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R: st: Re:


From   "Carlo Lazzaro" <[email protected]>
To   <[email protected]>
Subject   R: st: Re:
Date   Sat, 3 Dec 2011 19:13:54 +0100

Dear Yuval, 
sorry for the mishap. Unfortunately, like Steve reported some days ago, I do
not have access to your article, since I am not a resident academic.
Anyway, congratulations on your paper. 
Kindest Regards,
Carlo


-----Messaggio originale-----
Da: [email protected]
[mailto:[email protected]] Per conto di Yuval Arbel
Inviato: sabato 3 dicembre 2011 18.58
A: [email protected]
Oggetto: Re: st: Re:

Thanks Carlo. Note, however, this is the working paper. The official
paper in its final form may be found at:

http://www.sciencedirect.com/science/article/pii/S0166046210000438

You don't need to purchase it: My guess is that every university  with
a reasonable economics/business departments has a subscription to the
electronic version of sciencedirect.

What is nice about the tables in the paper is that they state the
formulas for the simple t-test which compares between groups. Needless
to say you can run these tests and confidence intervals in stata by
-ttest- and -ci- commands

If you come to think about it, this methodology is a good way to
simulate scientific comparisons between groups

On Sat, Dec 3, 2011 at 2:45 PM, Carlo Lazzaro <[email protected]> wrote:
> For those who may concern, I have freely downloaded Yuval's article at:
> http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1804689.
>
> Kindest Regards,
> Carlo
> -----Messaggio originale-----
> Da: [email protected]
> [mailto:[email protected]] Per conto di Yuval Arbel
> Inviato: giovedì 1 dicembre 2011 7.05
> A: [email protected]
> Oggetto: Re: st: Re:
>
> Steve and David,
>
> I still suggest you take a look at the full version of my RSUE paper:
> you can access it through science direct (www.sciencedirect.com). The
> paper also includes the formula for calculating the t-test that I used
> there. In addition, i believe you should take a look at the references
> of our paper, particularly about the literature that deals with
> hedonic indices
>
> Note that RSUE in one of the best journals in the field of urban
> economics and its editor (Dan McMillen) is a highly appreciated
> statitistician.
>
> What i did in the second part of the paper is a paired t-test after
> controlling all the characteristics of the apartment: I applied a
> methodology with a cross-sectional nature and simulated a situation
> where you modify the position of each dwelling unit with identical
> characteristics from frontline to non-frontline streets and
> vice-versa: you can check into the statistical literature to see that
> this is the  appropriate test in this case
>
> I am not sure that you can do precisely what I did in the paper by
> using -margins-: Maybe if -margins- can give you the standard
> deviation of the point estimator (something equivalent to
> -predict,stdp- but for a point estimator) - but this does not seem to
> be precisely equivalent to what i did and, in fact, it seems that
> while using this methodology - you loose information (you take only
> the average characteristics instead of the characteristics of each
> dwelling unit seperately).
>
> Finally, note that in empirical work you can only do your best effort
> to isolate the effects. You cannot get into perfection. Richard Arnott
> (another very famous empirical urban economist) said in one of his
> papers that isolating an effect via regression analysis is similar to
> a New-Yorker who comes out of his apartment during a busy morning in
> new York and tries to listen to a whisper
>
> On 11/30/11, David Ashcraft <[email protected]> wrote:
>> Steve,
>>
>> Can you please explain a little further. Let me rephrase the question
>> initially asked. Whether coefficients obtained after running regression
on
>> all managers (full dataset) are same as the
>> average coefficients obtained from running regressions on individual
>> mangers. I don't know a paper that has done analysis on this pattern, and
>> would like to know, if there exist any analysis like that. My idea is,
> both
>> method should reflect the similar results.
>>
>> David
>>
>>
>> ----- Original Message -----
>> From: Steve Samuels <[email protected]>
>> To: [email protected]
>> Cc:
>> Sent: Thursday, December 1, 2011 1:39:29 AM
>> Subject: Re: st: Re:
>>
>>
>>
>> Yuval,
>>
>> I don't have access to your article, but I have an observation: The
>> predictions (real and counterfactual) that are averaged are not
> independent,
>> because they are all functions of the estimated regression coefficients.
I
>> don't think a t-test accommodate the non-independence. In Stata, I would
> use
>> -margins- or -lincom- after -margins-.
>>
>> Steve
>>
>>
>>
>> On Nov 26, 2011, at 9:09 AM, Yuval Arbel wrote:
>>
>> 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 Sat, Nov 26, 2011 at 12:11 PM, David Ashcraft
>> <[email protected]> wrote:
>>> Hi Statalist,
>>>
>>> This is more like an econometric than a Stata question. I am little lost
>>> on the following scenario:
>>>
>>> The situation is: I want to measure the performance of managers, who has
> a
>>> specific approach against those who do not. I have several individual
>>> managers in each category. One way is to regress the performance of
these
>>> managers against their benchmark for the whole data using
>>> -regress manager benchmark, by(belief)
>>> The second option is to run individual regression on each manager and
get
>>> the coefficients of individual regressions and run a ttest alpha,
>>> by(belief) .
>>>
>>>
>>> Now the question is, how different is the result from the ttest of alpha
>>> from that of the alpha of the regression equation.
>>> Any help will be really appreciated.
>>>
>>> If anyone can suggest an academic paper on similar scenarios, that would
>>> be a great help.
>>>
>>>
>>> David
>>>
>>> *
>>> *   For searches and help try:
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>>>
>>
>>
>>
>> --
>> Dr. Yuval Arbel
>> School of Business
>> Carmel Academic Center
>> 4 Shaar Palmer Street, Haifa, Israel
>> e-mail: [email protected]
>>
>> *
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>>
>>
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>>
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>>
>
>
> --
> Dr. Yuval Arbel
> School of Business
> Carmel Academic Center
> 4 Shaar Palmer Street, Haifa, Israel
> e-mail: [email protected]
>
> *
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>
>
>
> *
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-- 
Dr. Yuval Arbel
School of Business
Carmel Academic Center
4 Shaar Palmer Street, Haifa, Israel
e-mail: [email protected]

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