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Re: st: estimating an asymmetrical relationship


From   David Jacobs <jacobs.184@sociology.osu.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: estimating an asymmetrical relationship
Date   Wed, 16 Dec 2009 15:48:28 -0500

Hi Gisella:

If you ever find out what is the matter with my suggestion from your colleague, shoot me an e-mail at jacobs.184@osu.edu.

I'm curious why it might be incorrect.

Dave Jacobs
.

At 03:31 AM 12/16/2009, you wrote:
Thank you very much Nick and David for your thoughtful and helpful replies.

On Nick's point about whether I need a model that treats
my variables as linked time series or whether I am lumping together data
without regard to time, I am not sure whether I understand this correctly and maybe I am exposing my ignorance here, but I am estimating a normal (?) time series model, so the observations have dates but I am not doing any explicit linking... One can look at this relationship in terms of economic theory and there are explanations, but what I need to do here is empirically test whether there is an asymmetry for a particular country over a particular time period. I haven't found literature that econometrically tests for this type of asymmetrical relationship in other contexts, which is why I am struggling about the correct way of doing it.

On David's suggestion of dummies for the different periods (increasing and decreasing of thee explanatory variable), actually this was something I considered but was told my an econometrician colleague that this was wrong (not sure why) and that only a nonlinear estimation would be appropriate. I would be interested in hearing the views of other list members on this?

Or alternatively, a suitable way of specifying and testing the relationship in STATA, whether using OLS or nonlinear specification?

Thank you!!!!

Gisella

--- On Tue, 12/15/09, David Jacobs <jacobs.184@sociology.osu.edu> wrote:

> From: David Jacobs <jacobs.184@sociology.osu.edu>
> Subject: Re: st: estimating an asymmetrical relationship
> To: statalist@hsphsun2.harvard.edu
> Date: Tuesday, December 15, 2009, 6:18 PM
> Gisella, how about this technique
> (and let's see what others on the list say about it, as it's
> been a while since I thought about this issue)?
>
> Construct a dummy coded 1 if there's growth in the
> explanatory variable of interest and construct another if
> there's negative change.  Multiply each dummy with the
> explanatory variable of interest thereby creating two
> interacted explanatory variables.  Enter both product
> terms in a model.  If there's a statistically
> significant difference between the coefficients on the two
> interacted terms, that should provide evidence that you
> indeed have asymmetric effects.
>
>
> At 11:55 AM 12/15/2009, you wrote:
> > This question is partly econometric and partly STATA,
> and I would greatly appreciate any advice. I need to
> estimate a relationship which I believe to be asymmetric -
> between growth as the explanatory variable of interest and
> unemployment as the dependent variable. Asymmetric in the
> sense that, while overall I expect a negative relationship,
> I expect the magnitude of the relationship to be higher when
> growth is going down than when it is going up (for reasons
> not necessary to go into here). That is, I expect the
> coefficient on the relationship to be higher during periods
> of high or increasing growth than during periods of low or
> decreasing growth (I realise that high and increasing is not
> the same thing but I will later figure out which). So I
> believe that OLS is not appropriate as it will not pick up
> these differences, and what I am really interested in
> investigating is whether there is asymmetry and how strong
> it is. Ideally I would like to get
> >  different coefficients for the 2 types of
> periods (note that this is not one long period and then
> another long period, but ups and downs). I believe that I
> need a nonlinear estimation method to do this. But beyond
> that I am not sure how to proceed and would be terribly
> grateful for any suggestions.
> >
> > Thank you very much.
> >
> > Gisella
> >
> >
> >
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