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Testing DSGE Models by Indirect Inference: a Survey of Recent Findings

Author

Listed:
  • David Meenagh

    () (Cardiff University)

  • Patrick Minford

    () (Cardiff University
    CEPR)

  • Michael Wickens

    (Cardiff University
    CEPR
    University of York)

  • Yongdeng Xu

    () (Cardiff University)

Abstract

We review recent findings in the application of indirect inference to DSGE models. We show that researchers should tailor the power of their test to the model under investigation in order to achieve a balance between high power and finding a robust model; this will involve choosing only a limited number of variables on whose behaviour they should focus. Also recent work reveals that it makes little difference which these variables are or how their behaviour is measured whether via a VAR, IRFs or moments. We also review identification issues, how to test part of a model and whether alternative evaluation methods such as forecasting or likelihood ratio tests are potentially helpful.

Suggested Citation

  • David Meenagh & Patrick Minford & Michael Wickens & Yongdeng Xu, 2019. "Testing DSGE Models by Indirect Inference: a Survey of Recent Findings," Open Economies Review, Springer, vol. 30(3), pages 593-620, July.
  • Handle: RePEc:kap:openec:v:30:y:2019:i:3:d:10.1007_s11079-019-09526-w
    DOI: 10.1007/s11079-019-09526-w
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    Cited by:

    1. Lucy Minford & David Meenagh, 2020. "Supply-Side Policy and Economic Growth: A Case Study of the UK," Open Economies Review, Springer, vol. 31(1), pages 159-193, February.
    2. Patrick Minford & Zhirong Ou & Zheyi Zhu, 2021. "Can a small New Keynesian model of the world economy with risk‐pooling match the facts?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1993-2021, April.
    3. Xiaoliang Yang & Patrick Minford & David Meenagh, 2021. "Inequality and Economic Growth in the UK," Open Economies Review, Springer, vol. 32(1), pages 37-69, February.

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    More about this item

    Keywords

    Pseudo-true inference; DSGE models; Indirect inference; Wald tests; Likelihood ratio tests; robustness;
    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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