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Re: st: Regression Across Two Groups


From   Muhammad Anees <anees@aneconomist.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Regression Across Two Groups
Date   Wed, 14 Dec 2011 14:37:40 +0500

Thanks Yual, I would try that for sure.

On Wed, Dec 14, 2011 at 2:27 PM, Yuval Arbel <yuval.arbel@gmail.com> wrote:
> Muhammad,
>
> You can look at my correspondence with David Ashcraft.
>
> For your convenience I copies part of it:
>
> David,
>
> You can simply use Difference in Difference (DD) analysis:
>
> Run a regression on the group of managers who take the first (second)
> approach. Then predict what would have happened to the performance of
> each manager in the case that he/she takes the other approach and use
> the -ttest- to see whether the difference is significant.
>
> Note to define dummy variables in any case that variables are ordinal,
> i.e., the numerical values have no quantitative meaning
>
> I use this approach quite often. You can look at the second part of my
> following paper published in RSUE:
>
> Arbel, Yuval; Ben Shahar,Danny; Gabriel, Stuart  and Yossef Tobol:
> "The Local Cost of Terror: Effects of the Second Palestinian Intifada
> on Jerusalem House Prices".Regional Science and Urban Economics (2010)
> 40:  415-426
>
> On Wed, Dec 14, 2011 at 11:18 AM, Maarten Buis <maartenlbuis@gmail.com> wrote:
>> On Wed, Dec 14, 2011 at 6:25 AM, Muhammad Anees wrote:
>>> Sorry for not clarifying the story about the types of variables, like
>>> earnings which I have at hand as a categorical/dichotomous variable.
>>> For example if an individual has a portion of earnings from doing
>>> consultancies or involved in any R&D organizations beside their normal
>>> routine jobs. In this case, I was interested in comparing the
>>> regression models (across foreign qualified and not foreign qualified)
>>> of earnings on other predictors say experience, research training, job
>>> nature, industry, region (rural and urban) using logit/probit in case
>>> of categorical variables and similarly using OLS for continuous
>>> dependent variable which at least I do not have at this stage.
>>
>> This is still not clear. The independent/explanatory/right-hand-side/x
>> variables aren't relevant here, they can be of any type, it is the
>> type of  the dependent/explained/left-hand-side/y variable that
>> matters. Earnings is typically collected as either a continuous
>> variable (how much do you earn?) or as a choice from a set of
>> intervals (did you earn less than x$, between x$ and y$, etc.?). None
>> of these are correctly modeled as a logit/probit. In the former case I
>> would use a -glm- with the -link(log)- option, in the latter case I
>> would start with assigning each category with a reasonable
>> representative number and than use -glm- with the -link(log)- option.
>> There are other solutions for the latter problem, e.g. -intreg-, but
>> if the underlying distribution is non-normal, which is likely to be
>> the case with earnings, then it is unclear whether these alternatives
>> are any better. The comparison is than just a matter of adding the
>> appropriate dummies and/or interactions.
>>
>> -- Maarten
>>
>> --------------------------
>> Maarten L. Buis
>> Institut fuer Soziologie
>> Universitaet Tuebingen
>> Wilhelmstrasse 36
>> 72074 Tuebingen
>> Germany
>>
>>
>> http://www.maartenbuis.nl
>> --------------------------
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>
>
>
> --
> Dr. Yuval Arbel
> School of Business
> Carmel Academic Center
> 4 Shaar Palmer Street, Haifa, Israel
> e-mail: yuval.arbel@gmail.com
>
> *
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-- 

Regards
---------------------------
Muhammad Anees
Assistant Professor
COMSATS Institute of Information Technology
Attock 43600, Pakistan
www.aneconomist.com

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