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Teaching Size and Power Properties of Hypothesis Tests Through Simulations

Author

Listed:
  • Taşpınar Süleyman

    (Economics Program, Queens College, The City University of New York, USA)

  • Doğan Osman

    (Istanbul Ulasim A.S., Project Department, Istanbul, Turkey)

Abstract

In this study, we review the graphical methods suggested in Davidson and MacKinnon (Davidson, Russell, and James G. MacKinnon. 1998. “Graphical Methods for Investigating the Size and Power of Hypothesis Tests.” The Manchester School 66 (1): 1–26.) that can be used to investigate size and power properties of hypothesis tests for undergraduate and graduate econometrics courses. These methods can be used to assess finite sample properties of various hypothesis tests through simulation studies. In addition, these methods can be effectively used in classrooms to reinforce students’ understanding of basic hypothesis testing concepts such as Type I error, Type II error, size, power, p-values and under-or-over-sized tests. We illustrate the procedural aspects of these graphical methods through Monte Carlo experiments, and provide the implementation codes written in Matlab and R for the classroom applications.

Suggested Citation

  • Taşpınar Süleyman & Doğan Osman, 2017. "Teaching Size and Power Properties of Hypothesis Tests Through Simulations," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-15, January.
    • Handle: RePEc:bpj:jecome:v:6:y:2017:i:1:p:15:n:7
    DOI: 10.1515/jem-2015-0014
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    References listed on IDEAS

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    1. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
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    Keywords

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: 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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