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The small-sample distribution of par...

Das, Debabrata.

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The small-sample distribution of parameter estimators in a spatial ARAR(1,1) model: A Monte Carlo study.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	The small-sample distribution of parameter estimators in a spatial ARAR(1,1) model: A Monte Carlo study./
作者:	Das, Debabrata.
面頁冊數:	326 p.
附註:	Co-Chairs: Harry Kelejian; Ingmar Prucha.
Contained By:	Dissertation Abstracts International61-04B.
標題:	Economics, General. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9967888
ISBN:	0599725451

The small-sample distribution of parameter estimators in a spatial ARAR(1,1) model: A Monte Carlo study.
Das, Debabrata.

The small-sample distribution of parameter estimators in a spatial ARAR(1,1) model: A Monte Carlo study. - 326 p.

Co-Chairs: Harry Kelejian; Ingmar Prucha.

Thesis (Ph.D.)--University of Maryland College Park, 2000.

This thesis studies the small sample distribution of the (quasi) ML estimator and the FGS2SLS estimator of parameters in a spatial ARAR(1,1) model. In order to compare the small sample distribution of these estimators a Monte Carlo study is performed. The FGS2SLS estimator was proposed by Kelejian and Prucha (1998) as an alternative to the ML estimator because the FGS2SLS is consistent and asymptotically normal and computationally simple. However, from a practical point of view, one needs to explore the small sample distribution of this estimator. Given the small sample efficiency of ML estimators in a number of econometric models, one may expect the QML estimator to be reasonably precise in the model we have considered. The results from the Monte Carlo study suggest that the small sample distribution of the FGS2SLS estimator is very similar to that of the QML estimator. Therefore, the FGS2SLS estimator not only has a major computational advantage over the QML estimator, but also has a distribution similar to QML estimator in small samples.

ISBN: 0599725451Subjects--Topical Terms:

1017424
Economics, General.

The small-sample distribution of parameter estimators in a spatial ARAR(1,1) model: A Monte Carlo study.
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500 $a Source: Dissertation Abstracts International, Volume: 61-04, Section: B, page: 2020.
502 $a Thesis (Ph.D.)--University of Maryland College Park, 2000.
520 $a This thesis studies the small sample distribution of the (quasi) ML estimator and the FGS2SLS estimator of parameters in a spatial ARAR(1,1) model. In order to compare the small sample distribution of these estimators a Monte Carlo study is performed. The FGS2SLS estimator was proposed by Kelejian and Prucha (1998) as an alternative to the ML estimator because the FGS2SLS is consistent and asymptotically normal and computationally simple. However, from a practical point of view, one needs to explore the small sample distribution of this estimator. Given the small sample efficiency of ML estimators in a number of econometric models, one may expect the QML estimator to be reasonably precise in the model we have considered. The results from the Monte Carlo study suggest that the small sample distribution of the FGS2SLS estimator is very similar to that of the QML estimator. Therefore, the FGS2SLS estimator not only has a major computational advantage over the QML estimator, but also has a distribution similar to QML estimator in small samples.
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