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The Ranking of Researchers by Publications and Citations: Using RePEc Data

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  • Kjell HAUSKEN

    (Faculty of Social Sciences, University of Stavanger, Norway)

Abstract

Researcher-level metrics assess a researcher’s publications and number of citations for each publication. This paper tests empirically 28 two-variable metrics, 26 of which are new in this paper, determined as geometric means from eight one-variable metrics. The 54 highest ranked researchers in RePEc are considered, 13 of whom are Nobel prize winners. One new one-variable metric, the number of citations for the 10th most cited publication, is introduced. Characteristics of the eight one-variable metrics are considered, illustrating why two-variable metrics are needed. The 54 researchers are ranked for all 36 metrics. The lowest sum of ranks for the 13 Nobel prize winners occurs for metric , the number of citations for the highest cited publication. The 13 Nobel prize winners have on average 5.3 higher rank on than on , suggesting a need for being widely cited, not captured by the -index. The metric , the square root of the product of the number of publications and the citation count, proposed as an interesting metric, correlates best with the RePEc scores. Correlations between the 36 metrics are determined. The 28 two-variable metrics are tentatively ranked according to how they capture characteristics apparently not captured by the one-variable metrics.

Suggested Citation

  • Kjell HAUSKEN, 2016. "The Ranking of Researchers by Publications and Citations: Using RePEc Data," Journal of Economics Bibliography, KSP Journals, vol. 3(4), pages 530-558, December.
    • Handle: RePEc:ksp:journ6:v:3:y:2016:i:4:p:530-558
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    References listed on IDEAS

    as
    1. Christian Zimmermann, 2013. "Academic Rankings with RePEc," Econometrics, MDPI, vol. 1(3), pages 1-32, December.
    2. S. Alonso & F. J. Cabrerizo & E. Herrera-Viedma & F. Herrera, 2010. "hg-index: a new index to characterize the scientific output of researchers based on the h- and g-indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 391-400, February.
    3. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    4. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    5. Chun-Ting Zhang, 2009. "The e-Index, Complementing the h-Index for Excess Citations," PLOS ONE, Public Library of Science, vol. 4(5), pages 1-4, May.
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    Cited by:

    1. Nadia Simoes & Nuno Crespo, 2020. "A flexible approach for measuring author-level publishing performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 331-355, January.
    2. Marlo M. Vernon & C. Makenzie Danley & Frances M. Yang, 2021. "Developing a measure of innovation from research in higher education data," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3919-3928, May.
    3. Mark Levene & Martyn Harris & Trevor Fenner, 2020. "A two-dimensional bibliometric index reflecting both quality and quantity," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(3), pages 1235-1246, June.

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    More about this item

    Keywords

    Scientific impact indices; Metrics; RePEc; Publications; Citations; Research output; Indices Ranking.;
    All these keywords.

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • C00 - Mathematical and Quantitative Methods - - General - - - General

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    1. Papers using RePEc data

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