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Comparing Indirect Inference and Likelihood testing: asymptotic and small sample results

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  • Minford, Patrick
  • Wickens, Michael R.
  • Meenagh, David
  • Xu, Yongdeng

Abstract

Indirect Inference has been found to have much greater power than the Likelihood Ratio in small samples for testing DSGE models. We look at asymptotic and large sample properties of these tests to understand why this might be the case. We find that the power of the LR test is undermined when re-estimation of the error parameters is permitted; this offsets the effect of the falseness of structural parameters on the overall forecast error. Even when the two tests are done on a like-for-like basis Indirect Inference has more power because it uses the distribution restricted by the DSGE model being tested.

Suggested Citation

  • Minford, Patrick & Wickens, Michael R. & Meenagh, David & Xu, Yongdeng, 2015. "Comparing Indirect Inference and Likelihood testing: asymptotic and small sample results," CEPR Discussion Papers 10765, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:10765
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    More about this item

    Keywords

    Dsge model; Error processes; indirect inference; Likelihood ratio; Structural parameters;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models

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