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Generalized Method of Moment and Indirect Estimation of the ARASMA Model

Author

Listed:
  • Brännäs, Kurt

    (Department of Economics, Umeå University)

  • de Luna, Xavier

    (University College London)

Abstract

Estimation in nonlinear time series models has mainly been performed by least squares or maximum likelihood (ML) methods. The paper suggests and studies the performance of generalized method of moments (GMM) and indirect estimators for the autoregressive asymmetric moving average model. Both approaches are easy to implement and perform well numerically. In a Monte Carlo study it is found that the MSE properties of GMM are close to those of ML. The indirect estimator performs poorly in this respect. On the other hand, the three estimation techniques lead to fairly similar power functions for a linearity test.

Suggested Citation

  • Brännäs, Kurt & de Luna, Xavier, 1997. "Generalized Method of Moment and Indirect Estimation of the ARASMA Model," Umeå Economic Studies 436, Umeå University, Department of Economics.
    • Handle: RePEc:hhs:umnees:0436
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    More about this item

    Keywords

    Estimation; Nonlinearity Test; Small Sample Properties; Time Series.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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