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New exact ML estimation and inference for a Gaussian MA(1) process

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  • Vougas, Dimitrios V.

Abstract

For a Gaussian MA(1) process, a new exact ML estimator is proposed that avoids the pile-up phenomenon (boundary estimates). Finite sample comparison is undertaken, along with Wald-type inference for an MA unit root or over-differencing (stationarity).

Suggested Citation

  • Vougas, Dimitrios V., 2008. "New exact ML estimation and inference for a Gaussian MA(1) process," Economics Letters, Elsevier, vol. 99(1), pages 172-176, April.
    • Handle: RePEc:eee:ecolet:v:99:y:2008:i:1:p:172-176
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    References listed on IDEAS

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    1. Tanaka, Katsuto & Satchell, S.E., 1989. "Asymptotic Properties of the Maximum-Likelihood and Nonlinear Least-Squares Estimators for Noninvertible Moving Average Models," Econometric Theory, Cambridge University Press, vol. 5(3), pages 333-353, December.
    2. Davis, Richard A. & Dunsmuir, William T.M., 1996. "Maximum Likelihood Estimation for MA(1) Processes with a Root on or near the Unit Circle," Econometric Theory, Cambridge University Press, vol. 12(1), pages 1-29, March.
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    7. Sargan, J D & Bhargava, Alok, 1983. "Maximum Likelihood Estimation of Regression Models with First Order Moving Average Errors When the Root Lies on the Unit Circle," Econometrica, Econometric Society, vol. 51(3), pages 799-820, May.
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    Cited by:

    1. Larsson, Rolf, 2014. "A likelihood ratio type test for invertibility in moving average processes," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 489-501.

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