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Academic ranking scales in economics: Prediction and imputation

Author

Listed:
  • Zharova, Alona
  • Mihoci, Andrija
  • Härdle, Wolfgang Karl

Abstract

Publications are a vital element of any scientist's career. It is not only the number of media outlets but aslo the quality of published research that enters decisions on jobs, salary, tenure, etc. Academic ranking scales in economics and other disciplines are, therefore, widely used in classification, judgment and scientific depth of individual research. These ranking systems are competing, allow for different disciplinary gravity and sometimes give orthogonal results. Here a statistical analysis of the interconnection between Handelsblatt (HB), Research Papers in Economics (RePEc, here RP) and Google Scholar (GS) systems is presented. Quantile regression allows us to successfully predict missing ranking data and to obtain a so-called HB Common Score and to carry out a cross-rankings analysis. Based on the merged ranking data from different data providers, we discuss the ranking systems dependence, analyze the age effect and study the relationship between the research expertise areas and the ranking performance.

Suggested Citation

  • Zharova, Alona & Mihoci, Andrija & Härdle, Wolfgang Karl, 2016. "Academic ranking scales in economics: Prediction and imputation," SFB 649 Discussion Papers 2016-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2016-020
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    References listed on IDEAS

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    8. Klaus Wohlrabe, 2013. "Einige Anmerkungen zum Handelsblatt-Ranking 2013," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(23), pages 79-83, December.
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    More about this item

    Keywords

    scientometrics; ranking; quantile regression; Handelsblatt; RePEc; Google Scholar;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General

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