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Some exact and inexact linear rational expectation models in vector autoregressive models

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  • Swensen, Anders Rygh

Abstract

In this paper we consider maximum likelihood estimation in some exact and inexact linear rational expectation (LRE) models. The implications of the two models on the coefficients of the vector autoregressive (VAR) model are spelled out. The inexact version is more complicated and possible simplification of the resulting constrained optimization problem is discussed.

Suggested Citation

  • Swensen, Anders Rygh, 2014. "Some exact and inexact linear rational expectation models in vector autoregressive models," Economics Letters, Elsevier, vol. 123(2), pages 216-219.
  • Handle: RePEc:eee:ecolet:v:123:y:2014:i:2:p:216-219
    DOI: 10.1016/j.econlet.2014.02.015
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    References listed on IDEAS

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    1. Boug, Pål & Cappelen, Adne & Swensen, Anders Rygh, 2010. "The new Keynesian Phillips curve revisited," Journal of Economic Dynamics and Control, Elsevier, vol. 34(5), pages 858-874, May.
    2. Luca Fanelli, 2008. "Testing the New Keynesian Phillips Curve Through Vector Autoregressive Models: Results from the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(1), pages 53-66, February.
    3. Søren Johansen & Anders Rygh Swensen, 2004. "More on testing exact rational expectations in cointegrated vector autoregressive models: Restricted constant and linear term," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 389-397, December.
    4. Johansen, Soren & Swensen, Anders Rygh, 1999. "Testing exact rational expectations in cointegrated vector autoregressive models," Journal of Econometrics, Elsevier, vol. 93(1), pages 73-91, November.
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    More about this item

    Keywords

    Vector autoregressive models; Exact rational expectations; Inexact rational expectations; Maximum likelihood estimation;
    All these keywords.

    JEL classification:

    • 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
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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