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Identifying excellent researchers: A new approach


  • Tol, Richard S.J.


Quantile kernel regression is a flexible way to estimate the percentile of a scholar's quality stratified by a measurable characteristic, without imposing inappropriate assumption about functional form or population distribution. Quantile kernel regression is here applied to identifying the one-in-a-hundred economist per age cohort according to the Hirsch index.

Suggested Citation

  • Tol, Richard S.J., 2013. "Identifying excellent researchers: A new approach," Journal of Informetrics, Elsevier, vol. 7(4), pages 803-810.
  • Handle: RePEc:eee:infome:v:7:y:2013:i:4:p:803-810
    DOI: 10.1016/j.joi.2013.06.003

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    References listed on IDEAS

    1. Herranz, Neus & Ruiz-Castillo, Javier, 2012. "Sub-field normalization in the multiplicative case: Average-based citation indicators," Journal of Informetrics, Elsevier, vol. 6(4), pages 543-556.
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    3. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
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    6. Falk, Michael, 1986. "On the estimation of the quantile density function," Statistics & Probability Letters, Elsevier, vol. 4(2), pages 69-73, March.
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    1. repec:eee:infome:v:11:y:2017:i:2:p:564-582 is not listed on IDEAS

    More about this item


    Quantile kernel regression; Hirsch index; Economics;

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists


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