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From | Beat Hintermann <b.hintermann@unibas.ch> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: RE: Cointegration analysis including exogenous variables |
Date | Wed, 09 Mar 2011 10:00:26 +0100 |
Dear Syedthank you very much for your offer to estimate it in Eviews. I might take you up on it, but only if I don't manage to estimate it myself. I have access to Eviews in our finance lab, I've just never used it. But now that I know that Eviews allows for exogenous variables, I might give it a shot. If I can't get it done I might give you another shout.
Thanks again, Beat On 08.03.2011 17:24, Syed Basher wrote:
This may not be relevant for Stata users, but the problem you described is easy to handle in other packages. For example, Eviews has an option to include exogenous variables in cointegrating model. If you do not mind sharing your data, I can attempt to estimate it for you in Eviews. Syed Basher Doha, Qatar. ----- Original Message ---- From: Beat Hintermann<b.hintermann@unibas.ch> To: statalist@hsphsun2.harvard.edu Sent: Tue, March 8, 2011 6:53:13 PM Subject: Re: st: RE: Cointegration analysis including exogenous variables i get your point. but i'm working with monthly weather measures, not long-term climate trends. i think it's safe to say that monthly heating-degree days and precipitation events are exogenous to today's fuel and electricity prices. exogenous or not, they are I(0) and therefore not part of the cointegrating relationship. how should I take them into the model? any idea? On 08.03.2011 16:35, Nick Cox wrote:Treating the weather as "truly exogenous" is not the best current science, although I imagine you don't want to build climate change into your model. Nick n.j.cox@durham.ac.uk Beat Hintermann I would like to estimate the cointegrating relationship between 3 I(1) variables, but in the presence of exogenous I(0) variables. Specifically, I want to estimate the long-term relationship between electricity, gas and coal prices, but taking into account exogenous weather shocks (like heating degree days or precipitation, stuff that is truly exogenous). From what I gathered in the Statalist archive, it is not advisable (and perhaps even impossible) to include exogenous and/or I(0) variables into the vec model framework. But since the weather definitely influences electricity and fuel prices, I don't see how ignoring this information will give me the best result. * * 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/
-- Beat Hintermann Assistant Professor University of Basel, Faculty of Business and Economics (WWZ) Peter Merian-Weg 6, 4002 Basel, Switzerland Tel. +41 61 267 3339 ------------------------------------------ * * 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/