IDEAS home Printed from https://ideas.repec.org/p/kyo/wpaper/851.html
   My bibliography  Save this paper

What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance

Author

Listed:
  • Chia-Lin Chang

    (Department of Applied Economics Department of Finance National Chung Hsing University, Taiwan)

  • Michael McAleer

    (Econometric Institute Erasmus School of Economics Erasmus University Rotterdam and Tinbergen Institute The Netherlands and Department of Quantitative Economics Complutense University of Madrid and Institute of Economic Research Kyoto University)

Abstract

Experts possess knowledge and information that are not publicly available. The paper is concerned with forecasting academic journal quality and research impact using a survey of international experts from a national project on ranking academic finance journals in Taiwan. A comparison is made with publicly available bibliometric data, namely the Thomson Reuters ISI Web of Science citations database (hereafter ISI) for the Business - Finance (hereafter Finance) category. The paper analyses the leading international journals in Finance using expert scores and quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in the expert scores and alternative RAMs, where the RAMs are based on alternative transformations of citations taken from the ISI database. Alternative RAMs may be calculated annually or updated daily to answer the perennial questions as to When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs include the most widely used RAM, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, PI-BETA (Papers Ignored - By Even The Authors), 2-year Self-citation Threshold Approval Ratings (2Y-STAR), Historical Self-citation Threshold Approval Ratings (H-STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). As data are not available for 5YIF, Article Influence and CAI for 13 of the leading 34 journals considered, 10 RAMs are analysed for 21 highly-cited journals in Finance. The harmonic mean of the ranks of the 10 RAMs for the 34 highly-cited journals are also presented. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal impact and influence relative to the Harmonic Mean rankings. A linear regression model is used to forecast expert scores on the basis of RAMs that capture journal impact, journal policy, the number of high quality papers, and quantitative information about a journal. The robustness of the rankings is also analysed.

Suggested Citation

  • Chia-Lin Chang & Michael McAleer, 2013. "What Do Experts Know About Forecasting Journal Quality? A Comparison with ISI Research Impact in Finance," KIER Working Papers 851, Kyoto University, Institute of Economic Research.
  • Handle: RePEc:kyo:wpaper:851
    as

    Download full text from publisher

    File URL: http://www.kier.kyoto-u.ac.jp/DP/DP851.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chia-Lin Chang & Michael McAleer, 2013. "Ranking journal quality by harmonic mean of ranks: an application to ISI statistics & probability," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(1), pages 27-53, February.
    2. 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.
    3. Chia-Lin Chang & Esfandiar Maasoumi & Michael McAleer, 2016. "Robust Ranking of Journal Quality: An Application to Economics," Econometric Reviews, Taylor & Francis Journals, vol. 35(1), pages 50-97, January.
    4. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2009. "Expert opinion versus expertise in forecasting," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 334-346.
    5. Chia-Lin Chang & Michael McAleer & Les Oxley, 2011. "What makes a great journal great in the sciences? Which came first, the chicken or the egg?," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(1), pages 17-40, April.
    6. -, 2011. "Information for the authors," Вестник Саратовского государственного социально-экономического университета, CyberLeninka;Государственное образовательное учреждение высшего профессионального образования "Саратовский государственный социально-экономического университет", issue 3, pages 179-180.
    7. Chia‐Lin Chang & Michael McAleer & Les Oxley, 2011. "What Makes A Great Journal Great In Economics? The Singer Not The Song," Journal of Economic Surveys, Wiley Blackwell, vol. 25(2), pages 326-361, April.
    8. Chia-Lin Chang & Michael McAleer & Les Oxley, 2011. "How are journal impact, prestige and article influence related? An application to neuroscience," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2563-2573, January.
    9. repec:spr:scient:v:86:y:2011:i:1:d:10.1007_s11192-010-0205-9 is not listed on IDEAS
    10. -, 2011. "Pro memoria," Экономика региона, CyberLeninka;Федеральное государственное бюджетное учреждение науки «Институт экономики Уральского отделения Российской академии наук», issue 2, pages 252-255.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chia-Lin Chang & Michael Mcaleer, 2014. "Just How Good Are The Top Three Journals In Finance? An Assessment Based On Quantity And Quality Citations," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 1-31.
    2. Tombazos, Christis G. & Dobra, Matthew, 2014. "Formulating research policy on expert advice," European Economic Review, Elsevier, vol. 72(C), pages 166-181.
    3. Chia-Lin Chang & Michael McAleer, 2016. "Quality weighted citations versus total citations in the sciences and social sciences, with an application to finance and accounting," Managerial Finance, Emerald Group Publishing, vol. 42(4), pages 324-337, April.
    4. Chia-Lin Chang & Michael McAleer, 2013. "Ranking Leading Econometrics Journals Using Citations Data from ISI and RePEc," Econometrics, MDPI, Open Access Journal, vol. 1(3), pages 1-19, November.
    5. Chia-Lin Chang & Michael McAleer, 2015. "Bibliometric Rankings of Journals Based on the Thomson Reuters Citations Database," Journal of Reviews on Global Economics, Lifescience Global, vol. 4, pages 120-125.

    More about this item

    Keywords

    Expert scores; Journal quality; RAMs; Impact factor; IFI; C3PO; PI-BETA; STAR; Eigenfactor; Article Influence; h-index; harmonic mean; robustness.;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:kyo:wpaper:851. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ryo Okui). General contact details of provider: http://edirc.repec.org/data/iekyojp.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.