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Economic importance and statistical significance: Guidelines for communicating empirical research

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  • Jane Miller
  • Yana van der Meulen Rodgers
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    Abstract

    A critical objective for many empirical studies is a thorough evaluation of both substantive importance and statistical significance. Feminist economists have critiqued neoclassical economics studies for an excessive focus on statistical machinery at the expense of substantive issues. Drawing from the ongoing debate about the rhetoric of economic inquiry and significance tests, this paper examines approaches for presenting empirical results effectively to ensure that the analysis is accurate, meaningful, and relevant for the conceptual and empirical context. To that end, it demonstrates several measurement issues that affect the interpretation of economic significance and are commonly overlooked in empirical studies. This paper provides guidelines for clearly communicating two distinct aspects of “significance” in empirical research, using prose, tables, and charts based on OLS, logit, and probit regression results. These guidelines are illustrated with samples of ineffective writing annotated to show weaknesses, followed by concrete examples and explanations of improved presentation.

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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Feminist Economics.

    Volume (Year): 14 (2008)
    Issue (Month): 2 ()
    Pages: 117-149

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    Handle: RePEc:taf:femeco:v:14:y:2008:i:2:p:117-149

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    Related research

    Keywords: Economic significance; regression analysis; statistical significance; writing; feminist economics; JEL Codes: Y1; A29; C10;

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    Cited by:
    1. Julie A. Nelson, 2012. "Are Women Really More Risk-Averse than Men?," GDAE Working Papers 12-05, GDAE, Tufts University.
    2. Athena Engman, 2013. "Is there life after P>0.05? Statistical significance and quantitative sociology," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 257-270, January.

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