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

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  • 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.

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Bibliographic Info

Paper provided by Kyoto University, Institute of Economic Research in its series KIER Working Papers with number 851.

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Length: 43pages
Date of creation: Mar 2013
Date of revision:
Handle: RePEc:kyo:wpaper:851

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

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References

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  1. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2008. "Expert opinion versus expertise in forecasting," Econometric Institute Research Papers EI 2008-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Michael McAleer & Chia-Lin Chang, 2012. "Ranking Journal Quality by Harmonic Mean of Ranks:An Application to ISI Statistics & Probability," KIER Working Papers 819, Kyoto University, Institute of Economic Research.
  3. Chia-Lin Chang & Michael McAleer & Les Oxley, 2011. "How are Journal Impact, Prestige and Article Influence Related? An Application to Neuroscience," Documentos del Instituto Complutense de Análisis Económico 2011-25, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
  4. Chia-Lin Chang & Michael McAleer & Les Oxley, 2010. "Great Expectatrics: Great Papers, Great Journals, Great Econometrics," KIER Working Papers 714, Kyoto University, Institute of Economic Research.
  5. Chia-Lin Chang & Michael McAleer & Les Oxley, 2010. "What Makes a Great Journal Great in Economics? The Singer Not the Song," Working Papers in Economics 10/43, University of Canterbury, Department of Economics and Finance.
  6. Chia-Lin Chang & Esfandiar Maasoumi & Michael McAleer, 2012. "Robust Ranking of Journal Quality: An Application to Economics," Documentos del Instituto Complutense de Análisis Económico 2012-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, revised Mar 2012.
  7. Chia-Lin Chang & Michael McAleer & Les Oxley, 2010. "What Makes a Great Journal Great in the Sciences? Which Came First, the Chicken or the Egg?," KIER Working Papers 746, Kyoto University, Institute of Economic Research.
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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," Documentos del Instituto Complutense de Análisis Económico 2014-10, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
  2. Chia-Lin Chang & Michael McAleer, 2014. "Ranking Leading Econometrics Journals Using Citations Data from ISI and RePEc," Working Papers in Economics 14/01, University of Canterbury, Department of Economics and Finance.

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