IDEAS home Printed from https://ideas.repec.org/p/sus/susewp/6013.html
   My bibliography  Save this paper

Measuring catch-up growth in malnourished populations

Author

Listed:
  • Richard S.J. Tol

    (Department of Economics, University of Sussex
    Institute for Environmental Studies, Vrije Universiteit, Amsterdam, The Netherlands
    Department of Spatial Economics, Vrije Universiteit, Amsterdam, The Netherlands)

Abstract

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 number.

Suggested Citation

  • Richard S.J. Tol, 2013. "Measuring catch-up growth in malnourished populations," Working Paper Series 6013, Department of Economics, University of Sussex Business School.
    • Handle: RePEc:sus:susewp:6013
    as

    Download full text from publisher

    File URL: http://www.sussex.ac.uk/economics/documents/wps-60-2013.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Glenn Ellison, 2013. "How Does the Market Use Citation Data? The Hirsch Index in Economics," American Economic Journal: Applied Economics, American Economic Association, vol. 5(3), pages 63-90, July.
    3. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
    4. Christian Zimmermann, 2013. "Academic Rankings with RePEc," Econometrics, MDPI, vol. 1(3), pages 1-32, December.
    5. Thomas Krichel & Christian Zimmermann, 2009. "The Economics of Open Bibliographic Data Provision," Economic Analysis and Policy, Elsevier, vol. 39(1), pages 143-152, March.
    6. Thed N. Van Leeuwen & Martijn S. Visser & Henk F. Moed & Ton J. Nederhof & Anthony F. J. Van Raan, 2003. "The Holy Grail of science policy: Exploring and combining bibliometric tools in search of scientific excellence," Scientometrics, Springer;Akadémiai Kiadó, vol. 57(2), pages 257-280, June.
    7. Tomislav Hengl & Budiman Minasny & Michael Gould, 2009. "A geostatistical analysis of geostatistics," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(2), pages 491-514, August.
    8. 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.
    9. 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.
    10. 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.
    11. Falk, Michael, 1986. "On the estimation of the quantile density function," Statistics & Probability Letters, Elsevier, vol. 4(2), pages 69-73, March.
    12. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
    13. Liming Liang, 2006. "h-index sequence and h-index matrix: Constructions and applications," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 153-159, October.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics Profession > Ranking in Economics > Ranking Methodology

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tol, Richard S.J., 2013. "Identifying excellent researchers: A new approach," Journal of Informetrics, Elsevier, vol. 7(4), pages 803-810.
    2. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
    3. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    4. David L. Anderson & John Tressler, 2017. "Researcher rank stability across alternative output measurement schemes in the context of a time limited research evaluation: the New Zealand case," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4542-4553, September.
    5. Lutz Bornmann & Alexander Butz & Klaus Wohlrabe, 2018. "What are the top five journals in economics? A new meta-ranking," Applied Economics, Taylor & Francis Journals, vol. 50(6), pages 659-675, February.
    6. Christian Zimmermann, 2013. "Academic Rankings with RePEc," Econometrics, MDPI, vol. 1(3), pages 1-32, December.
    7. Joseph Gerald Hirschberg & Jeanette Ngaire Lye, 2020. "Grading Journals In Economics: The Abcs Of The Abdc," Journal of Economic Surveys, Wiley Blackwell, vol. 34(4), pages 876-921, September.
    8. Klaus Wohlrabe, 2014. "Eine Kritik des FAZ-Ökonomenrankings 2013," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 67(13), pages 63-67, July.
    9. Etienne Farvaque & Frédéric Gannon, 2018. "Profiling giants: the networks and influence of Buchanan and Tullock," Public Choice, Springer, vol. 175(3), pages 277-302, June.
    10. Rodrigo Dorantes-Gilardi & Aurora A. Ramírez-Álvarez & Diana Terrazas-Santamaría, 2023. "Is there a differentiated gender effect of collaboration with super-cited authors? Evidence from junior researchers in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2317-2336, April.
    11. Ferda, HALICIOGLU, 2014. "Research Ranking Place of Turkish Economists in the World," MPRA Paper 54058, University Library of Munich, Germany.
    12. Gnewuch, Matthias & Wohlrabe, Klaus, 2018. "Super-efficiency of education institutions: an application to economics departments," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 26, pages 610-623.
    13. Carlo D'Ippoliti, 2021. "“Many‐Citedness”: Citations Measure More Than Just Scientific Quality," Journal of Economic Surveys, Wiley Blackwell, vol. 35(5), pages 1271-1301, December.
    14. Tol, Richard S.J., 2023. "Nobel begets Nobel in economics," Journal of Informetrics, Elsevier, vol. 17(4).
    15. Klaus Wohlrabe & Lutz Bornmann, 2022. "Alphabetized co-authorship in economics reconsidered," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2173-2193, May.
    16. Klaus Wohlrabe & Elisabeth Friedrich, 2017. "The efficiency of economics departments reconsidered," Economics Bulletin, AccessEcon, vol. 37(3), pages 1602-1611.
    17. Matthias Gnewuch & Klaus Wohlrabe, 2018. "Die (Super-)Effizienz von volkswirtschaftlichen Fakultäten," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 71(15), pages 30-34, August.
    18. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    19. Katharina Rath & Klaus Wohlrabe, 2016. "Trends in economics publications represented by JEL categories between 2007 and 2013," Applied Economics Letters, Taylor & Francis Journals, vol. 23(9), pages 660-663, June.
    20. Püttmann, Vitus & Thomsen, Stephan L. & Trunzer, Johannes, 2020. "Zur Relevanz von Ausstattungsunterschieden für Forschungsleistungsvergleiche: Ein Diskussionsbeitrag für die Wirtschaftswissenschaften in Deutschland," Hannover Economic Papers (HEP) dp-679, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, revised Mar 2021.

    More about this item

    Keywords

    quantile kernel regression; Hirsch number; economics;
    All these keywords.

    JEL classification:

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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Papers using RePEc data

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sus:susewp:6013. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: University of Sussex Business School Communications Team (email available below). General contact details of provider: https://edirc.repec.org/data/ecsusuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.