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From |
"Nick Cox" <[email protected]> |

To |
<[email protected]> |

Subject |
st: RE: Calculate rolling mean using last observation in a group |

Date |
Tue, 12 Aug 2008 13:51:17 +0100 |

If I understand your question correctly, it yields to a minor variation on the technique documented in SJ-7-3 pr0033 . . . . . . . . . . . . . . Stata tip 51: Events in intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. J. Cox Q3/07 SJ 7(3):440--443 (no commands) tip for counting or summarizing irregularly spaced events in intervals and explained in my posting replying to your previous question: <http://www.hsph.harvard.edu/cgi-bin/lwgate/STATALIST/archives/statalist .0808/date/article-20.html> local N = _N gsort Company_No - Date gen avex = . qui forval i = 1/`N' { egen tag = tag(Investor_id) /// if Company_no == Company_no[`i'] & /// inrange(Date, Date[`i'] - 90, Date[`i']) su x if tag, meanonly replace avex = r(mean) in `i' drop tag } The obvious variations on the previous example are using -summarize, meanonly- to get the mean and specifying the previous 90 days within an -inrange()- condition. (This code includes the current date; modify according to taste.) The not-so-obvious variation is using -egen, tag()- to tag the _last_ relevant observation for each distinct Investor_id. -egen, tag()- tags just one of any repetitions of each distinct value of the variable specified. It's not documented, but the observation tagged is in fact the _first_ such occurrence in the dataset in the current sort order. Hence use -gsort- first to reverse date order in each panel, so that tagging catches the last such occurrence in time. Nick [email protected] Marietta Jones I have a new problem related to the dataset I presented in my original email (see below). For each observation in the dataset, I would like to calculate the mean of variable x for the same company_no on a rolling prior 90 day basis. The extra complexity arises by the fact that there may be more than one observations of variable x for the same investor_id for a given company_no. I would only like to include the last observation per investor_id for a given company_no in the calculation of the mean. >> I have the following dataset: >> >> Company_no Date Investor_id >> 1 03/01/2000 1 >> 1 04/09/2000 1 >> 1 12/12/2001 2 >> 2 13/12/2000 4 >> 2 07/08/2001 7 >> 3 09/08/2000 4 >> 3 19/03/2001 4 >> 3 02/05/2001 5 >> 3 03/12/2001 6 >> >> >> For each observation, I would like to calculate the number of distinct >> investors owning shares in a given company in the previous 12 months. >> The new variable (No_investors_past_12_months) will look as follows: >> >> Company_no Date Investor_id No_investors_past_12_months >> 1 03/01/2000 1 1 >> 1 04/09/2000 1 1 >> 1 12/12/2001 2 1 >> 2 13/12/2000 4 1 >> 2 07/08/2001 7 2 >> 3 09/08/2000 4 1 >> 3 19/03/2001 4 1 >> 3 02/05/2001 5 2 >> 3 03/12/2001 6 3 >> >> For example, for company 2 on 07/08/2001 there are two investors who >> have owned shares of this company within the past 12 months. >> >> The idea is that the same investor should be counted only once and we >> should count all observations over the past 12 months, including the >> current observation date. If there are no observations over the past >> 12 months, the value of the new variable should equal 1. * * 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/

**Follow-Ups**:**Re: st: RE: Calculate rolling mean using last observation in a group***From:*"Marietta Jones" <[email protected]>

**References**:**st: Calculate rolling mean using last observation in a group***From:*"Marietta Jones" <[email protected]>

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