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Confidence Intervals for Recursive Journal Impact Factors

Author

Listed:
  • Johannes Koenig

    (Department of Economics, Economic Policy, Innovation and Entrepreneurship, University of Kassel, Germany)

  • David I. Stern

    (Arndt-Corden Department of Economics, Crawford School of Public Policy, The Australian National University, 132 Lennox Crossing, Acton, ACT 2601, Australia)

  • Richard S.J. Tol

    (Department of Economics, University of Sussex, BN1 9SL Falmer, United Kingdom)

Abstract

We compute confidence intervals for recursive impact factors, that take into account that some citations are more prestigious than others, as well as for the associated ranks of journals, applying the methods to the population of economics journals. The Quarterly Journal of Economics is clearly the journal with greatest impact, the confidence interval for its rank only includes one. Based on the simple bootstrap, the remainder of the "Top-5" journals are in the top 6 together with the Journal of Finance, while the Xie et al. (2009), and Mogstad et al. (2022) methods generally broaden estimated confidence intervals, particularly for mid-ranking journals. All methods agree that most apparent differences in journal quality are, in fact, mostly insignicant.

Suggested Citation

  • Johannes Koenig & David I. Stern & Richard S.J. Tol, 2022. "Confidence Intervals for Recursive Journal Impact Factors," Working Paper Series 0122, Department of Economics, University of Sussex Business School.
  • Handle: RePEc:sus:susewp:0122
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Bibliometrics; citation analysis; publishing; bootstrapping;
    All these keywords.

    JEL classification:

    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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