RE: st: Modelling of categorical-continuous variable interaction

[Daniel Yue <xyrixx@hotmail.com>]

Wow, thanks a lot Maarten, that was really really helpful!

a) Is there a quick way to explain why "it is not recommended" to leave out the main effects?
b) regarding question 3: should that model 

by I: xtreg y x1 x2 x3, fe

give the same/equivalent results, if specified correctly?

Thanks again!

All the Best from Munich,

Daniel


----------------------------------------
> Date: Mon, 1 Jul 2013 15:44:27 +0200
> Subject: Re: st: Modelling of categorical-continuous variable interaction
> From: maartenlbuis@gmail.com
> To: statalist@hsphsun2.harvard.edu
>
> If you want to use one #, then it is up to you to include at least one
> main effect. I would choose i.l. Then the two models give different
> numbers, but the results are equivalent. The first will give the
> effects of the xs in groups 1, 2, and 3, while the second gives you
> the effect in group 1 and by how much that effect differs from group 1
> in groups 2 and 3. You could also use 1 # and both main effects, then
> the the first and second models are completely the same. It is not
> recommended to use 1 # without any of the main effects.
>
> *------------------ begin example ------------------
> sysuse nlsw88, clear
>
> gen byte occat = cond(occupation < 3 , 1, ///
> cond(inlist(occupation, 5, 6, 8, 13), 2, 3)) ///
> if occupation < .
> label variable occat "occupation in categories"
> label define occat 1 "high" ///
> 2 "middle" ///
> 3 "low"
> label value occat occat
>
> reg wage i.occat i.occat#c.grade
>
> reg wage i.occat##c.grade
>
> lincom grade + 2.occat#c.grade
> lincom grade + 3.occat#c.grade
>
> reg wage i.occat grade i.occat#c.grade
>
> *------------------- end example -------------------
> * (For more on examples I sent to the Statalist see:
> * http://www.maartenbuis.nl/example_faq )
>
> Hope this helps,
> Maarten
>
>
> On Mon, Jul 1, 2013 at 3:10 PM, Daniel Yue <xyrixx@hotmail.com> wrote:
>> Dear Statalisters,
>>
>> I would love your advice my model of the following specifications:
>>
>> y = i + t + (I*x1) + (I*x2) + (I*x3)
>>
>> where i and t are firm- and time-fixed effects, respectively, “I” is an indicator variable with values 0-2 and x1-x3 are the three IVs. “I” are supposed to illustrate three “categories” the firms are put into, depending on firm performance relative to two reference points: I==1 if performance of the firm is below a both reference points, I==2 if it is in between, I==3 if it is above. What I want to find out is whether y’s reaction to x1 x2 x3 differs in strength, i.e. if the slope of the coefficients for x1-x3 are different, depending on the “category” of the firm (hence the indicators),
>> The data is in panel format. I – xtset – the dataset and ran the following in Stata 12:
>>
>> xtreg y I#c.x1 I#c.x2 I#c.x3, fe
>>
>> My questions:
>>
>> 1.Do the coefficients for I#x1 I#x2 I#x3 really measure what I want them to, as described above?
>>
>> 2.If I instead run
>>
>> xtreg y I##c.x1 I##c.x2 I##c.x3, fe
>>
>> the results seem to differ by a lot, although I had expected them to be the same. What is wrong?
>>
>> 3. I also ran
>>
>> by I: xtreg y x1 x2 x3, fe
>>
>> because I thought the results there should be the same as with the original equation. Again, there are not. Why not? What am I missing?
>>
>> Thanks for your consideration!
>>
>> Daniel
>> *
>> * 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/
>
>
>
> --
> ---------------------------------
> Maarten L. Buis
> WZB
> Reichpietschufer 50
> 10785 Berlin
> Germany
>
> http://www.maartenbuis.nl
> ---------------------------------
>
> *
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> * http://www.stata.com/support/faqs/resources/statalist-faq/
> * http://www.ats.ucla.edu/stat/stata/ 		 	   		  
*
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