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Computing second-order-accurate solutions for rational expectation models using linear solution methods

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  • Sutherland, Alan
  • Lombardo, Giovanni

Abstract

This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. The result is a state-space representation for the realized values of the variables of the model. This state-space representation can easily be used to compute impulse responses as well as conditional and unconditional forecasts. JEL Classification: C63, E0

Suggested Citation

  • Sutherland, Alan & Lombardo, Giovanni, 2005. "Computing second-order-accurate solutions for rational expectation models using linear solution methods," Working Paper Series 487, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:2005487
    Note: 656519
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    References listed on IDEAS

    as
    1. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
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    More about this item

    Keywords

    Second order approximation; Solution method for rational expectation models;

    JEL classification:

    • E63 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Comparative or Joint Analysis of Fiscal and Monetary Policy; Stabilization; Treasury Policy
    • E0 - Macroeconomics and Monetary Economics - - General

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