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

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: regression on quartiles |

Date |
Sat, 15 May 2004 09:17:29 -0400 |

I don't think sureg is what you want -- sureg is used for models estimated

on the same sample. What you want is more like a Chow test or, preferably,

just create interaction terms on the slope (and/or intercept). This latter

approach can be done for you by xi. For example, if you create zquart to

hold the quartiles of Z, then you could

xi: reg Y X i.zquart*X

and then look at the significance of the _I terms and perform tests on them

Michael Blasnik

michael.blasnik@verizon.net

----- Original Message -----

From: "Vuri, Daniela" <Daniela.Vuri@iue.it>

To: <statalist@hsphsun2.harvard.edu>

Sent: Thursday, May 13, 2004 4:43 AM

Subject: st: compare coefficients after sureg

> Dear Stata users,

> I have the following problem.

> I have a regression of Y on X and Z and I want to see if the effect of Z

is different across quartile of Z.

> I do the following:

>

> gen quart=1 if Z is in the first quartile

> replace quart=2 if Z is in the second quartile

> replace quart=3 if Z is in the third quartile

> replace quart=4 if Z is in the fourth quartile

>

> and then I do the following

>

> bysort quart: sureg(Y X)

>

> at this point I would like to test whether the beta coefficient I get in

the first equation (the first quartile) is equal to the beta coefficient I

get in the second equation (the second quartile) and so on.

>

> Is sureg the right command? and how can I get the test of equality of the

coefficients across quartiles?

>

> thanks

> daniela

>

There are two approaches that one could follow here. Michael's suggestion implies a linear regression model in which there is a single intercept term and four different slopes (one for each quartile). Since the number of observations are equal (assuming mod(N,4)=0) in each quartile, Daniela could reshape the data wide by quart, and then run sureg on the four different "equations": eqn_i contains the Y and X from quartile i, etc. In the SUR context, one can then test that the slopes are equal across equations. This model would allow for different slopes, intercepts, and sigma^2 for each quartile. An intermediate form would be to follow Michael's suggestion and allow for quartile-specific intercepts; that form still assumes that the errors are homoskedastic across quartiles.

Kit

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**Follow-Ups**:**st: Re: regression on quartiles***From:*"Michael Blasnik" <michael.blasnik@verizon.net>

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