The Approximate Moments of the Least Squares Estimator for the Stationary Autoregressive Model Under a General Error Distribution

I derive the approximate bias and mean squared error of the least squares estimator of the autoregressive coefficient in a stationary first-order dynamic regression model, with or without an intercept, under a general error distribution. It is shown that the effects of nonnormality on the approximate moments of the least squares estimator come into play through the skewness and kurtosis coefficients of the nonnormal error distribution

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Year of publication:	2016
Authors:	Bao, Yong
Publisher:	[2016]: [S.l.] : SSRN
Subject:	Autokorrelation \| Autocorrelation \| Kleinste-Quadrate-Methode \| Least squares method \| Schätztheorie \| Estimation theory
Description of contents:	Abstract [papers.ssrn.com]

Extent:	1 Online-Ressource
Type of publication:	Book / Working Paper
Language:	English
Notes:	In: Econometric Theory, Vol. 23, No. 5, 2007, DOI: org/10.1017/S0266466607070405 Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 25, 2007 erstellt Volltext nicht verfügbar
Source:	ECONIS - Online Catalogue of the ZBW

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