Finite sample properties of estimators of spatial models with autoregressive, or moving average, disturbances and system feedback

B. Fingleton; J. Le Gallo

Finite sample properties of estimators of spatial models with autoregressive, or moving average, disturbances and system feedback

B. Fingleton, J. Le Gallo

Economics

Research output: Contribution to journal › Article › peer-review

Abstract

This paper extends Kelejian and Prucha's 1998 feasible generalized spatial two-stage least squares (FGS2SLS) estimator to account for endogenous variables due to system feedback, given an autoregressive or a moving average error process. An empirical example illustrating the different estimators is proposed. The finite sample properties of the estimators are investigated by means of Monte-Carlo simulations depending of the sample size, the weights matrix, the presence of cross-equation correlation and the nature of the instruments.

Original language	English
Pages (from-to)	39-62
Number of pages	24
Journal	Annales d'Économie et de Statistique
Issue number	87/88
Publication status	Published - 2007

Keywords

Spatial models
Monte Carlo simulation
weights matrix

Access to Document

http://www.mendeley.com/research/finite-sample-properties-estimators-spatial-models-autoregressive-moving-average-disturbances-system-feedback/

Cite this

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title = "Finite sample properties of estimators of spatial models with autoregressive, or moving average, disturbances and system feedback",

abstract = "This paper extends Kelejian and Prucha's 1998 feasible generalized spatial two-stage least squares (FGS2SLS) estimator to account for endogenous variables due to system feedback, given an autoregressive or a moving average error process. An empirical example illustrating the different estimators is proposed. The finite sample properties of the estimators are investigated by means of Monte-Carlo simulations depending of the sample size, the weights matrix, the presence of cross-equation correlation and the nature of the instruments.",

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AB - This paper extends Kelejian and Prucha's 1998 feasible generalized spatial two-stage least squares (FGS2SLS) estimator to account for endogenous variables due to system feedback, given an autoregressive or a moving average error process. An empirical example illustrating the different estimators is proposed. The finite sample properties of the estimators are investigated by means of Monte-Carlo simulations depending of the sample size, the weights matrix, the presence of cross-equation correlation and the nature of the instruments.

KW - Spatial models

KW - Monte Carlo simulation

KW - weights matrix

UR - http://www.mendeley.com/research/finite-sample-properties-estimators-spatial-models-autoregressive-moving-average-disturbances-system-feedback/

M3 - Article

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EP - 62

JO - Annales d'Économie et de Statistique

JF - Annales d'Économie et de Statistique

SN - 0769-489X

IS - 87/88

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