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st: Re: Question about scaling intercept
From
Christopher Baum <[email protected]>
To
"BOONYAWAT K." <[email protected]>
Subject
st: Re: Question about scaling intercept
Date
Wed, 28 Nov 2012 19:16:22 +0000
<>
The easiest way to do this is with analytic weights. Using analytic weights keeps the summary statistics in the usual realm, which manual scaling does not.
. sysuse auto,clear
(1978 Automobile Data)
. g pp = price/mpg
. g hh = headroom/mpg
. g ll = length/mpg
. g mm = 1/mpg
. reg pp hh ll mm, nocons
Source | SS df MS Number of obs = 74
-------------+------------------------------ F( 3, 71) = 135.81
Model | 10400518.4 3 3466839.45 Prob > F = 0.0000
Residual | 1812466.22 71 25527.6932 R-squared = 0.8516
-------------+------------------------------ Adj R-squared = 0.8453
Total | 12212984.6 74 165040.332 Root MSE = 159.77
------------------------------------------------------------------------------
pp | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
hh | -722.7482 503.9827 -1.43 0.156 -1727.661 282.1648
ll | 82.69822 19.34002 4.28 0.000 44.13532 121.2611
mm | -6918.923 3358.944 -2.06 0.043 -13616.47 -221.3797
------------------------------------------------------------------------------
. reg price headroom length [aw=1/mpg^2]
(sum of wgt is 1.9839e-01)
Source | SS df MS Number of obs = 74
-------------+------------------------------ F( 2, 71) = 9.41
Model | 179144244 2 89572121.9 Prob > F = 0.0002
Residual | 676064553 71 9522035.95 R-squared = 0.2095
-------------+------------------------------ Adj R-squared = 0.1872
Total | 855208796 73 11715189 Root MSE = 3085.8
------------------------------------------------------------------------------
price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
headroom | -722.748 503.9827 -1.43 0.156 -1727.661 282.165
length | 82.69822 19.34002 4.28 0.000 44.13532 121.2611
_cons | -6918.924 3358.944 -2.06 0.043 -13616.47 -221.3807
------------------------------------------------------------------------------
Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html
An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html
An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html
On Nov 28, 2012, at 1:50 PM, BOONYAWAT K. <[email protected]>
wrote:
> Dear Prof. Kit,
>
> I wonder if you could kindly give me some suggestions about how to scale intercept.
>
> I would like to scale all variables including intercept with "1/asset" in the following equation.
>
> yit = a+ β1Xit +eit
>
>
> Do I need to scale all variables manually before running the equation? I am not sure how to scale intercept manually (because Stata will calculate the intercept automatically).
>
> or is it the same as I run the equation with -regress- , nocon ?
>
> yit /(1/asset)= a(1/asset) + β1X/(1/asset)it +eit
>
> Thank you very much for your kindly attention.
>
> Best regards,
> Karuntarat
>
>
>
>
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