### Abstract

This paper extends a matrix inverse result of Higgins and presents a new unified double length regression method to calculate the two-step generalised least squares estimators of two types of rational expectations model with current anticipated and unanticipated components. The estimator can be applied directly in most of the standard econometric computer packages such as PC-Give and Microfit.

Original language | English |
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Pages (from-to) | 423-429 |

Number of pages | 7 |

Journal | Oxford Bulletin of Economics and Statistics |

Volume | 58 |

Issue number | 1 |

Publication status | Published - 1 May 1996 |

Externally published | Yes |

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### Cite this

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*Oxford Bulletin of Economics and Statistics*, vol. 58, no. 1, pp. 423-429.

**A double length regression computation method for the 2SGLS estimator of rational expectations model.** / Ma, Yue; Liu, Shuangzhe.

Research output: Contribution to journal › Article

TY - JOUR

T1 - A double length regression computation method for the 2SGLS estimator of rational expectations model

AU - Ma, Yue

AU - Liu, Shuangzhe

PY - 1996/5/1

Y1 - 1996/5/1

N2 - This paper extends a matrix inverse result of Higgins and presents a new unified double length regression method to calculate the two-step generalised least squares estimators of two types of rational expectations model with current anticipated and unanticipated components. The estimator can be applied directly in most of the standard econometric computer packages such as PC-Give and Microfit.

AB - This paper extends a matrix inverse result of Higgins and presents a new unified double length regression method to calculate the two-step generalised least squares estimators of two types of rational expectations model with current anticipated and unanticipated components. The estimator can be applied directly in most of the standard econometric computer packages such as PC-Give and Microfit.

UR - http://www.scopus.com/inward/record.url?scp=17644386595&partnerID=8YFLogxK

M3 - Article

VL - 58

SP - 423

EP - 429

JO - Oxford Bulletin of Economics and Statistics

JF - Oxford Bulletin of Economics and Statistics

SN - 0305-9049

IS - 1

ER -