How to divide my data set into sub-sample(s) and generate a variable leader/ follower for examining mimicking behavior

[muhammad ayaz]

Hello Dear professor.
I have a quarry about a problem. I have the following data consist of two groups variables. The first one is the firms' specific variables( bl, prof, tang,size liqu, bk, nts,gao andieqshok) and the second group is the peer firms average characteristics (pbl, pprof, ptang, psize, pliqu, pbk, pnts, pgoa and peqshock). My basic objectives are to divide my data into sub-sample and create leader and follower firms based on size, prof and goa. Further, i want to examine mimicking behavior between leader and follower ( who follow whom). My limited knowledge donot enable me. so kindly if possible assist me. Your valuable insight will be highly appreciated. Sorry for inconveniences.

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* Example generated by -dataex-. To install: ssc install dataex
clear
input int(companyid year) float(bl pbl prof tang size liqu bk nts gao ieqshok pprof ptang psize pliqu pbk pnts pgao iaeqshock)
 1 2011  .24794 .393869   .08435 .427675  7.7274 1.70839 .020751 .036037 -3.78408 .000085   .04356  .36046 5.29694  2.7034  .327713 -.036451  1.00265 .000152
 1 2012 .228582 .398956  .099142 .412992  7.7274 1.67297 .020751 .037425 -1.77693 .000453  .038517 .367371 5.30874 2.69247 -.005217  .032469  4.60129 .000334
 1 2013  .20635 .378759  .114672 .397599  7.7274 2.00966 .020751 .034749 -1.32234 .000111 -.021454 .362777 5.34636 3.05064  .321999  .032744 -.021547 .000283
 1 2014 .204459 .414312  .123248  .37271  7.7274 2.19686 .020751  .03513  1.24052 .000155  .013539 .361989 5.38515 2.89328  .330657  .032363  1.00265 .000198
 1 2015  .21693 .440635  .082983 .367576  7.7274  1.9417 .020751 .037851 -1.39517 .000085  .040915 .354502 5.46115 3.15969  .321627 -.003254  .003655 .000169
 1 2016 .290245 .391355  .078592 .380793  7.7274 1.10949 .020751 .035431  9.22901 .000068    .0475  .34688 5.50848 3.59625  .312616 -.003254 -1.02486 .000184
 2 2011 .479802 .392521 -.100327 .347442  5.2937 1.62546 .370811  .03803  15.3895 .000037   .04527 .360924  5.2996 2.70389  .325668 -.036451  1.00265 .000153
 2 2012 .538248 .397166 -.100327 .397515 5.18176 1.34115 .414751 .042591 -10.5898 .000225  .039745 .367461 5.32681 2.69439  .325971  .032439  4.65253 .000335
 2 2013 .681036 .377169 -.100327 .383503 4.91558 .849131 .541331 .069776 -20.1742  .00062  .037204 .362858 5.36589 3.05735 -.007452  .032378  5.54665  .00028
 2 2014 .666305 .411642 -.100327 .481143 4.68968 .799558 .678611 .069776 -20.1742 .000104  -.00547 .361362 5.40605 2.90135  .327326  .032155  1.00265 .000198
 2 2015 .222728 .440635  .009438 .522075 4.80972 2.28331 .601944 .042927  12.7543 .000127 -.006981 .353609 5.48128 3.15772 -.007452 -.003254  .003655 .000169
 2 2016 .094859 .392491  .109302 .451085 5.29674 6.24624 .369952 .030994  38.2993 .000101    .0475 .346491  5.5263 3.56848 -.007452 -.003254  1.02548 .000184
 3 2011 .094324 .394763  .096062 .339468 6.94076 8.52213 .071495 .041836  5.18581  .00015  .043492  .36097 5.29694 2.68017  .327409 -.036451  1.00265 .000152
