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Solving Non-linear Rational Expectations Models By Eigenvalue-Eigenvector Decompositions

Author

Listed:
  • Alfonso Novales
  • Emilio Dominguez
  • Javier J. Perez
  • Jesus Ruiz

Programming Language

Matlab

Abstract

This code supports the text in Alfonso Novales, Emilio Dominguez, Javier J. Perez and Jesus Ruiz, Solving Non-linear Rational Expectations Models By Eigenvalue-Eigenvector Decompositions, in Ramon Marimon and Andrew Scott (eds), Computational Methods for the Study of Dynamic Economies, Chapter 4, Oxford University Press. This chapter deals with a solution to rational expectations models, which is based on eigenvalue/eigenvector decompositions. The methods gives an exact solution in th case of linear expectations and an approximate solution in the case of nonlinear models. The programs execute the calculations of sections 4 and 6 of the chapter.

Suggested Citation

  • Alfonso Novales & Emilio Dominguez & Javier J. Perez & Jesus Ruiz, 1998. "Solving Non-linear Rational Expectations Models By Eigenvalue-Eigenvector Decompositions," QM&RBC Codes 124, Quantitative Macroeconomics & Real Business Cycles.
    • Handle: RePEc:dge:qmrbcd:124
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    File URL: https://dge.repec.org/codes/marimon-scott/Novales/
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    Cited by:

    1. Mr. Christopher S Adam & Mr. Edward F Buffie, 2020. "The Minimum Wage Puzzle in Less Developed Countries: Reconciling Theory and Evidence," IMF Working Papers 2020/023, International Monetary Fund.
    2. Jaime Alonso-Carrera & María Jesús Freire-Serén & Baltasar Manzano, 2004. "Rentabilidad social de la inversión pública española en infraestructuras," Hacienda Pública Española, IEF, vol. 170(3), pages 81-103, september.

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    Keywords

    Matlab;

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