A Robust and Efficient Method for Solving Nonlinear Rational Expectations Models

September 1, 1996

Preview Citation

Format: Chicago

Michel Juillard, and Douglas Laxton. A Robust and Efficient Method for Solving Nonlinear Rational Expectations Models, (USA: International Monetary Fund, 1996) accessed December 3, 2024

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

The development and use of forward-looking macro models in policymaking institutions has proceeded at a pace much slower than predicted in the early 1980s. An important reason is that researchers have not had access to robust and efficient solution techniques for solving nonlinear forward-looking models. This paper discusses the properties of a new algorithm that is used for solving MULTIMOD, the IMF’s multicountry model of the world economy. This algorithm is considerably faster and much less prone to simulation failures than to traditional algorithms and can also be used to solve individual country models of the same size.

Subject: Economic theory, Exchange rates, Financial services, Foreign exchange, Long term interest rates, Rational expectations, Short term interest rates

Keywords: Exchange rates, Fair-Taylor algorithm, F-T algorithm, L-B-J algorithm, L-B-J method, L-B-J result, Long term interest rates, Rational expectations, Short term interest rates, WP

Publication Details

Pages:

30
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 1996/106
Stock No:

WPIEA1061996
ISBN:

9781451947144
ISSN:

1018-5941

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