 3 2012 .116487 .399604  .088276 .313943 7.01329 7.15626 .066472 .039101  7.52206  .00062   .03858 .367944 5.31622 2.68017  .327984  .032459  4.54722 .000333
 3 2013 .104639 .379346  .084263 .314325 6.96991 8.30202 .069397 .040393 -4.24555 .000134  .035162 .363258 5.35401 3.01427  .321709  .032711 -.021547 .000283
 3 2014 .114972 .414829  .088111 .314303 6.92337 7.00414 .072685 .043838 -4.54665 .000136  .013742 .362327 5.39314 2.86549  .330657  .032312  1.00265 .000198
 3 2015 .151004 .440635  .112954 .331554  6.8298 4.61005 .079796 .049306 -8.93337 .000091  .040742  .35471  5.4696 3.14427  .321275 -.003254  .003655 .000169
 3 2016  .16431 .392087  .122701 .345153 6.73981 4.00293 .087272  .05761 -8.60539 .000091    .0475 .347086 5.51796 3.58145   .31221 -.003541 -1.02486 .000184
 4 2011  .22289 .394015  .160909 .221794 6.24579 2.66667 .143116 .031622  12.8301 .000131  .042871  .36165 5.29694 2.69783  .326992 -.036451  1.00265 .000152
 4 2012 .167266  .39931  .160909 .193911 6.30473 3.83517 .134907 .031843   6.0707 .000189  .038065 .368265 5.32031 2.68017  .327588  .032501  4.55566 .000336
 4 2013 .130649 .379196  .160909  .29378 6.33324 5.09858 .131106  .03104   2.8917 .000164 -.021454 .363377 5.35769 3.03279  .321353  .032765 -.021547 .000283
 4 2014 .139145 .414689  .160909 .320402 6.39488 4.76704  .12326 .032977  6.35872 .000147  .013201 .362291 5.39619 2.87842  .330536  .032375  1.00265 .000198
 4 2015 .213642 .440635  .137397 .301975 6.56921 3.31971 .103521  .03397  19.0441 .000083  .040601 .354881 5.47111 3.15173  .321137 -.003254  .003655 .000169
 4 2016 .149251 .392174  .126759 .349349 6.52877  5.4021 .107777 .036114 -3.96252 .000118    .0475 .347062 5.51918 3.57336  .312092 -.003254 -1.02486 .000184
 5 2011 .272831 .393725  .057387 .163379  5.6177 2.46031 .268294  .01818  6.35244 .000069  .043716 .361988 5.29772 2.69903  .326264 -.036451  1.00265 .000152
 5 2012 .274399 .398691 -.012078 .218252 5.57698 2.59995 .279518 .018787 -3.99012  .00062   .03916 .368265 5.32452 2.68711  .326753  .032577  4.61416 .000331
 5 2013 .223756 .378658 -.024764 .224461 5.44896 3.22101 .317764 .021173  -12.016 .000215  .035792 .363777 5.36281 3.04364  .320274  .032822 -.021548 .000282
 5 2014 .136146 .414707  .049861 .075372 5.27896 6.66688 .376733  .01619 -15.6341 .000075  .013963 .363912 5.40264 2.86744  .329071  .032472  1.00265 .000198
 5 2015 .093913 .440635        0 .075372 5.48656 8.52213 .306183 .005721  23.0729 .000094 -.006981 .356488 5.47736 3.08599  .319966 -.003254  .003655 .000169
 5 2016 .093913  .39277  .015456 .075372 5.46149 8.52213 .313957 .005721 -2.47612 .000135 -.021492 .348937 5.52534  3.5071 -.007452 -.003254 -1.02486 .000184
 6 2011 .093913 .395073  -.03246 .663208 5.28902 7.95497 .373523 .015438  7.63819 .000103  .044235 .359099 5.29963 2.68017  .325653 -.036451  1.00265 .000152
 6 2012 .093913 .399999 -.017991 .649653 5.29994 7.02499 .369546 .012804  1.09766 .000242  .039195 .366003 5.32612 2.68017  .326232  .032611  4.58458 .000335
