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Communicating quantitative information: tables vs graphs

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  • Klein, Torsten L.

Abstract

In applied statistics and computational econometrics a key task for researchers is to bring the sizable but unstructured body of numeric evidence, for example from Monte Carlo simulation, in a form ready for introducing to scientific dialog. At their disposal they find established means of arrangement: narrative text, tables, graphs. Employing classical principles of communication to evaluate their suitability graphical devices seem optimal. They absorb large quantities of data, and organize content into a productive tool. Graphs confirm the advantage when put to work in a standard simulation exercise. However, theory and application contrast with the norm observed in peer-reviewed journals – by a wide margin and with considerable persistency researchers prefer tables.

Suggested Citation

  • Klein, Torsten L., 2014. "Communicating quantitative information: tables vs graphs," MPRA Paper 60514, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:60514
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    File URL: https://mpra.ub.uni-muenchen.de/60514/1/MPRA_paper_60514.pdf
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    References listed on IDEAS

    as
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    6. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    7. Klein, Torsten L., 2014. "The small multiple in econometrics – a redesign," MPRA Paper 60521, University Library of Munich, Germany.
    8. Carlo V. Fiorio & Vassilis A. Hajivassiliou & Peter C. B. Phillips, 2010. "Bimodal t-ratios: the impact of thick tails on inference," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 271-289, July.
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    Cited by:

    1. Klein, Torsten L., 2014. "The small multiple in econometrics – a redesign," MPRA Paper 60521, University Library of Munich, Germany.

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    More about this item

    Keywords

    econometric and statistical methods; Monte Carlo; bivariate probit model; exogeneity testing; modes of communication; data visualization; economics of science;
    All these keywords.

    JEL classification:

    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Y10 - Miscellaneous Categories - - Data: Tables and Charts - - - Data: Tables and Charts

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