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Higher-Order Perturbation Solutions to Dynamic, Discrete-Time Rational Expectations Models: Methods and an Application to Optimal Monetary Policy

Author

Listed:
  • Eric Swanson
  • Gary Anderson
  • Andrew Levin

Abstract

We present an algorithm and software routines for computing nth-order approximate solutions to dynamic, discrete-time rational expectations models around a nonstochastic steady state. We apply these routines to investigate the optimal monetary policy with commitment in an optimizing-agent model with nominal price rigidities, subject to a fiscal policy that is stochastic, suboptimal, and exogenous to the central bank

Suggested Citation

  • Eric Swanson & Gary Anderson & Andrew Levin, 2005. "Higher-Order Perturbation Solutions to Dynamic, Discrete-Time Rational Expectations Models: Methods and an Application to Optimal Monetary Policy," Computing in Economics and Finance 2005 146, Society for Computational Economics.
    • Handle: RePEc:sce:scecf5:146
    as

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    More about this item

    Keywords

    perturbation methods; Mathematica; nth order; optimal monetary policy;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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