### Abstract

This paper analyzes the large sample properties of several two step estimators that have recently been suggested for estimating autoregressive moving-average models. As these estimators typically involve generated regressors, the generated regressor literature suggests that, in general, they will be inefficient and their estimated formula standard errors will be inconsistent estimates of the true standard errors. Deriving the covariance matrix of the true disturbances in these models enables consistent estimates of the true standard errors and efficient generalized least squares estimators to be computed.

Original language | English |
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Pages (from-to) | 451-456 |

Number of pages | 6 |

Journal | Mathematics and Computers in Simulation |

Volume | 43 |

Issue number | 3-6 |

Publication status | Published - 1997 Mar |

Externally published | Yes |

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### ASJC Scopus subject areas

- Information Systems and Management
- Control and Systems Engineering
- Applied Mathematics
- Computational Mathematics
- Modelling and Simulation

### Cite this

*Mathematics and Computers in Simulation*,

*43*(3-6), 451-456.

**The properties of some two step estimators of ARMA Models.** / Mckenzie, Colin R.

Research output: Contribution to journal › Article

*Mathematics and Computers in Simulation*, vol. 43, no. 3-6, pp. 451-456.

}

TY - JOUR

T1 - The properties of some two step estimators of ARMA Models

AU - Mckenzie, Colin R

PY - 1997/3

Y1 - 1997/3

N2 - This paper analyzes the large sample properties of several two step estimators that have recently been suggested for estimating autoregressive moving-average models. As these estimators typically involve generated regressors, the generated regressor literature suggests that, in general, they will be inefficient and their estimated formula standard errors will be inconsistent estimates of the true standard errors. Deriving the covariance matrix of the true disturbances in these models enables consistent estimates of the true standard errors and efficient generalized least squares estimators to be computed.

AB - This paper analyzes the large sample properties of several two step estimators that have recently been suggested for estimating autoregressive moving-average models. As these estimators typically involve generated regressors, the generated regressor literature suggests that, in general, they will be inefficient and their estimated formula standard errors will be inconsistent estimates of the true standard errors. Deriving the covariance matrix of the true disturbances in these models enables consistent estimates of the true standard errors and efficient generalized least squares estimators to be computed.

UR - http://www.scopus.com/inward/record.url?scp=0031096270&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031096270&partnerID=8YFLogxK

M3 - Article

VL - 43

SP - 451

EP - 456

JO - Mathematics and Computers in Simulation

JF - Mathematics and Computers in Simulation

SN - 0378-4754

IS - 3-6

ER -