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From |
Bersant Hobdari <bh.cees@cbs.dk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Re: coeffs across equations |

Date |
Fri, 27 Jun 2003 12:18:26 +0100 |

Dear Christopher, Thanks for the reply. I too was suspicious of using SURE. As I have different number of obs in every sample it makes it stronger the argument of not using it. I guess I have to pool the sample to test for coefficient differences. It will however introduce endogeneity in the estimation, exactly the reason why I had to split the sample. Sincerely, Bersant ----- Original Message ----- From: Christopher F Baum <baum@bc.edu> Date: Friday, June 27, 2003 12:25 pm Subject: st: Re: coeffs across equations > On Friday, June 27, 2003, at 02:33 AM, Scott wrote in response to > Bersant: > > > Date: Thu, 26 Jun 2003 21:00:53 -0500 > > From: "Scott Merryman" <smerryman@kc.rr.com> > > Subject: Re: st: test coefficients across equations [was: Re: > sample > > selection bias] > > > > - ----- Original Message ----- > > From: "Bersant Hobdari" <bh.cees@cbs.dk> > > To: <statalist@hsphsun2.harvard.edu> > > Sent: Thursday, June 26, 2003 11:51 AM > > Subject: Re: st: Re: sample selection bias > > > > > >> Hi Everyone, > >> > >> I had a question on testing coefficient across separately estimated > >> samples. The problem is the following: I estimate firm- level > >> production > >> function where I divide the sample in 5 sub-samples defined by > >> majority > >> owner: I.e., if majority owner is the State I classify the firm > in > >> that > >> group, if it is a financial institution I classify it in that > group > >> and > >> so on. After estimating regressions I would like to test the > equality > >> of > >> coefficients across equations. > >> > >> Any suggestion how this could be implemented is highly appreciated. > >> > >> Sincerely, > >> Bersant Hobdari > > > > > > You could create a dummy variable on majority owner then interact > it > > with > > your other variables and test the coefficients on the fully > interacted > > model > > (see the Stata FAQ on Chow tests). Example using the auto dataset. > > > > Equation 1: mpg = b0 + b1*price (if domestic) > > Equation 2: mpg = b0' + b1'*price (if foreign) > > > > Create the interaction term (if you have more categories -xi- > comes in > > handy) > > gen priceXforeign = price *foreign > > > > Regress the full interacted model > > regress mpg = price foreign priceXforeign > > > > A test on foreign will compare common intercepts, a test on > > priceXforeign > > will test common slopes, and a test on both foreign and > priceXforeign > > will > > test if they are jointly equal to zero, or if equation 2 differs > from> equation 1. > > > > However, if you are concerned about correlation across equation > (or > > wish to > > test for it), -reshape- your data into a wide data structure and > > use -sureg-. > > > > > This is a FAQ on Statalist. One cannot in general test coefficients > from separate estimations. Pooling the data and estimating a > single, > fully interacted model, as suggested, is probably the most sensible > approach, although it does then assume homoskedasticity across the > 5 > categories, which 5 separate regressions will not. Thus, one may > want > to test for groupwise heteroskedasticity if the est. sigma^2 from > the > category regressions are very different. > > The suggestion for sureg relaxes that assumption, and handles the > separate coefficients (including making it easy to test / constrain > across equations). However most implementations of SURE will demand > that there are the same number of observations in each equation (a > constraint not required by SURE, in that one can calculate > consistent > estimates of the residual covariance matrix from the dot products > of > the residuals, whatever their length). I suspect Bersant may not > have > equal numbers of firms per category. > > Kit > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > ********************************************************************** ****** > Denne e-mail er scannet af mailFence fra Sure Solutions > (www.suresolutions.dk),og der er ikke fundet vira. > ********************************************************************** ****** >

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