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Back to Basics: Is Statistical Significance all that Matters?

Author

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  • Nektarios A. Michail

    (Central Bank of Cyprus)

  • Constantinos I. Massouras

Abstract

We examine whether statistical significance can convey all the information necessary for the econometrician to judge the performance of his models. We find that in some cases, the t-statistic and the R-squared can be biased due to high correlation between the variables and variables can appear significant even though their correlation with the dependent variable is very low. The solution we propose is a back-to-basics approach: examine correlations between variables and variable variances in order for a correct interpretation of the regression outcome.

Suggested Citation

  • Nektarios A. Michail & Constantinos I. Massouras, 2014. "Back to Basics: Is Statistical Significance all that Matters?," Working Papers 2014-3, Central Bank of Cyprus.
    • Handle: RePEc:cyb:wpaper:2014-3
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    File URL: https://www.centralbank.cy/images/media/pdf/WorkingPaper_2014-3.pdf
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    References listed on IDEAS

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    Cited by:

    1. Nektarios A. Michail & George Thucydides, 2019. "The impact of foreign demand on Cyprus house prices," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 13(2), pages 48-71, December.

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    More about this item

    Keywords

    correlation; statistical significance; hypothesis testing; t test; F test;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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