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From |
Christopher Baum <kit.baum@bc.edu> |

To |
"BOONYAWAT K." <karuntarat.boonyawat@durham.ac.uk> |

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. <karuntarat.boonyawat@durham.ac.uk> 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 > > > > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

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