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Local Identification in DSGE Models

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  • Nikolay Iskrev

Abstract

The issue of parameter identification arises whenever structural models are estimated. This paper develops a simple condition for local identification in linearized DSGE models. The condition is necessary and sufficient for identification with likelihood-based methods under normality, or with limited information methods that utilize only second moments of the data. Using the methodology developed in the paper researchers can answer, prior to estimation, the following questions: which parameters are locally identified and which are not; is the identification failure due to data limitations, such as a lack of observations for some variables, or is it intrinsic to the structure of the model.

Suggested Citation

  • Nikolay Iskrev, 2009. "Local Identification in DSGE Models," Working Papers w200907, Banco de Portugal, Economics and Research Department.
  • Handle: RePEc:ptu:wpaper:w200907
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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