Hi again,
I have some data that has firm ID (firm), Edate (event date), a dummy variable IsForecast, and a count variable ForecastNum, which can take value 0, 1, or 2. IsForecast indicate whether there is (at least 1) forecast, whereas ForecastNum count its actual number, so when IsForecast == 1, ForecastNum must be either 1 or 2, it can't be 0.
For each firm, there is one or several event dates. For those firms with more than one event dates, I want to keep one event date with IsForecast and ForecastNum not be 0. The entry not necessarily occur first or last within each firm, so I don't know how to deal with it.
Some event dates are missing, if that is the case, both IsForecast and ForecastNum will be 0. Some data here:
Note: the instances of ForecastNum == 2 is not very common, so the example data generated by dataex does not show the instances where ForecastNum is 2.
Thanks in advance for any help!
I have some data that has firm ID (firm), Edate (event date), a dummy variable IsForecast, and a count variable ForecastNum, which can take value 0, 1, or 2. IsForecast indicate whether there is (at least 1) forecast, whereas ForecastNum count its actual number, so when IsForecast == 1, ForecastNum must be either 1 or 2, it can't be 0.
For each firm, there is one or several event dates. For those firms with more than one event dates, I want to keep one event date with IsForecast and ForecastNum not be 0. The entry not necessarily occur first or last within each firm, so I don't know how to deal with it.
Some event dates are missing, if that is the case, both IsForecast and ForecastNum will be 0. Some data here:
Note: the instances of ForecastNum == 2 is not very common, so the example data generated by dataex does not show the instances where ForecastNum is 2.
Code:
* Example generated by -dataex-. For more info, type help dataex clear input double firm float(Edate IsForecast ForecastNum) 150 21937 1 1 153 . 0 0 156 21934 0 0 157 21930 0 0 159 21937 1 1 159 22020 0 0 166 21853 0 0 338 . 0 0 400 22020 0 0 400 21932 0 0 403 21930 0 0 408 22020 0 0 411 21848 0 0 415 22021 0 0 419 22019 0 0 420 22020 0 0 420 21937 1 1 422 21932 0 0 423 21934 0 0 423 22020 0 0 428 21935 0 0 428 22020 0 0 430 22020 0 0 430 21935 0 0 488 22019 0 0 501 22015 0 0 509 21935 0 0 509 22020 0 0 516 21945 1 1 516 22020 0 0 517 21936 0 0 517 22020 0 0 519 22019 0 0 520 22019 0 0 526 22020 0 0 526 21936 0 0 528 21937 1 1 534 22005 0 0 536 22020 0 0 536 21937 1 1 544 21930 0 0 545 22022 0 0 546 21932 0 0 546 22020 0 0 547 21932 0 0 553 21937 1 1 554 . 0 0 558 22020 0 0 558 21932 0 0 558 21853 0 0 559 22020 0 0 561 22020 0 0 563 21918 0 0 564 21937 1 1 564 22020 0 0 568 . 0 0 576 22019 0 0 582 21945 1 1 584 22020 0 0 584 21945 1 1 590 21935 0 0 592 22020 0 0 596 . 0 0 601 . 0 0 606 21937 1 1 606 22020 0 0 607 22020 0 0 607 21853 0 0 610 22018 0 0 610 21932 0 0 612 21936 0 0 612 22016 0 0 615 21945 0 0 615 22020 0 0 617 . 0 0 619 22014 0 0 623 21935 0 0 627 . 0 0 629 21929 0 0 629 22016 0 0 630 22020 0 0 631 22019 0 0 632 . 0 0 633 21935 0 0 633 22020 0 0 635 21937 1 1 635 22019 0 0 636 21937 1 1 637 22020 0 0 637 21935 0 0 639 21945 1 1 655 22019 0 0 655 21936 0 0 661 21917 0 0 663 21935 0 0 663 22020 0 0 665 . 0 0 669 22020 0 0 669 21937 1 1 670 22020 0 0 end
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