 6 2013 .093913  .37974 -.009577 .658118 5.27224 8.52213 .380009    .014 -2.73207 .000183  .035704 .361271 5.36383 3.01005  .319914  .032822 -.021547 .000282
 6 2014 .093913 .415297  .018357 .636545 5.29577 8.52213 .371254 .013033  2.38131 .000186  .014145 .360464 5.40255 2.84606  .329102   .03249  1.00265 .000198
 6 2015 .093913 .440635  .001432 .075372 5.60738 8.52213 .271922  .01302   36.562 .000078 -.006981  .35639 5.47667 2.91318  .320164 -.003254  .003655 .000169
 6 2016 .093913 .392895 -.020669 .075372 5.51112 8.52213 .299467 .008115  -9.1767 .000125 -.021492 .349023 5.52506 3.41223 -.007452 -.003254 -1.02486 .000184
 7 2011 .633364 .391629  .033307 .591181 7.47041 1.21978 .042216 .009749  37.1848 .000038  .043855 .359515 5.29694 2.70625  .327579 -.036451  1.00265 .000153
 7 2012 .592342 .396853  .007558 .692048 7.39526 1.05597 .045519 .021555 -7.23896 .000052  .039047 .365708 5.31401 2.69604 -.005217  .032561  4.63305 .000336
 7 2013  .66446 .377169 -.020276 .692048 7.36405 .762605 .046974 .033093 -3.07274 .000119  .035766 .360923 5.35174 3.05985  .321839  .032753 -.021547 .000283
 7 2014 .704567 .411021 -.014064 .692048 7.26145 .762605 .052064 .035208 -9.75205 .000179  .014332 .359882 5.39118 2.90391  .330657  .032362  1.00265 .000198
 7 2015 .423234  .43954  .012416 .578693 6.53692 1.03581 .107476 .025694 -20.1742 .000043 -.006981 .353282 5.47129 3.16493  .321115 -.003254  .003655 .000169
 7 2016 .460266 .390366  .010049 .579276 6.55047 1.07472 .106059 .025943  1.36389 .000404 -.021492 .346491 5.51905 3.59625  .312101 -.003254 -1.02486 .000183
 8 2011 .218772 .394039  .106578 .475406 7.08693 2.72139 .062018 .039588  1.89943 .000218  .043431 .360184 5.29694 2.69752  .327464 -.036451  1.00265 .000152
 8 2012 .263261 .398755  .100168 .477767 7.18764 2.61424 .056034 .037897  10.5961 .000235  .038512 .366997 5.31521 2.68703 -.005217  .032466  4.52935 .000335
 8 2013 .239827 .378565   .10029 .447449 7.21463 3.14282 .054494 .038874  2.73556 .000272  .035069 .362488  5.3526 3.04409  .321796   .03272 -.021547 .000282
 8 2014 .279212  .41388  .106525 .453286 7.33183 2.59935  .04842 .029499  12.4339 .000097  .013635 .361523 5.39078 2.89095  .330657  .032395  1.00265 .000198
 8 2015 .294547 .440284   .07867 .485346 7.44445 2.26992 .043207 .029414  11.9206 .000122   .04094 .353821 5.46605 3.15779  .321486 -.003254  .003655 .000169
 8 2016 .322984 .391164  .081193  .44977 7.61662 2.03576  .03634 .032764  18.7883 .000108    .0475 .346491 5.51289 3.59282  .312505 -.003254 -1.02486 .000184
 9 2011 .498503 .392413  .048009 .615192 7.02101 1.04237 .065854 .035743   21.037 .000188   .04377 .359376 5.29694 2.70728  .327441 -.036451  1.00265 .000152
 9 2012 .508391 .397339  .040101 .586236 7.13574 1.02276  .05872 .038116  12.1574 .000115  .038859  .36637 5.31551 2.69623 -.005217  .032465  4.52028 .000336
 9 2013 .503391 .377169  .045708 .594036 7.12808 1.01399 .059174 .045004 -.762859  .00033  .035385 .361641  5.3531  3.0564  .321769  .032684 -.021547 .000282
 9 2014 .450319 .412891  .033258 .654948 7.30834 .957111  .04941 .036942  19.7525 .000227  .014059 .360358 5.39091 2.90044  .330657  .032352  1.00265 .000197
