I work on a regression and I am not quite sure how to code it properly. Basically my regression looks like this (without dummy variable)
Code:
xtset company modate xtreg rirf rmrf smb hml cma rmw zfund
I am not sure how to add the dummy variable into the regression. My solution would be either
Code:
xtreg rirf rmrf smb hml cma rmw zfund cdo
Code:
xtreg rirf rmrf smb hml cma rmw zfund if cdo == 1
After applying the regression I have a question regarding intepretating the results. I know this is not a Stata Coding question but maybe someone can help me with the interpretation. Basically I want to interpretate the effect of zfund*cdo on the rirf (The smb hml cam rmw results are irrelevant for this case).
Should I look at the correlation of zfund and cdo to analyse the combined effect of cdo and zfund on rirf ? I hope someone can help me out as I am very confused about the interpretation of the table with a dummy variable.
Thanks to everyone
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(modate zfund mktrf smb hml rmw cma rf) int company byte(cdo bank) float(ret_us count rirf rmrf) 624 -1.0642962 5.05 2.1 -.99 -2.05 -1.41 0 1 1 1 .2823721 97 .2823721 -2.05 625 -1.1153159 4.42 -1.69 .32 -.38 -.06 0 1 1 1 .1192195 97 .1192195 -.38 626 -1.118736 3.11 -.51 1.19 -.57 .81 0 1 1 1 .20075314 97 .20075314 -.57 627 -1.1402786 -.85 -.51 -.8 1.26 .67 0 1 1 1 -.1525615 97 -.1525615 1.26 628 -1.0566843 -6.19 -.03 -.78 2.5 2.41 .01 1 1 1 -.09245268 97 -.10245268 2.49 629 -.968369 3.89 .94 .63 -1.26 .32 0 1 1 1 .1129328 97 .1129328 -1.26 630 -.9747435 .79 -2.68 -.07 .93 .1 0 1 1 1 -.10269023 97 -.10269023 .93 631 -1.1112053 2.55 .43 1.21 -1.42 -.72 .01 1 1 1 .0885586 97 .0785586 -1.43 632 -.57883817 2.73 .65 1.53 -1.32 1.6 .01 1 1 1 .10652078 97 .09652078 -1.33 633 -1.0946654 -1.76 -.82 3.68 -1.5 2.27 .01 1 1 1 .05549365 97 .04549365 -1.51 634 -1.098425 .78 .31 -.94 .39 .92 .01 1 1 1 .05793252 97 .04793252 .38 635 -1.1478089 1.18 1.88 3.52 -1.79 .89 .01 1 1 1 .17860857 97 .16860856 -1.8 636 -1.0501254 5.57 .55 .91 -1.72 1.46 0 1 1 1 -.02497326 97 -.02497326 -1.72 637 -.9873649 1.29 -.36 .07 -.65 .47 0 1 1 1 -.007075083 97 -.007075083 -.65 638 -.9471298 4.03 .85 -.2 .55 1.32 0 1 1 1 .08459456 97 .08459456 .55 639 -.9412989 1.55 -2.29 .55 .13 .48 0 1 1 1 .010677938 97 .010677938 .13 640 -.7633607 2.8 1.99 2.65 -2.01 -.74 0 1 1 1 .10966566 97 .10966566 -2.01 641 .003116382 -1.2 1.35 -.02 -.35 -.02 0 1 1 1 -.05784499 97 -.05784499 -.35 642 -.9454608 5.65 1.81 .58 -1.33 .55 0 1 1 1 .13530035 97 .13530035 -1.33 643 -.7979175 -2.71 -.03 -2.67 .59 -2.18 0 1 1 1 -.032880723 97 -.032880723 .59 644 -.5600812 3.77 2.65 -1.19 -.6 -1.26 0 1 1 1 -.02197802 97 -.02197802 -.6 645 -.8588011 4.18 -1.49 1.2 2.78 .84 0 1 1 1 .01232065 97 .01232065 2.78 646 -.9537788 3.13 1.33 .31 .13 .07 0 1 1 1 .13242933 97 .13242933 .13 647 -.7821412 2.81 -.58 -.05 -.47 .09 0 1 1 1 -.01517821 97 -.01517821 -.47 648 -.8911942 -3.32 .58 -2.02 -3.93 -1.36 0 