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From |
Nick Cox <n.j.cox@durham.ac.uk> |

To |
"'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: RE: RE: st: Unit roots in non linear regression models |

Date |
Fri, 11 Feb 2011 10:41:21 +0000 |

It sounds as if you have a clear idea of what the generating processes might be. Given that, one of the best ways to establish whether you get a problem, and more importantly how big it is, in the nonlinear case is by simulation. Nick n.j.cox@durham.ac.uk Johannes Muck I will try to clarify my question: If we go back to the linear case and look at two random variables, say y and x, both of which are independent I(1) processes so that: y_t = y_t-1 + a_t and x_t = x_t-1 + e_t with a_t and e_t being i.i.d. innovations with mean zero and constant variances. If I run a regression of y_t on x_t this will often result in a significant coefficient for x although there is no relationship between y and x (spurious regression problem). My main question now is whether this problem carries over to the nonlinear case, so that in my nonlinear regression model the coefficients a1 - a4 and b0 - b2 are estimated to have a significant impact on y although in reality they don't. My two questions posted earlier refer to this question. In particular I would like to know: - Whether the spurious regression problem due to integrated time series is also a problem with nonlinear regression models - If the answer is yes: how can I test whether spurious regression is a problem in my nonlinear model? - If spurious regression is a problem in my model: what are possible remedies? * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Unit roots in non linear regression models***From:*Johannes Muck <Johannes.Muck@dice.uni-duesseldorf.de>

**st: RE: Unit roots in non linear regression models***From:*Nick Cox <n.j.cox@durham.ac.uk>

**st: RE: RE: Unit roots in non linear regression models***From:*Nick Cox <n.j.cox@durham.ac.uk>

**AW: RE: RE: st: Unit roots in non linear regression models***From:*Johannes Muck <Johannes.Muck@dice.uni-duesseldorf.de>

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