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Identifying excellent researchers: A new approach

Listed author(s):
  • 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.

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File URL: http://www.sciencedirect.com/science/article/pii/S1751157713000503
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Article provided by Elsevier in its journal Journal of Informetrics.

Volume (Year): 7 (2013)
Issue (Month): 4 ()
Pages: 803-810

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Handle: RePEc:eee:infome:v:7:y:2013:i:4:p:803-810
DOI: 10.1016/j.joi.2013.06.003
Contact details of provider: Web page: http://www.elsevier.com/locate/joi

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  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.
  2. Neus Herranz & Javier Ruiz-Castillo, 2012. "Sub-field normalization in the multiplicative case: High- and low-impact citation indicators," Research Evaluation, Oxford University Press, vol. 21(2), pages 113-125, April.
  3. Lundberg, Jonas, 2007. "Lifting the crown—citation z-score," Journal of Informetrics, Elsevier, vol. 1(2), pages 145-154.
  4. Seiler, Christian & Wohlrabe, Klaus, 2012. "Ranking economists on the basis of many indicators: An alternative approach using RePEc data," Journal of Informetrics, Elsevier, vol. 6(3), pages 389-402.
  5. Waltman, Ludo & van Eck, Nees Jan & van Leeuwen, Thed N. & Visser, Martijn S. & van Raan, Anthony F.J., 2011. "Towards a new crown indicator: Some theoretical considerations," Journal of Informetrics, Elsevier, vol. 5(1), pages 37-47.
  6. M. Ruth & K. Donaghy & P. Kirshen, 2006. "Introduction," Chapters,in: Regional Climate Change and Variability, chapter 1 Edward Elgar Publishing.
  7. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
  8. van Raan, Anthony F.J. & van Leeuwen, Thed N. & Visser, Martijn S. & van Eck, Nees Jan & Waltman, Ludo, 2010. "Rivals for the crown: Reply to Opthof and Leydesdorff," Journal of Informetrics, Elsevier, vol. 4(3), pages 431-435.
  9. Beirlant, Jan & Glänzel, Wolfgang & Carbonez, An & Leemans, Herlinde, 2007. "Scoring research output using statistical quantile plotting," Journal of Informetrics, Elsevier, vol. 1(3), pages 185-192.
  10. Falk, Michael, 1986. "On the estimation of the quantile density function," Statistics & Probability Letters, Elsevier, vol. 4(2), pages 69-73, March.
  11. Sarabia, José María & Prieto, Faustino & Trueba, Carmen, 2012. "Modeling the probabilistic distribution of the impact factor," Journal of Informetrics, Elsevier, vol. 6(1), pages 66-79.
  12. Thomas Krichel & Christian Zimmermann, 2009. "The Economics of Open Bibliographic Data Provision," Economic Analysis and Policy, Elsevier, vol. 39(1), pages 143-152, March.
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