1 1 1 .0757885 97 .0757885 -3.93 649 -.8099153 4.65 .11 -.37 -.24 -.41 0 1 1 1 -.013131475 97 -.013131475 -.24 650 -.4301951 .43 -1.13 4.91 2.17 1.83 0 1 1 1 .04113565 97 .04113565 2.17 651 .21623185 -.19 -4.13 1.11 3.53 1.02 0 1 1 1 -.11977196 97 -.11977196 3.53 652 -.15925674 2.06 -1.91 -.12 .03 -1.05 0 1 1 1 0 97 0 .03 653 -.8320168 2.61 3.09 -.68 -1.91 -1.95 0 1 1 1 .015854314 97 .015854314 -1.91 654 -.7724395 -2.04 -4.27 -.02 .92 .47 0 1 1 1 -.007810143 97 -.007810143 .92 655 -.7282271 4.24 .3 -.58 -.61 -.7 0 1 1 1 .05508108 97 .05508108 -.61 656 -.4211756 -1.97 -3.75 -1.31 1.24 -.53 0 1 1 1 .06295789 97 .06295789 1.24 657 .4413366 2.52 3.8 -1.82 -.48 -.19 0 1 1 1 .006446443 97 .006446443 -.48 658 -.8405004 2.55 -2.29 -2.87 1.49 .2 0 1 1 1 -.006991793 97 -.006991793 1.49 659 .29060632 -.06 2.86 2.18 -1.16 .88 0 1 1 1 .0529222 97 .0529222 -1.16 660 -.51582384 -3.11 -.88 -3.5 1.68 -1.65 0 1 1 1 -.1531569 97 -.1531569 1.68 661 -.4917158 6.14 .23 -1.89 -1.16 -1.78 0 1 1 1 .04355939 97 .04355939 -1.16 662 -.05449453 -1.12 3.04 -.43 .1 -.51 0 1 1 1 -.02349115 97 -.02349115 .1 663 1.7682045 .59 -3.05 1.84 -.04 -.45 0 1 1 1 .035089232 97 .035089232 -.04 664 .1549665 1.36 .81 -1.19 -1.82 -.74 0 1 1 1 .035777695 97 .035777695 -1.82 665 .9248865 -1.53 2.86 -.76 .42 -1.5 0 1 1 1 .03456662 97 .03456662 .42 666 -.51957136 1.54 -4.51 -4.19 .1 -2.5 0 1 1 1 .05052426 97 .05052426 .1 667 -.9541405 -6.04 .39 2.63 .69 1.24 0 1 1 1 -.08612797 97 -.08612797 .69 668 2.0981243 -3.07 -2.77 .51 1.86 -.45 0 1 1 1 -.04350589 97 -.04350589 1.86 669 -.3357938 7.75 -2.18 -.21 .87 .41 0 1 1 1 .0770238 97 .0770238 .87 670 .9741321 .56 3.37 -.53 -2.64 -1.08 0 1 1 1 .03873625 97 .03873625 -2.64 671 -.7577139 -2.17 -3 -2.52 .45 .04 .01 1 1 1 -.031684853 97 -.04168485 .44 672 .1876454 -5.77 -3.41 1.98 2.81 3.05 .01 1 1 1 -.1598321 97 -.16983213 2.8 673 .27772656 -.08 .98 -.56 3.34 2.12 .02 1 1 1 -.11457096 97 -.13457096 3.32 674 -.621363 6.96 1.08 1.06 .77 -.08 .02 1 1 1 .08389845 97 .063898444 .75 675 -.5156671 .92 1.17 3.3 -2.89 2.01 .01 1 1 1 .0769271 97 .0669271 -2.9 676 -.669097 1.78 -.71 -1.72 -1.19 -2.52 .01 1 1 1 .01579454 97 .00579454 -1.2 677 -.18034604 -.05 .5 -1.46 1.41 1.98 .02 1 1 1 -.09974915 97 -.11974914 1.39 678 -.5001811 3.95 2.61 -1.23 1.14 -1.24 .02 1 1 1 .091932 97 .071932 1.12 679 -.31458 .5 1.67 3.24 -1.81 -.35 .02 1 1 1 .1190519 97 .0990519 -1.83 680 -.3065128 .25 1.78 -1.2 -2.13 -.06 .02 1 1 1 -.030364247 97 -.05036425 -2.15 681 -.006094114 -2.02 -4.08 4.04 .91 .21 .02 1 1 1 .05431573 97 .034315735 .89 682 -.9032302 4.86 6.8 8.15 -.07 3.78 .01 1 1 1 .28454354 97 .27454355 -.08 683 -.07185087 1.81 .41 3.49 1.14 -.29 .03 1 1 1 .0464054 97 .016405398 1.11 684 -.5030931 1.94 -1.34 -2.77 -.5 -.94 .04 1 1 1 .02443303 97 -.01556697 -.54 685 .5648496 3.57 -2.18 -1.78 .27 -1.74 .04 1 1 1 .09010552 97 .05010552 .23 686 .56005853 .17 .8 -3.25 .8 -1.04 .03 1 1 1 -.04135505 97 -.07135505 .77 687 .4321061 1.09 .48 -2.05 1.96 -1.58 .05 1 1 1 -.01059837 97 -.06059837 1.91 688 .452172 1.06 -3.1 -3.69 1.02 -1.93 .06 1 1 1 -.03663163 97 -.09663163 .96 689 -.10064785 .78 2.46 1.43 -2.23 -.05 .06 1 1 1 .08255441 97 .022554416 -2.29 690 -.5032098 1.87 -1.65 -.33 -.77 -.21 .07 1 1 1 -.005772489 97 -.07577249 -.84 691 1.514892 .16 -1.8 -2.3 .14 -2.42 .09 1 1 1 -.004557754 97 -.09455775 .05 692 -.3397476 2.51 4.79 3.11 -1.38 1.64 .09 1 1 1 .06069768 97 -.02930232 -1.47 693 .58235365 2.25 -1.96 .07 .93 -3.35 .09 1 1 1 .08089957 97 -.009100437 .84 694 -.27973685 3.12 -.33 -.06 3.3 .05 .08 1 1 1 .032858547 97 -.04714145 3.22 695 .00677294 1.06 -1.03 .27 .72 1.67 .09 1 1 1 .04792359 97 -.04207641 .63 696 .6013967 5.58 -3.2 -1.24 -.82 -.86 .11 1 1 1 .08401144 97 -.025988564 -.93 697 .011041225 -3.65 .37 -1.02 .58 -2.23 .11 1 1 1 .003124674 97 -.10687532 .47 698 1.256413 -2.35 3.6 -.14 -.45 0 .12 1 1 1 -.06217043 97 -.1821704 -.57 699 .4582822 .29 .96 .46 -2.33 1.18 .14 1 1 1 -.002333806 97 -.1423338 -2.47 700 2.458111 2.65 4.74 -3.15 -2.01 -1.44 .14 1 1 1 -.02540194 97 -.16540194 -2.15 701 .7331362 .48 .89 -2.27 .83 .34 .14 1 1 1 -.0292688 97 -.1692688 .69 702 .3634799 3.19 -1.95 .58 1.53 .4 .16 1 1 1 .09542326 97 -.06457674 1.37 703 1.2807873 3.44 .62 -3.87 -.15 -2.47 .16 1 1 1 .0016172507 97 -.15838274 -.31 704 .3231561 .06 -2.47 -1.7 .59 1.26 .15 1 1 1 -.04289338 97 -.1928934 .44 705 .1547048 -7.68 -4.57 3.62 .86 3.42 .19 1 1 1 -.06653293 97 -.25653294 .67 706 .12342313 1.69 -.79 .2 -.63 .33 .18 1 1 1 .032727633 97 -.14727238 -.81 707 .8793025 -9.55 -3.01 -1.88 -.09 .15 .19 1 1 1 -.12744075 97 -.31744075 -.28 708 .6319562 8.41 3.07 -.56 -.65 -1.36 .21 1 1 1 .1554367 97 -.05456328 -.86 709 1.2497272 3.4 1.79 -2.72 .09 -1.47 .18 1 1 1 .02669617 97 -.15330383 -.09 710 .2043876 1.1 -3.56 -4.2 .86 -1.03 .19 1 1 1 -.05123946 97 -.24123946 .67 711 2.945461 3.96 -1.17 2 1.64 -2.18 .21 1 1 1 .10837473 97 -.10162526 1.43 712 3.196913 -6.94 -1.52 -2.15 -.54 1.78 .21 1 1 1 -.13015136 97 -.3401514 -.75 713 .20777777 6.93 .33 -.82 .99 -.38 .18 1 1 1 .09609094 97 -.08390907 .81 714 1.672993 1.19 -1.9 .3 -.16 .34 .19 1 1 1 .05792966 97 -.13207033 -.35 715 1.1428357 -2.58 -3.3 -4.93 .43 -.88 .16 1 1 1 -.10332292 97 -.26332292 .27 716 1.2313054 1.43 .26 6.78 1.99 3.5 .18 1 1 1 .06712751 97 -.1128725 1.81 717 .9599003 2.06 .21 -2.09 .25 -.99 .15 1 1 1 .07199332 97 -.07800668 .1 718 .58086735 3.87 .5 -1.87 -1.58 -1.24 .12 1 1 1 .06555604 97 -.05444396 -1.7 719 3.268818 2.77 .96 1.93 .09 1.29 .14 1 1 1 .0627736 97 -.0772264 -.05 624 -1.0642962 5.05 2.1 -.99 -2.05 -1.41 0 2 1 1 .08692265 97 .08692265 -2.05 625 -1.1153159 4.42 -1.69 .32 -.38 -.06 0 2 1 1 .07576478 97 .07576478 -.38 626 -1.118736 3.11 -.51 1.19 -.57 .81 0 2 1 1 .07316217 97 .07316217 -.57 627 -1.1402786 -.85 -.51 -.8 1.26 .67 0 2 1 1 .027214566 97 .027214566 1.26 end format %tm modate
0 Response to Running a Regression with a Dummy Variable (1,0)
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