Full Maximum Likelihood Estimation of Second-Order Autoregressive Error Models
Charles Beach and
James MacKinnon
Working Paper from Economics Department, Queen's University
Abstract:
This paper develops a technique for estimating linear models with second-order autoregressive errors, which utilizes the full set of observations, and explicitly constrains the estimates of the error process to satisfy a priori stationarity conditions. A nonlinear solution technique which is new to econometrics and works very efficiently is put forward as part of the estimating procedure. Empirical results are presented which emphasize the importance of utilizing the full set of observations and the associated stationarity restrictions.
Pages: 20
Date: 1977
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Published in Journal of Econometrics, 7, 1978
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Journal Article: Full maximum likelihood estimation of second- order autoregressive error models (1978) 
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Persistent link: https://EconPapers.repec.org/RePEc:qed:wpaper:259
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