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From |
Yuval Arbel <yuval.arbel@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Re: |

Date |
Wed, 30 Nov 2011 22:05:29 -0800 |

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 <ashcraftd@rocketmail.com> 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 <sjsamuels@gmail.com> > To: statalist@hsphsun2.harvard.edu > 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 > <ashcraftd@rocketmail.com> 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: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ >> > > > > -- > Dr. Yuval Arbel > School of Business > Carmel Academic Center > 4 Shaar Palmer Street, Haifa, Israel > e-mail: yuval.arbel@gmail.com > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- Dr. Yuval Arbel School of Business Carmel Academic Center 4 Shaar Palmer Street, Haifa, Israel e-mail: yuval.arbel@gmail.com * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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