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st: RE: RE: re: simultaneous equations


From   "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: RE: re: simultaneous equations
Date   Fri, 27 Feb 2009 16:18:25 -0000

An alternative explanation (similar to Nick's point) is that the scaling
of the variables is crazy.  Stata can get grumpy when your variables are
wildly different orders of magnitude.

Try rescaling your variables (including the instruments) - i.e.,
multiply or divide each one by the appropriate power of 10 - so that
they all have a mean of about the same order of magnitude, and then see
what happens.

--Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
> Sent: Friday, February 27, 2009 3:43 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: RE: re: simultaneous equations
> 
> With coefficients of the order of 1e8 there seems to be a massive
> problem with the data. Look (again?) at the data, e.g. using a scatter
> plot matrix. There could be a substantial outlier, or some built-in
> dependency, or something else. Whatever it is, it is not obvious that
> any model can make sense of the predictor set you are using. 
> 
> Nick 
> n.j.cox@durham.ac.uk 
> 
> mmolina@uniroma3.it
> 
> As you adviced me I tried ivregress 2sls ... and obtained:
> 
> ivregress 2sls expshare b2b l1 age l4a (normscore = l11a l10),
> note: l10 dropped because of collinearity
> 
> Instrumental variables (2SLS) regression               Number of obs =
> 198
>                                                        Wald chi2(5)  =
> 40.30
>                                                        Prob > chi2   =
> 0.0000
>                                                        R-squared     =
>   .
>                                                        Root MSE      =
> 7.9e+07
> 
> --------------------------------------------------------------
> ----------
> ------
>     expshare |      Coef.   Std. Err.      z    P>|z|     [95% Conf.
> Interval]
> -------------+------------------------------------------------
> ----------
> ------
>    normscore |   4.04e+08   3.93e+08     1.03   0.304    -3.66e+08
> 1.18e+09
>          b2b |  -238087.7     387449    -0.61   0.539    -997473.9
> 521298.5
>           l1 |   66040.49   14947.01     4.42   0.000     36744.89
> 95336.09
>          age |   134492.7   220864.6     0.61   0.543    -298393.9
> 567379.3
>          l4a |  -95654.77   20067.76    -4.77   0.000    -134986.9
> -56322.68
>        _cons |  -1.33e+08   1.18e+08    -1.13   0.260    -3.65e+08
> 9.85e+07
> --------------------------------------------------------------
> ----------
> ------
> Instrumented:  normscore
> Instruments:   b2b l1 age l4a l11a
> 
> I agree with and don't know why the constant term is dropped.
> I was looking for some causality link between normscore and expshare,
> and
> supossed Simultaneous Equations may help me.
> 
> Kit Baum <baum@bc.edu>
> 
> MMolina said
> 
> I run this command:
> 
> 
> reg3 (normscore l1 b2b age l4a l11a l10) (expshare b2b l1 age 
> normscore
> l4a)
> 
> And obtained this results. Could you please tell me if the Std. Error
> 
> found for the expshare variable may invalidate the analysis or create
> any
> robustness problem?
> 
> I find it very strange, if expshare is really a fraction, that you get
> coefficients on the order of 10^8 on any regressor. Would you try
> running
> 
> ivreg expshare b2b l1 age l4a (normscore = l11a l10), first
> 
> 
> and show us what you get from that regression? (you could also use
> ivregress 2sls ... , first if you are using Stata 10)
> 
> 
> Also, is there a good reason (given definitions of the variables) that
> the
> constant term is dropped in your first equation?
> 
> 
> This system is triangular, in that normscore can be estimated with OLS
> as
> it does not contain expshare. You may still want to estimate it with
> 3SLS,
> but something fishy is going on here. See what the single- equation
> estimates of your second equation reveal.
> 
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> 


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