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From |
agostino@unical.it |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: reshaping data? |

Date |
Sat, 27 Oct 2012 18:50:34 +0200 |

dear Nick, P_1 and P_2 are the prices of two substitute goods,

best Maria Quoting Nick Cox <njcoxstata@gmail.com>:

I am getting closer, but it seems to me that there is still some arbitrariness here. If I am 789 then the others are 790 and 791 and should be P_1 P_2. But which should be which? I can't see a rationale here. Nick On Fri, Oct 26, 2012 at 2:35 PM, <agostino@unical.it> wrote:dear Nick, each item is observed each week (for two years, so I have 106 observations for each supermarket in my sample), and belongs to a family. The families include from one up to 16 items (the number of items is not fixed for each fam). What follows is an example of a family made up of three items Code_item week Q P Code_family 789 1 8 2 1 790 1 25 4 1 791 1 9 1.3 1 789 2 12 2 1 790 2 2 3 1 791 2 20 1.2 1 and so forth for 106 times (each supermarket) I'd like to regress Q on P (and other ctrl vbls, that I omit for brevity) and the prices of the other two items (substitute goods), in other words to have a dataset like follows: Code_item week Q P Code_family P_1 P_2 789 1 8 2 1 4 1.3 790 1 25 4 1 2 1.3 791 1 9 1.3 1 2 4 789 2 12 2 1 3 1.2 790 2 2 3 1 2 1.2 791 2 20 1.2 1 2 3 thanks for your patience... Quoting Nick Cox <njcoxstata@gmail.com>:Sorry, but this seems to imply as many predictors as observations, which isn't a good idea. Presumably you don't mean that, so you have tell us more about your data structure for this to be clear to me. Nick On Fri, Oct 26, 2012 at 12:31 PM, <agostino@unical.it> wrote:dear Nick, I'd like to estimate separate regressions, one for each family, hence the number of predictors would be the same for each family hope this clarifies best M. Quoting Nick Cox <njcoxstata@gmail.com>:In that case I really don't understand what you are seeking. See also Yuval's comments. I've never come across a model in which there are a different number of predictors for different observations, although I am always happy to be educated. It seems to me that 1. Either you are applying a standard model, in which case you can give literature references. 2. Or this is a new model, in which case you need to explain how it would be set-up and estimated. Note that it's easy to get variables such as the mean of the other prices in the same family. See FAQ . . Creating variables recording prop. of the other members of a group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. J. Cox 4/05 How do I create variables summarizing for each individual properties of the other members of a group? http://www.stata.com/support/faqs/data/members.html On Thu, Oct 25, 2012 at 3:39 PM, <agostino@unical.it> wrote:dear Nick, thanks for your prompt reply. Unfortunately, the number of items is not fixed best regards Maria Quoting Nick Cox <njcoxstata@gmail.com>:This model formulation makes me feel a bit queasy, but I think what you want is something like this. Suppose for concreteness the number of items is fixed at 8. (I don't see how this will work if the number is not fixed.) So, "for any value of 8" sort code_family code_item forval i = 1/8 { by code_family : gen P`i' = P[`i'] } Note that, contrary to your title, there is no -reshape- here as you want your observations to remain observations; at least that's my understanding. Nick On Thu, Oct 25, 2012 at 3:08 PM, <agostino@unical.it> wrote:I have to estimate the equation Q1=a+b1P1+b2P2+...bnPn+e Where Q1 is the quantity of item 1 sold by a supermarket during a week , P1 is the price of item 1 in that week, the other prices are those of the n items belonging to the same family of items. My data set is organized as follows: Code_item week Q P Code_family 789 1 8 2 1 790 1 25 4 1 791 1 9 1.3 1 792 1 12 2 1 800 1 7 2 2 801 1 20 1.2 2 802 1 11 1.6 2 803 1 12 2 2 And so forth for the other weeks and families... For each item, how can I include in my regression the prices of the other (n-1) items of the same family, ignoring the prices of the items belonging to other families?* * 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/---------------------------------------------------------------- This message was sent using IMP, the Internet Messaging Program. **** Riservatezza / Confidentiality **** In ottemperanza al D.Lgs. n. 196 del 30/6/2003 in materia di protezione dei dati personali, le informazioni contenute in questo messaggio sono strettamente riservate ed esclusivamente indirizzate al destinatario indicato (oppure alla persona responsabile di rimetterlo al destinatario). Vogliate tener presente che qualsiasi uso, riproduzione o divulgazione di questo messaggio e' vietato. 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---------------------------------------------------------------- This message was sent using IMP, the Internet Messaging Program. **** Riservatezza / Confidentiality **** In ottemperanza al D.Lgs. n. 196 del 30/6/2003 in materia di protezione dei dati personali, le informazioni contenute in questo messaggio sono strettamente riservate ed esclusivamente indirizzate al destinatario indicato (oppure alla persona responsabile di rimetterlo al destinatario). Vogliate tener presente che qualsiasi uso, riproduzione o divulgazione di questo messaggio e' vietato. Nel caso in cui aveste ricevuto questo messaggio per errore, vogliate cortesemente avvertire il mittente e distruggere il presente messaggio. * * 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/

**Follow-Ups**:**Re: st: reshaping data?***From:*Nick Cox <njcoxstata@gmail.com>

**References**:**st: reshaping data?***From:*agostino@unical.it

**Re: st: reshaping data?***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: reshaping data?***From:*agostino@unical.it

**Re: st: reshaping data?***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: reshaping data?***From:*agostino@unical.it

**Re: st: reshaping data?***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: reshaping data?***From:*agostino@unical.it

**Re: st: reshaping data?***From:*Nick Cox <njcoxstata@gmail.com>

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