I do run into an issue when i try to hold my monthly dates fix in a panel regression. My monthly data goes from 2010m2 to 2017m12 and my company IDs from 1 to 36. This is how I set up my panel data and run the regression where I hold my monthly data as fix.
Code:
xtset company monthly_date, monthly xtreg rirf smb hml rmrf logfund i.monthly_date, fe
Code:
692 to 695 omitted because of collinearity
Could there be an issue with my monthly_dates since it includes the year as well?
This is my dataset
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float monthly_date double(smb hml rmrf) float logfund byte(company cdo) float(rirf count) 601 -.036514175869505734 .0025293933861673763 .033348853308805326 -.10161838 1 1 .00900477 95 602 -.0215275974788165 .01524125748892807 .0671608830527568 -4.1915917 1 1 -.066759616 95 603 .05550790308483817 .016953214795139483 -.014319209221417939 4.086231 1 1 .008650292 95 604 -.016084222905528123 -.02544223358694256 -.06268477647586279 . 1 1 -.10051205 95 605 .02654983178013808 -.026604682410637286 -.04670257776458653 . 1 1 .00862416 95 606 -.00886170225805974 .0027967609693756654 .06855798416035297 .8645698 1 1 .09878013 95 607 -.011097842408922651 -.007216067466606142 -.002605998486428396 -3.3417 1 1 -.01486315 95 608 .01182346043102811 .00733166483484201 .06504451846776926 -.9084993 1 1 .026974116 95 609 .012117052096444971 .01198267355369398 .024898367040149028 1.5605234 1 1 .02062775 95 610 -.006399954583929786 -.0010655676616467182 -.02294212419408337 . 1 1 -.0201264 95 611 .019644539618828505 .017975768239058894 .07101945566406642 . 1 1 .009254899 95 612 .01077754621823239 .04483825069637799 -.0057110701052867086 . 1 1 .06898722 95 613 -.029092239543648753 -.0028042045008483526 .023532975618520524 2.1314764 1 1 .011119372 95 614 .01230163857190266 -.02233653236390789 -.008534058966924718 -4.7492657 1 1 -.0575213 95 615 .02613016784821751 -.02895988958783636 .030606216620311155 3.454747 1 1 .06345803 95 616 .009289561401437193 -.018097620265274648 -.007607569331971931 -1.655642 1 1 -.036296807 95 617 .00002914416762892988 -.01876131940307323 -.00491498049572503 -2.685545 1 1 -.05022915 95 618 .008036222380935987 -.015927560541959984 -.022461609715633934 -1.7793577 1 1 -.017468331 95 619 -.034311907281683075 -.03593227335451528 -.06929402493718684 -.016998496 1 1 -.09608927 95 620 -.005623074355629684 -.0037081138111124887 -.050484771738572354 2.930478 1 1 -.11443503 95 621 -.04171612828532815 .03736264272951367 .07857916734233927 . 1 1 .13584907 95 622 -.02693544312619141 -.020497889685058775 -.004034888475733633 . 1 1 -.10499 95 623 -.030261232599096095 -.011027060354750633 .008235358990462016 1.597355 1 1 -.01898357 95 624 .06815461747411422 .018008271927890743 .02686230474442275 .2579462 1 1 .09503626 95 625 .03332802232021279 .010554173727011423 .04256108985570095 1.622247 1 1 .06088224 95 626 .03258665022769277 -.02638991921262206 -.009821751454205163 1.5921386 1 1 .014433577 95 627 -.006723463055800775 -.013646608332801714 -.003627949879624226 -.0959006 1 1 .01654744 95 628 -.007647472958901345 -.0446909047614286 -.06825410085641948 -1.9475297 1 1 -.12108926 95 629 -.01015187422923272 .02149253541855473 .04793511731582378 1.7317373 1 1 .121951 95 630 -.00839674525972568 .0038843329882057107 .013070814455744983 -1.415052 1 1 -.04969415 95 631 .022109671189466315 -.004532378270757396 .021941545201706214 2.284748 1 1 .04921225 95 632 .036389738036252166 .006986563554366151 .010641840379512768 -3.452483 1 1 .06512122 95 633 .007291517991277678 .02091703975561352 .010161542555200631 .4359791 1 1 .06901934 95 634 -.004706083792818343 -.023014286668762058 .017360576800751426 .27342716 1 1 .04181667 95 635 .039838922492127865 .036944795977378986 .009589810546145605 1.1399254 1 1 .0286327 95 636 -.01047002895328017 .007491489230127241 .06350787766650834 -.1870548 1 1 .08035851 95 637 .021440265952123522 -.03851744839277014 .022479996348479636 -.5839676 1 1 -.02321159 95 638 .004467927620971997 -.030007977856374095 .013790078065550881 .7561522 1 1 -.023453426 95 639 .007187433774620971 .007571860114914886 .005541814749907115 -.5541095 1 1 .02617436 95 640 .018998745903347946 .004076869567070658 .028857446712000634 .7699007 1 1 .01356897 95 641 .029646761754481957 -.013256487898461962 -.050186404013339514 .05071711 1 1 -.06037876 95 642 .011184472446057414 .0161777750039964 .0675494806732666 .7218434 1 1 .09575707 95 643 .029326422459260888 -.0012290111232412804 -.02237600810842366 -2.3478177 1 1 -.069222786 95 644 .012946069141060154 .024081010093778353 .010870124366911593 3.21029 1 1 .0363553 95 645 -.0031673632064038912 .008939541134347289 .04262777652538041 -.2583155 1 1 .019869646 95 646 .01729014471928265 -.0029961459178782244 -.007217252937173013 -.21119948 1 1 .01903418 95 647 .009957719460398126 .005753078839537089 .018149939209104682 -1.2031468 1 1 -.01801914 95 648 .05117161536252421 .012536805753994148 -.030824471928474373 1.60728 1 1 -.06105831 95 649 -.010406512922892372 .0064731877085343545 .052111414023473746 -.3218664 1 1 .023789003 95 650 .002818461825582673 -.025215630343872177 -.02640462774782537 2.3768537 1 1 -.022286864 95 651 -.05069939558569984 .037715904556980026 .02134724869082838 -2.227464 1 1 .00688445 95 652 -.006481343126716534 -.01954972008639737 .013459540114304724 -1.7826566 1 1 .04431939 95 653 -.006273052946618607 .009364433876928778 -.013167212887771784 2.818183 1 1 -.03978315 95 654 -.0004718323919503699 .018827422385349214 -.0033372295379971995 -.10404377 1 1 .05949596 95 655 .00032042844890393246 -.01865599288963321 .02119507531754583 -1.113073 1 1 .01691253 95 656 .0050589203097871115 -.010805213440073248 -.02810894718432133 -.2348104 1 1 -.06302201 95 657 -.010312131725831461 -.013780855157571461 -.007201302475405735 1.9372303 1 1 .017601803 95 658 -.021015179237970427 -.018125270293037052 .028877005101984876 -.54536074 1 1 -.02529287 95 659 .039447237200893465 .0005183292481098396 -.01629614057446971 -.54531413 1 1 -.04905805 95 660 -.031547864978734096 -.023463569249313462 .02595494603411508 .602177 1 1 -.03548355 95 661 .014401264138617082 .031695393074570526 .03694463773913359 -1.9047877 1 1 -.02588804 95 662 .021180274592925485 -.014069639222224472 -.017026400861084423 .9617122 1 1 -.02329002 95 663 -.0015417348751962285 .01573314287536166 .03000143239507591 2.664853 1 1 .16848493 95 664 .03836922633755008 -.021919003631563592 .013106775549405203 -3.398118 1 1 -.036418404 95 665 .04553317787241746 -.011647200365225773 -.057890170056590584 1.7016034 1 1 -.05683103 95 666 .0008566452210352163 -.03970912756107644 .023582996873041884 -.3471177 1 1 .008551351 95 667 .0332395147634645 -.018284622970875478 -.053605934227328844 .48566735 1 1 -.1084181 95 668 -.0035941715390133944 -.039068628837402086 -.027711616304930353 -.33487836 1 1 -.05348196 95 669 -.039522921940401856 .026294645993469257 .04656962874037118 -1.0604249 1 1 .05068932 95 670 -.009071788690842039 -.03401955315799056 .005316195898865672 2.3604498 1 1 .016334798 95 671 .025810807329112468 -.008845475605861842 -.013110171787779734 -1.0584207 1 1 -.008863819 95 672 -.04980502074428275 .01009454707728813 -.031215305984526154 -.2067911 1 1 -.11678335 95 673 -.02207787200947993 -.021563677900521893 .007640342126203237 -1.201201 1 1 -.08310047 95 674 .01113350943691084 .014586873773870785 .01901043501083355 1.261201 1 1 .005262943 95 675 -.02366443699028754 .04009040587575487 .010997352266630012 -.25275686 1 1 .06252409 95 676 .028812074998646575 -.013168133572902255 .006473111237397244 .5999759 1 1 -.007415673 95 677 -.14775208707903628 .008502035614135435 .02788164497814205 -1.5793946 1 1 -.03883302 95 678 .04382344719109804 -.04147098269910863 .039799088113590564 .9965172 1 1 .0551574 95 679 .03471075678566517 -.004561228311805164 .018794482530042567 .3449778 1 1 .14002751 95 680 -.007581936228231723 .0012440462001456504 .016791902351763532 -.6039599 1 1 .01698872 95 681 -.02933695985455939 .05235982772270942 .005482367087739082 .7865248 1 1 .013802608 95 682 .04076320443415304 .028433620610781876 -.01636625715321438 -1.1880202 1 1 .05479895 95 683 .004319939178638589 .004299526987199417 .050107000587825246 -.7444353 1 1 .022772023 95 684 .010162926767272982 .01432264386103109 -.003427903207179228 2.6936486 1 1 .04825846 95 685 -.014053917875231997 -.02866341212899485 .031047991880304382 -2.1482768 1 1 -.030404136 95 686 .01131645057252604 -.009112925992691728 .012224722316625414 1.8258836 1 1 .011650962 95 687 .040778794967030386 -.002145789106071043 -.003751498469118819 -.8791324 1 1 .011682705 95 688 -.018531407308152927 -.014771428692268834 .043574759204644486 -1.0940979 1 1 .07134932 95 689 .008212105184067018 .014697217808404588 -.02479842717326819 1.9173255 1 1 .05985358 95 690 .01688821749905164 .04676639789030443 .01155920170391922 -.25643367 1 1 .079426 95 691 -.008357128740045133 -.0005543163262659943 .013753982825459143 .8859343 1 1 -.021450344 95 692 .024712721473576324 -.003569915515021286 -.004474118376849856 -.2330929 1 1 .022434713 95 693 -.0072434902404322375 -.001500686231827311 .018372140165074713 .26410604 1 1 -.0042443913 95 694 .007245510855860056 .01574284157613552 -.016853037219334177 1.2233366 1 1 .018644895 95 695 -.019623897710339306 .02061271926966939 .04747781880020718 -1.9489802 1 1 .04335742 95 601 -.036514175869505734 .0025293933861673763 .033348853308805326 -.10161838 2 1 .1022899 95 602 -.0215275974788165 .01524125748892807 .0671608830527568 -4.1915917 2 1 .14836912 95 603 .05550790308483817 .016953214795139483 -.014319209221417939 4.086231 2 1 -.05310606 95 604 -.016084222905528123 -.02544223358694256 -.06268477647586279 . 2 1 -.14159651 95 605 .02654983178013808 -.026604682410637286 -.04670257776458653 . 2 1 -.08731487 95 end format %tm monthly_date
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