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A Practical Approach to Testing Calibration Strategies

Author

Listed:
  • Yongquan Cao

    (Indiana University)

  • Grey Gordon

    (Indiana University)

Abstract

A calibration strategy tries to match target moments using a model’s parameters. We propose tests for determining whether this is possible. The tests use moments at random parameter draws to assess whether the target moments are similar to the computed ones (evidence of existence) or appear to be outliers (evidence of non-existence). Our experiments show the tests are effective at detecting both existence and non-existence in a non-linear model. Multiple calibration strategies can be quickly tested using just one set of simulated data. Applying our approach to indirect inference allows for the testing of many auxiliary model specifications simultaneously. Code is provided.

Suggested Citation

  • Yongquan Cao & Grey Gordon, 2019. "A Practical Approach to Testing Calibration Strategies," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1165-1182, March.
    • Handle: RePEc:kap:compec:v:53:y:2019:i:3:d:10.1007_s10614-018-9793-x
    DOI: 10.1007/s10614-018-9793-x
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    References listed on IDEAS

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    More about this item

    Keywords

    Calibration; GMM; Indirect inference; Existence; Misspecification; Outlier detection; Data mining;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • F34 - International Economics - - International Finance - - - International Lending and Debt Problems

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