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A Log-linear Homotopy Approach to Initialize the Parameterized Expectations Algorithm

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Abstract

In this paper I present a proposal to obtain appropriate initial conditions when solving general equilibrium rational expectations models with the Parameterized Expectations Algorithm. The proposal is based on a log-linear approximation to the model under study, so that it can be though of as a particular variant of the homotopy approach.The main advantages of the proposal are: i. it guarantees the ergodicity of the initial time series used as an input to the Parameterized Expectations algorithm; ii. it performs well as regards speed of convergence when compared to some homotopy alternatives; iii. it is easy to implement. The claimed advantages are successfully illustrated in the framework of the Cooley and Hansen (1989) model with indivisible labor and money demand motivated via a cash-in-advance constraint, as compared to a procedure based on the standard implementation of homotopy principles.

Suggested Citation

  • Javier J. Pérez, 2001. "A Log-linear Homotopy Approach to Initialize the Parameterized Expectations Algorithm," Economic Working Papers at Centro de Estudios Andaluces E2001/02, Centro de Estudios Andaluces.
    • Handle: RePEc:cea:doctra:e2001_02
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    1. Albert Marcet & David A. Marshall, 1994. "Solving nonlinear rational expectations models by parameterized expectations: convergence to stationary solutions," Working Paper Series, Macroeconomic Issues 94-20, Federal Reserve Bank of Chicago.
    2. Collard, Fabrice & Juillard, Michel, 2001. "A Higher-Order Taylor Expansion Approach to Simulation of Stochastic Forward-Looking Models with an Application to a Nonlinear Phillips Curve Model," Computational Economics, Springer;Society for Computational Economics, vol. 17(2-3), pages 125-139, June.
    3. Duffy, John & McNelis, Paul D., 2001. "Approximating and simulating the stochastic growth model: Parameterized expectations, neural networks, and the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1273-1303, September.
    4. Albert Marcet, 1991. "Simulation analysis of dynamic stochastic models: Applications to theory and estimation," Economics Working Papers 6, Department of Economics and Business, Universitat Pompeu Fabra.
    5. Albert Marcet & Guido Lorenzoni, 1998. "Parameterized expectations approach; Some practical issues," Economics Working Papers 296, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Jensen, Mark J, 1997. "A Homotopy Approach to Solving Nonlinear Rational Expectation Problems," Computational Economics, Springer;Society for Computational Economics, vol. 10(1), pages 47-65, February.
    7. Eaves, B. Curtis & Schmedders, Karl, 1999. "General equilibrium models and homotopy methods," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1249-1279, September.
    8. Marimon, Ramon & Scott, Andrew (ed.), 1999. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780198294979.
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    Cited by:

    1. Antonio Morales & Pablo Brañas Garza, 2003. "Computational Errors in Guessing Games1," Economic Working Papers at Centro de Estudios Andaluces E2003/11, Centro de Estudios Andaluces.
    2. Paul Pichler, 2005. "Evaluating Approximate Equilibria of Dynamic Economic Models," Vienna Economics Papers 0510, University of Vienna, Department of Economics.
    3. Pérez, Javier J. & Sánchez, A. Jesús, 2009. "Alternatives to initialize the Parameterized Expectations Algorithm," Economics Letters, Elsevier, vol. 102(2), pages 116-118, February.

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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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