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Citation-Capture Rates by Economic Journals:Do they Differ from Other Disciplines and Does it Matter?

Author

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  • David L. Anderson

    (Queen's University)

  • John Tressler

    (University of Waikato)

Abstract

In this paper we compare the rate of citation-capture across the social sciences and sciences, with particular attention paid to economics and its border disciplines generally located in Schools of Business. We also explore citation time-flow differences between a number of leading journals in economics and a representative science category, and between higher and lower ranked economics journals. Our findings suggest that short-term citation counting, either directly or indirectly, for purposes of generating impact factors and the like, introduces a bias in favour of the sciences over the social sciences. This is in addition to the well-known differences in the absolute number of cites between these discipline categories over the short and long term. Our findings call into question the usefulness of citation analysis in national research assessment exercises that concentrate on recent research contributions. Furthermore, within economics, we found short-term impact factors to be systematically biased in favour of lower ranked journals.

Suggested Citation

  • David L. Anderson & John Tressler, 2014. "Citation-Capture Rates by Economic Journals:Do they Differ from Other Disciplines and Does it Matter?," Working Papers in Economics 14/10, University of Waikato.
  • Handle: RePEc:wai:econwp:14/10
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    File URL: https://repec.its.waikato.ac.nz/wai/econwp/1410.pdf
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    References listed on IDEAS

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    1. Chia-Lin Chang & Michael McAleer & Les Oxley, 2011. "Great Expectatrics: Great Papers, Great Journals, Great Econometrics," Econometric Reviews, Taylor & Francis Journals, vol. 30(6), pages 583-619.
    2. David L. Anderson & John Tressler, 2013. "The Relevance of the “h-” and “g-” Index to Economics in the Context of A Nation-Wide Research Evaluation Scheme: The New Zealand Case," Economic Papers, The Economic Society of Australia, vol. 32(1), pages 81-94, March.
    3. Daniel Sgroi & Andrew J. Oswald, 2013. "How Should Peer‐review Panels Behave?," Economic Journal, Royal Economic Society, vol. 0, pages 255-278, August.
    4. John Tressler & David L. Anderson, 2012. "Citations as a Measure of the Research Outputs of New Zealand's Economics Departments: The Problem of 'Long and Variable Lags'," Agenda - A Journal of Policy Analysis and Reform, Australian National University, College of Business and Economics, School of Economics, vol. 19(1), pages 17-40.
    5. Jonathan M. Levitt & Mike Thelwall, 2008. "Patterns of annual citation of highly cited articles and the prediction of their citation ranking: A comparison across subjects," Scientometrics, Springer;Akadémiai Kiadó, vol. 77(1), pages 41-60, October.
    6. Hoepner, Andreas G.F. & Kant, Benjamin & Scholtens, Bert & Yu, Pei-Shan, 2012. "Environmental and ecological economics in the 21st century: An age adjusted citation analysis of the influential articles, journals, authors and institutions," Ecological Economics, Elsevier, vol. 77(C), pages 193-206.
    7. Jonathan Adams, 2005. "Early citation counts correlate with accumulated impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(3), pages 567-581, June.
    8. David L. Anderson & John Tressler, 2008. "Research Output in New Zealand Economics Department 2000-2006," Working Papers in Economics 08/05, University of Waikato.
    9. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2011. "Assessing the varying level of impact measurement accuracy as a function of the citation window length," Journal of Informetrics, Elsevier, vol. 5(4), pages 659-667.
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    Cited by:

    1. David Anderson & John Tressler, 2018. "The Impact of Citation Timing: A Framework and Examples," Review of Economics and Institutions, Università di Perugia, vol. 9(2).

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    More about this item

    Keywords

    research measurement; research assessment exercises; time pattern of citations;
    All these keywords.

    JEL classification:

    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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