1979
DOI: 10.2307/2335241
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Maximum Likelihood Estimation of Regression Models with Autoregressive- Moving Average Disturbances

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Cited by 82 publications
(68 citation statements)
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“…In some cases such as in Harvey and Phillips (1979) and Hannan (1976) this formulation has computational or theoretical advantages. More interestingly, unobserved components models such as Nerlove (1971), Pagan (1975), and Engle (1979a) can be formulated and estimated in this framework.…”
Section: General Formulation Of the Modelmentioning
confidence: 99%
“…In some cases such as in Harvey and Phillips (1979) and Hannan (1976) this formulation has computational or theoretical advantages. More interestingly, unobserved components models such as Nerlove (1971), Pagan (1975), and Engle (1979a) can be formulated and estimated in this framework.…”
Section: General Formulation Of the Modelmentioning
confidence: 99%
“…Since the trend and its slope are not stationary, it is not possible to estimate their variances in the same way. One alternative is to follow the proposal of Harvey and Phillips (1979), which considers extremely large numbers, with which the variance and covariance matrix approaches its exact value after several iterations. It is important to highlight that the state variables (trend and cycle) are not sensitive to these specifications.…”
Section: Initial Valuesmentioning
confidence: 99%
“…However, the work started at that time for obtaining a procedure for Kalman Filter in the field of statistics. Likewise the work of [16], [17] and [18] decided that the Kalman Filter have a great importance for statistical applications in econometrics, for example forecasting of time series data and other economic properties. The forecasts of the state space models are obtained by the Kalman filtering technique.…”
Section: Introductionmentioning
confidence: 99%