Hello everyone I hope you're doing all good.
As part my study, I am aggregating assets of "divisions" (fundno) of "companies" (portno) to keep only these companies that have at least 10 mln assets, when all divisions are summarized in a month t. If a company does not have a minimum of 10 mln assets it is dropped.
Yet sometimes, the company achieves the 10 mln, but later it might drop below the level. Thus, once it has reached 10 mln, even if in some future months the assets are below 10mln, I would like to keep it in my sample to make it less volatile and to avoid selection bias.
May I kindly ask you for some help on that case?
So far I did:
-egen totalmtna=total(mtna), by (crsp_portno mofd)- and then
-drop if totalmtna<10-
Sample
Forgive me if my question seems trivial for you.
Best,
Rafal
As part my study, I am aggregating assets of "divisions" (fundno) of "companies" (portno) to keep only these companies that have at least 10 mln assets, when all divisions are summarized in a month t. If a company does not have a minimum of 10 mln assets it is dropped.
Yet sometimes, the company achieves the 10 mln, but later it might drop below the level. Thus, once it has reached 10 mln, even if in some future months the assets are below 10mln, I would like to keep it in my sample to make it less volatile and to avoid selection bias.
May I kindly ask you for some help on that case?
So far I did:
-egen totalmtna=total(mtna), by (crsp_portno mofd)- and then
-drop if totalmtna<10-
Sample
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input double(crsp_fundno crsp_portno) float mofd double mtna 4278 1000001 566 .3 4276 1000001 534 7.9 4279 1000001 577 22.8 4278 1000001 570 1.4 4273 1000001 526 393.9 4278 1000001 597 5.6 4275 1000001 411 1.385 4276 1000001 561 24.5 4275 1000001 416 1.22 4275 1000001 560 26.9 4275 1000001 468 224.9 4273 1000001 527 395 4276 1000001 568 27.6 4273 1000001 438 272.7 4278 1000001 586 2.4 4273 1000001 410 193.00300000000001 4276 1000001 567 27.4 4276 1000001 578 21.9 4275 1000001 565 27.5 4276 1000001 542 8.7 4273 1000001 523 372.3 4276 1000001 492 110 4279 1000001 548 20.3 4278 1000001 604 7 4275 1000001 465 197.5 4276 1000001 499 85.4 4275 1000001 406 1.428 4276 1000001 601 22.9 4279 1000001 600 173 4276 1000001 491 110.7 4273 1000001 525 384.9 4277 1000001 550 .1 4279 1000001 545 19.4 4273 1000001 402 236.00099999999998 4275 1000001 437 20.777 4277 1000001 548 .1 4275 1000001 492 106 4275 1000001 537 35.2 4273 1000001 413 172.37 4275 1000001 472 196.2 4275 1000001 464 182.6 4275 1000001 443 39.784 4279 1000001 552 23.2 4279 1000001 570 42.5 4276 1000001 513 8.7 4278 1000001 565 .7 4277 1000001 594 3 4276 1000001 559 23.2 4275 1000001 522 39.4 4275 1000001 505 63.7 4275 1000001 519 34.4 4275 1000001 592 12.3 4276 1000001 443 2.327 4279 1000001 549 19.7 4273 1000001 444 489.257 4276 1000001 597 20.3 4277 1000001 553 .1 4273 1000001 427 162.245 4275 1000001 581 20.4 4273 1000001 593 150.70000000000002 4275 1000001 523 41.6 4275 1000001 490 100.9 4275 1000001 474 191.9 4276 1000001 521 8.6 4273 1000001 540 348.7 4278 1000001 551 .1 4277 1000001 556 .1 4276 1000001 462 208.507 4273 1000001 389 280.808 4273 1000001 423 143.93099999999998 4273 1000001 462 1335.3780000000002 4273 1000001 598 158.4 4276 1000001 501 74.8 4276 1000001 457 187.313 4275 1000001 425 1.797 4275 1000001 507 63.3 4275 1000001 471 195.3 4277 1000001 544 .1 4275 1000001 452 145.464 4279 1000001 598 167 4275 1000001 405 1.23 4275 1000001 429 2.301 4275 1000001 446 66.738 4275 1000001 584 17.5 4275 1000001 413 1.365 4279 1000001 604 196.2 4275 1000001 598 13.4 4277 1000001 567 1.1 4275 1000001 403 .095 4278 1000001 576 2 4276 1000001 484 116.7 4279 1000001 603 213.6 4278 1000001 548 .1 4275 1000001 481 169.4 4277 1000001 597 3.6 4276 1000001 512 8.9 4278 1000001 564 .7 4276 1000001 580 28 4273 1000001 568 298.1 4276 1000001 498 93.9 end
Best,
Rafal
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