Authors: Arnold, Matthias
Title: GMM estimation of the autoregressive parameter in a spatial autoregressive error model using regression residuals
Language (ISO): en
Abstract: This paper suggests an improved GMM estimator for the autoregressive parameter of a spatial autoregressive error model by taking into account that unobservable regression disturbances are different from observable regression residuals. Although this difference decreases in large samples, it is important in small samples. Monte Carlo simulations show that the bias can be reduced by 65 − 80% compared to a GMM estimator that neglects the difference between disturbances and residuals. The mean squared error is smaller, too.
Subject Headings: Generalized method of moments estimator
GMM estimation
Regression residuals
Spatial autoregression
URI: http://hdl.handle.net/2003/24712
http://dx.doi.org/10.17877/DE290R-8890
Issue Date: 2007-09-05T12:55:54Z
Appears in Collections:Sonderforschungsbereich (SFB) 475

Files in This Item:
File Description SizeFormat 
TR_25-arnold.pdfDNB141.78 kBAdobe PDFView/Open


This item is protected by original copyright



All resources in the repository are protected by copyright.