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RE: st: Coefficient Constraints as Counterfactuals


From   Matthew C Mahutga <[email protected]>
To   "[email protected]" <[email protected]>
Subject   RE: st: Coefficient Constraints as Counterfactuals
Date   Thu, 10 Jan 2013 19:18:15 +0000

Hi Nick.

Thanks for this and for asking me to clarify.

I'm using xtpcse with a first order autocorrelation correction.

Do I understand you correctly that if my original model (with other covariates omitted) is 

Y = b0 + b1x1+b2x2+b3x1*x2

And I want to estimate the predicted values of a model in which b1 = b1+b3, then I would regress Y^(=y-b1+b3x1) on x2 and the rest of the covariates and then estimated the prediction? 

Thanks again,

Matthew

-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Nick Cox
Sent: Thursday, January 10, 2013 10:41 AM
To: [email protected]
Subject: Re: st: Coefficient Constraints as Counterfactuals

If you want say to -regress- such that

y = b_0 + b_1 x_1 + 42 x_2

then calculate

y - 42 x_2

and -regress- on x_1. Naturally, this isn't universal, but what could be universal across all possible estimation commands? Moral: You should tell us more about the command you are using.

Nick

On Thu, Jan 10, 2013 at 6:25 PM, Matthew C Mahutga <[email protected]> wrote:

> I have a question that I hope has an easy answer that escapes me.
>
> I am using  estimation command that does not support the constraints option, but I would like to constrain a select group of coefficients. For example, one model includes an interaction term between a given socioeconomic process and a dummy variable for institutional regime. I would like to ask questions like "what would the trend in my outcome look like if the socioeconomic process had the larger of the two conditional (i.e. by regime type) effects".
>
> Is there a universal means by which to set a given coefficient to a fixed value prior to model estimation. Or, can I estimate predicted values using stored results but change the coefficient on one covariate beforehand?

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