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Re: st: Generating trend on dummies


From   Seema Bhatia <ler02sb@reading.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Generating trend on dummies
Date   Thu, 13 Sep 2007 15:17:52 +0100

Thanks Maarten

That is useful as usual!

Regards

Seema

----- Original Message ----- 
From: "Maarten buis" <maartenbuis@yahoo.co.uk>
To: <statalist@hsphsun2.harvard.edu>
Sent: Thursday, September 13, 2007 3:04 PM
Subject: Re: st: Generating trend on dummies


> --- Seema Bhatia <ler02sb@reading.ac.uk> wrote:
>> I have fitted a panel Random Effects model for my data over 20 years.
>> I have 4 dummies within the model in which I would like to see the
>> change over the 20 years.
>>
>> I would like to see how the dummies com, com_1, sadc and sadc_1 have
>> evolved over the 20 year period and plot them. I am told that the
>> within equation can be used to generate yearly coefficients this. Any
>> ideas on how I can use the within estimator to generate yearly
>> coefficients on each of these dummies?
>
> The answer depends on your grouping variable:
>
> Things are easy (though not necesarily correct) if you are grouping on
> year. In that case you make the dummies com, com_1, sadc, and sadc_1
> random and use predict to get annual estimates.
>
> In your case it would be more common to group on country or dyad of
> countries. In that case you can get annual estimates by entering year
> in dummies and the interaction term of the dummies com, com_1, sadc,
> and sadc_1 with the annual dummies. One useful trick in this case is
> that by excluding the main effect of the dummies com, com_1, sadc, and
> sadc_1 you can enter all interactions, which are now directly the
> annual effects instead of deviations from the baseline year. This is
> shown in the example below (which, just for fun, also shows how to put
> 95% confidence intervals around those estimates):
>
> *-------------------- begin example ------------------
> set more off
> webuse nlswork, clear
>
> /*create annual dummies*/
> tab year, gen(yd)
>
> /*create interation effects*/
> foreach var of varlist yd* {
> gen `var'Xgrade = `var'*grade
> }
> drop yd1 /*base category*/
>
> xtmixed ln_w yd* age ttl_exp tenure || id:
>
> /*store annual effects*/
> matrix b = e(b)
> matrix b = b[1, "ln_wage:yd1Xgrade".."ln_wage:yd15Xgrade"]
> matrix b = b'
> svmat b
>
> /*store confidence interval*/
> matrix V = e(V)
> matrix V = V["ln_wage:yd1Xgrade".."ln_wage:yd15Xgrade", /*
> */ "ln_wage:yd1Xgrade".."ln_wage:yd15Xgrade"]
> matrix se = vecdiag(cholesky(diag(vecdiag(V))))'
> svmat se
> gen lb = b1 - 1.96*se1
> gen ub = b1 + 1.96*se1
>
> /*generate year*/
> gen y = _n + 1967 if b1 < .
>
> /*create graph*/
> twoway rcap ub lb y || scatter b1 y
> *------------------- end example ---------------------------
> (For more on how to use examples I sent to the Statalist, see
> http://home.fsw.vu.nl/m.buis/stata/exampleFAQ.html )
>
> Hope this helps,
> Maarten
>
>
> -----------------------------------------
> Maarten L. Buis
> Department of Social Research Methodology
> Vrije Universiteit Amsterdam
> Boelelaan 1081
> 1081 HV Amsterdam
> The Netherlands
>
> visiting address:
> Buitenveldertselaan 3 (Metropolitan), room Z434
>
> +31 20 5986715
>
> http://home.fsw.vu.nl/m.buis/
> -----------------------------------------
>
>
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