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Estimating nonlinear DSGE models with moments based methods


  • Sergey, Ivashchenko


This article suggests the new approach to an approximation of nonlinear DSGE models moments. This approach is fast and accurate enough to use it for an estimation of nonlinear DSGE models. The small financial DSGE model is repeatedly estimated by several modifications of suggested approach. Approximations of moments are close to the results of large sample Monte Carlo estimation. Quality of parameters estimation with suggested approach is close to the Central Difference Kalman Filter (the CDKF) based. At the same time suggested approach is much faster.

Suggested Citation

  • Sergey, Ivashchenko, 2014. "Estimating nonlinear DSGE models with moments based methods," Dynare Working Papers 32, CEPREMAP.
  • Handle: RePEc:cpm:dynare:032

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    References listed on IDEAS

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    More about this item


    DSGE; DSGE-VAR; GMM; nonlinear estimation;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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