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On the Use of Enumeration for Investigating the Performance of Hypothesis Tests for Economic Models with a Discrete Response Variable

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  • Simon Peters
  • Andrew Chesher

Abstract

This article notes that it is now practical to use the method of enumeration to analyse the performance of estimators and hypothesis tests of fully parametric binary data models. The general method is presented and then employed to investigate the power performance of a common misspecification test for the Probit model. The advantages, disadvantages and limitations of enumeration compared with standard Monte Carlo simulation are then discussed. Finally, an example from experimental economics is used to demonstrate that the methodology can also be used in small empirical studies.

Suggested Citation

  • Simon Peters & Andrew Chesher, 2000. "On the Use of Enumeration for Investigating the Performance of Hypothesis Tests for Economic Models with a Discrete Response Variable," Computational Economics, Springer;Society for Computational Economics, vol. 15(3), pages 273-289, June.
    • Handle: RePEc:kap:compec:v:15:y:2000:i:3:p:273-289
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    Cited by:

    1. Eleni Aristodemou, 2022. "Strictly log-concave probability distributions in discrete response models," University of Cyprus Working Papers in Economics 06-2022, University of Cyprus Department of Economics.
    2. Aristodemou, Eleni, 2023. "Strictly log-concave probability distributions in discrete response models," Statistics & Probability Letters, Elsevier, vol. 193(C).

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