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Re: st: Constructing a variable from standard deviations


From   Austin Nichols <[email protected]>
To   [email protected]
Subject   Re: st: Constructing a variable from standard deviations
Date   Mon, 22 Nov 2010 16:49:21 -0500

M.P.J. van Zaal <[email protected]>:

egen ... , by(occ)
not
egen ... , by(each residual value)


On Mon, Nov 22, 2010 at 4:44 PM, M.P.J. van Zaal
<[email protected]> wrote:
> I have now run all the regression for the occupation
>
> reg ink controls dummy1, robust
> predict resid1, resid
> .
> reg ink controls dummy106, robust
> predict resid106, resid
>
>
> Then I used:
> egen s = sd( res ), by(resid1-resid106)
> g newerror = s*rnormal()
>
> But now i get a variable with value "0" and frequency "6".
>
> What did i do wrong?
>
> I checked the stand deviations with tabstat and this works. They are all
> varying even more now.
> ----- Original Message -----
> From: Austin Nichols <[email protected]>
> Date: Monday, November 22, 2010 9:23 pm
> Subject: Re: st: Constructing a variable from standard deviations
> To: [email protected]
>
>> M.P.J. van Zaal <[email protected]>:
>>
>> Don't say "you guys claim that the estimates from this procedure would
>> be meaningless" --Stas agreed with the basic approach, as do I, since
>> it is standard and easily understood.  Stas almost gave you the
>> answer:
>>
>> regress depvar whatever i.occupation
>> predict res, res
>> egen s = sd( res ), by( occupation )
>> g newerror = s*rnormal()
>>
>>
>> On Mon, Nov 22, 2010 at 3:09 PM, M.P.J. van Zaal
>> <[email protected]> wrote:
>> > I am still digesting all this new information..
>> >
>> > The approach used by Kit seems to be familiar to an approach i used
>> > earlier. My prof gave me the advice to include all the dummies in
>> the> regression and then calculate the residual per occupation,
>> since this is
>> > what Bonin et all do.
>> >
>> > However, you guys claim that the estimates from this procedure
>> would be
>> > meaningless. I will start over again and make regression per
>> occupation> and then predict the residuals.
>> >
>> > When I estimate the standard error of all these residuals I will
>> > probably have 106 different "variables". How can I construct one
>> > variable from all these standard deviations? This is the problem at
>> > which I was stuck at my old approach, so i will probably have the
>> > problem again when i use a new method.
>

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