When are two step estimators efficient?

Michael McAleer, Colin R Mckenzie

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

Kruskal’s theorem is used to provide simple and elegant alternative derivations of the efficiency of some two step estimators (2SE) for models containing anticipated and unanticipated variables. Several new results are established: 2SE is not efficient for a structural equation with current and lagged values of both anticipated and unanticipated variables; 2SE is always efficient for the parameter associated with the current unanticipated variable, and for the parameter associated with the lagged unanticipated variable if there is no lagged dependent variable in the expectations equation; the inclusion of additional regressors in the structural equation and contemporaneous correlation of the structural and expectations errors can both be analysed in a straightforward manner; the single-equation generalized least squares estimator can be as efficient as the systems maximum likelihood estimator.

Original languageEnglish
Pages (from-to)235-252
Number of pages18
JournalEconometric Reviews
Volume10
Issue number2
DOIs
Publication statusPublished - 1991 Jan 1
Externally publishedYes

Fingerprint

Two-step estimator
Structural equations
Generalized least squares
Inclusion
Maximum likelihood estimator
Contemporaneous correlation
Least squares estimator

Keywords

  • generated regressors
  • Kruskal's theorem
  • rational expectations models
  • two step estimation

ASJC Scopus subject areas

  • Economics and Econometrics

Cite this

When are two step estimators efficient? / McAleer, Michael; Mckenzie, Colin R.

In: Econometric Reviews, Vol. 10, No. 2, 01.01.1991, p. 235-252.

Research output: Contribution to journalArticle

McAleer, Michael ; Mckenzie, Colin R. / When are two step estimators efficient?. In: Econometric Reviews. 1991 ; Vol. 10, No. 2. pp. 235-252.
@article{3cc21ebbe26f402a8bd44713ed3c6589,
title = "When are two step estimators efficient?",
abstract = "Kruskal’s theorem is used to provide simple and elegant alternative derivations of the efficiency of some two step estimators (2SE) for models containing anticipated and unanticipated variables. Several new results are established: 2SE is not efficient for a structural equation with current and lagged values of both anticipated and unanticipated variables; 2SE is always efficient for the parameter associated with the current unanticipated variable, and for the parameter associated with the lagged unanticipated variable if there is no lagged dependent variable in the expectations equation; the inclusion of additional regressors in the structural equation and contemporaneous correlation of the structural and expectations errors can both be analysed in a straightforward manner; the single-equation generalized least squares estimator can be as efficient as the systems maximum likelihood estimator.",
keywords = "generated regressors, Kruskal's theorem, rational expectations models, two step estimation",
author = "Michael McAleer and Mckenzie, {Colin R}",
year = "1991",
month = "1",
day = "1",
doi = "10.1080/07474939108800206",
language = "English",
volume = "10",
pages = "235--252",
journal = "Econometric Reviews",
issn = "0747-4938",
publisher = "Taylor and Francis Ltd.",
number = "2",

}

TY - JOUR

T1 - When are two step estimators efficient?

AU - McAleer, Michael

AU - Mckenzie, Colin R

PY - 1991/1/1

Y1 - 1991/1/1

N2 - Kruskal’s theorem is used to provide simple and elegant alternative derivations of the efficiency of some two step estimators (2SE) for models containing anticipated and unanticipated variables. Several new results are established: 2SE is not efficient for a structural equation with current and lagged values of both anticipated and unanticipated variables; 2SE is always efficient for the parameter associated with the current unanticipated variable, and for the parameter associated with the lagged unanticipated variable if there is no lagged dependent variable in the expectations equation; the inclusion of additional regressors in the structural equation and contemporaneous correlation of the structural and expectations errors can both be analysed in a straightforward manner; the single-equation generalized least squares estimator can be as efficient as the systems maximum likelihood estimator.

AB - Kruskal’s theorem is used to provide simple and elegant alternative derivations of the efficiency of some two step estimators (2SE) for models containing anticipated and unanticipated variables. Several new results are established: 2SE is not efficient for a structural equation with current and lagged values of both anticipated and unanticipated variables; 2SE is always efficient for the parameter associated with the current unanticipated variable, and for the parameter associated with the lagged unanticipated variable if there is no lagged dependent variable in the expectations equation; the inclusion of additional regressors in the structural equation and contemporaneous correlation of the structural and expectations errors can both be analysed in a straightforward manner; the single-equation generalized least squares estimator can be as efficient as the systems maximum likelihood estimator.

KW - generated regressors

KW - Kruskal's theorem

KW - rational expectations models

KW - two step estimation

UR - http://www.scopus.com/inward/record.url?scp=0010714232&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0010714232&partnerID=8YFLogxK

U2 - 10.1080/07474939108800206

DO - 10.1080/07474939108800206

M3 - Article

VL - 10

SP - 235

EP - 252

JO - Econometric Reviews

JF - Econometric Reviews

SN - 0747-4938

IS - 2

ER -