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A solution to the global identification problem in DSGE models

Author

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  • Andrzej Kocięcki
  • Marcin Kolasa
Abstract
We develop an analytical framework to study global identification in structural models with forward-looking expectations. Our identification condition combines the similarity transformation linking the observationally equivalent state space systems with the constraints imposed on them by the model parameters. The key step of solving the identification problem then reduces to finding all roots of a system of polynomial equations. We show how it can be done using the concept of a Gröbner basis and recently developed algorithms to compute it analytically. In contrast to papers relying on numerical search, our approach can prove whether a model is identified or not at a given parameter point, explicitly delivering the complete set of observationally equivalent parameter vectors. We present the solution to the global identification problem for several popular DSGE models.

Suggested Citation

  • Andrzej Kocięcki & Marcin Kolasa, 2023. "A solution to the global identification problem in DSGE models," KAE Working Papers 2023-083, Warsaw School of Economics, Collegium of Economic Analysis.
    • Handle: RePEc:sgh:kaewps:2023083
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    File URL: http://hdl.handle.net/20.500.12182/1142
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    References listed on IDEAS

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    More about this item

    Keywords

    global identification; state space systems; DSGE models; Gröbner basis;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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