising Everything, Delivering Nothing," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue 98, pages 23-48.

    Book Chapters

    The following chapters of this book are listed in IDEAS

    More about this item

    Keywords

    Economics and Finance;

    Statistics

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