Nonlinear regression for unit root models with autoregressive errors

This paper shows that the nonlinear least squares estimator for unit root models has the limiting distribution free of nuisance parameters and is more efficient than the augmented Dickey-Fuller estimator when the sum of coefficients for lagged variables is negative.

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Year of publication:	2008
Authors:	Kim, Chang Sik ; Kim, In-Moo
Published in:	Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 100.2008, 3, p. 326-329
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005355766