 9 2015 .469327 .439274   .03139 .640862 7.36028 .961281 .046909 .036138  5.33097 .000219 -.006981 .352922 5.46653 3.16536  .321465 -.003254  .003655 .000168
 9 2016 .453454 .390406  .043153 .631776 7.36685 .987197 .046601 .033858  .660065 .000049 -.021492 .346491 5.51433 3.59625  .312445 -.003254 -1.02486 .000185
10 2011 .163274 .394362   .03302  .39411 5.43734  6.0162 .321288 .049737  1.63758 .000089  .043857 .360654 5.29877 2.68017  .325956 -.036451  1.00265 .000152
10 2012 .151249 .399403  .008326 .453211  5.3927 6.62744 .336045 .050224 -4.36542 .000151  .039042 .367139 5.32559 2.68017  .326426  .032395  4.61634 .000336
10 2013 .163343 .379007 -.019869  .43921 5.36385 5.66776 .345972 .059458   -2.844 .000123  .035764 .362536  5.3633  3.0295  .320111  .032601 -.021547 .000283
10 2014 .177079  .41447  -.01549  .41689 5.37024 4.94258 .343854 .057497  .641551 .000152   .01434 .361734 5.40212 2.87741  .329261  .032233  1.00265 .000198
10 2015 .261361 .440476 -.007737  .36382 5.43052 3.05866 .323823 .050274  6.21269 .000078 -.006981 .354524 5.47769 3.15324  .319864 -.003254  .003655 .000169
10 2016 .215364  .39179  .020841 .327087 5.34584 4.01102  .35253 .056782 -8.11944 .000246 -.021492  .34719 5.52601  3.5814 -.007452 -.003541 -1.02486 .000183
11 2011 .505946 .392369 -.006096 .311361 5.11406 1.54582 .445148 .011188 -1.61701 .000065  .044083 .361133 5.30064 2.70435  .325236 -.036451  1.00265 .000153
11 2012 .472709 .397545  -.03008 .477407 5.32601 1.33263 .360212 .007772  23.6083 .000203  .039264 .366999 5.32597 2.69444  .326286   .03264   4.4537 .000336
11 2013 .437614 .377422 -.034041  .53814 5.18437  1.2383 .415111 .013269 -13.2062 .000145  .035846 .361964 5.36434  3.0551  .319711  .032822  5.54665 .000283
11 2014 .327423 .413601   -.0235 .259741 5.07941 1.22488 .461152 .008894 -9.96408 .000146  .014387 .362642  5.4038  2.8989 -.005217  .032514  1.00265 .000198
11 2015 .273295 .440407 -.018054 .308287 5.06066 1.17806 .469986  .00839 -1.85774 .000061 -.006981 .354845 5.47983 3.16411  .319019 -.003254  .003655 .000169
11 2016 .248796 .391596 -.018874 .325688 5.01661 1.23361 .491262 .008376 -4.30898 .000317 -.021492 .347198 5.52792 3.59625  .309875 -.003254 -1.02486 .000181
12 2011 .149408 .394442  .043536 .140164 4.38264 3.33792 .927357 .009869 -.720575 .000115  .043796 .362122  5.3049 2.69393  .322433 -.036451  1.00265 .000152
12 2012 .093913  .39998  .039898 .144178 4.29813 8.52213 1.00938 .010685 -8.10379 .000288   .03886 .368265 5.33191 2.68017  .322534  .032624  4.63807 .000335
12 2013 .093913 .379699  .021221 .139001 4.30386 8.52213 1.00386  .01107  .575025  .00062  .035526 .364271 5.36943 2.91839 -.007452  .032822 -.021547 .000279
12 2014 .164262 .414544  .020874 .097476    4.66 5.82736 .703247 .007261  38.2993 .000115   .01413  .36358 5.40622 2.87229  .327183  .032524  1.00265 .000198
12 2015 .327216 .440095  .043596 .083649 4.91903 2.88647 .542896 .005721  29.5676 .000119 -.006981 .356143 5.48064 3.15423 -.007452 -.003254  .003655 .000169
