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Re: st: Nonlinear least squares restrictions

From   "G. Anderson" <>
Subject   Re: st: Nonlinear least squares restrictions
Date   06 Jun 2013 09:40:40 +0100

Hi Maarten,

Thanks a lot for your suggestions- they are proving very useful. I am currently using the propcnsreg function using the "lcons" identification option.

My variables included in lambda are annual dummies. Since I am looking at 2000-2005, I therefore have included a dummy for 2001,2002,2003,2004,2005- with no dummy for 2000 to avoid the collinearity. Does this sound sensible?

Am I right in thinking that with the "lcons" identification option, I can interpret the constrained coefficients the indirect effects of my constrained variables on the dependent variable, through the latent variable in the year 2000 (since as noted above 2000 is omitted as an annual dummy)?

Ideally I'd like to be able to interpret the constrained coefficients as the average effect over the years 2000-2003, rather than just in the year 2000- although at the moment I'm struggling to do this in this program.

Thanks for all your help,


On Jun 5 2013, Maarten Buis wrote:

On Wed, Jun 5, 2013 at 4:34 PM, G. Anderson wrote:
Is the right setup using  propcnsreg:

yield dum00 dum01 dum02 dum03 dum04 dum05 ,constrained(gdp unemployment
inflation) lambda(dum00 dum01 dum02 dum03 dum04 dum05)

Where dum are annual dummies. In particular- do I include the annual dummies as both independent variables and variables in lambda?

Yes, I did it this way to allow for a more flexible specification of
time as the main effect than in the interaction effect (-lambda()-).
So, you could have time as dummies for the main effect, but constrain
time to be linear in the interaction effect. The other way around is
technically possible, but I would not recommend it.

Is it also possible to impose a normalization so
that on average the coefficients on the dummies is equal to 1?

Just create your variables using an effect or sigma or deviation
coding scheme (different names for the same thing).

Hope this helps,

Maarten L. Buis
Reichpietschufer 50
10785 Berlin
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