12 2016 .440066 .390484 -.005273 .080523 6.94629 1.35345 .071516 .005721  38.2993 .000164 -.021492 .348616 5.51676 3.59625  .312301 -.003254  1.23549 .000184
13 2011 .304166 .393542  .075509 .506179 4.30574 3.72653 1.00418 .030368  2.20335 .000223  .043611 .360006 5.30534 2.69167  .321986 -.036451  1.00265 .000152
13 2012 .293011 .398584  .057697 .491853 4.33687 3.11469 .973649 .026456  3.16227 .000261  .038757 .366915 5.33169 2.68414   .32274  .032532  4.57257 .000335
13 2013 .255648 .378474  .071303 .490916 4.31191 3.30977 .998509 .027526 -2.46508 .000196  .035237 .362237 5.36938 3.04313 -.007452  .032786 -.021547 .000282
13 2014 .236923 .414124  .048123 .523774 4.29217  2.5755 1.00938  .02828 -1.95487 .000262  .013973 .361116 5.40835 2.89109   .32536  .032402  1.00265 .000197
13 2015 .176068 .440635  .021204 .537919 4.21544 3.57378 1.00938 .033947 -7.38598 .000077 -.006981 .353517 5.48471 3.15026 -.007452 -.003254  .003655 .000169
13 2016 .233628 .391684  .023732 .489319 4.26685 3.28784 1.00938 .032259  5.27583 .000095 -.021492 .346491 5.52918 3.58558  .306672 -.003254 -1.02486 .000184
14 2011 .450246 .392693  .035965  .17175 5.05421  1.3392 .476422 .018183 -2.22531 .000068   .04384 .361939 5.30099 2.70555  .325054 -.036451  1.00265 .000152
14 2012 .483176 .397484  .015789 .248807 5.11959 1.23665 .446388  .02566  6.75576 .000187  .038999 .368265 5.32717 2.69499  .325788  .032537  4.55168 .000336
14 2013 .512703 .377169  .012083 .236015 5.14595    1.24 .434883 .022412  2.67179 .000168  .035579 .363711 5.36456 3.05509  .319597  .032815 -.021547 .000283
14 2014 .448996 .412898  .039029 .200553  5.2874 1.27038 .377618 .022737  15.1938 .000102  .014025 .362984  5.4026 2.89863  .329065  .032434  1.00265 .000198
14 2015 .430069 .439501 -.006269 .205967  5.2111 1.19968 .407665  .02263 -7.34578 .000248 -.006981 .355436 5.47896 3.16398  .319379 -.003254  .003655 .000168
14 2016 .497739 .390148  .071743  .16287  5.3599  1.3213 .351389 .019116   16.044 .000048    .0475  .34814 5.52593 3.59625 -.007452 -.003254 -1.02486 .000185
15 2011 .305719 .393533  .068107 .153935 7.65673 2.97426 .032296 .014155 -7.62154 .000067  .043654 .362042 5.29694 2.69605  .327637 -.036451  1.00265 .000152
15 2012 .237483 .398904  .077534 .218498 7.64936 3.03087 .032503  .01623 -.734199  .00049  .038642 .368265 5.31254 2.68462 -.005217  .032591  4.59523 .000334
15 2013 .211807 .378727  .101789 .228282 7.66867 3.07147 .031836 .024662  1.95042  .00062  .035061 .363755 5.34998  3.0445  .321927  .032802 -.021547 .000279
15 2014 .221209 .414215  .112475 .206145  7.7274 2.98918 .028017 .034476  13.2533 .000321  .013601 .362952 5.38811  2.8887  .330657  .032366  1.00265 .000197
15 2015  .25913 .440489  .111715 .213281  7.7274 2.50586 .024099 .014959  15.5221 .000145  .040749 .355394  5.4632 3.15643  .321597 -.003254  .003655 .000169
15 2016 .284225  .39139  .102149 .225939  7.7274 2.13996 .020751 .016505  15.3903 .000082    .0475 .347775 5.51021 3.59222  .312595 -.003254 -1.02486 .000184
16 2011 .145193 .394467  .037755 .289208 4.27801 5.36323 .923883 .026367  1.51933 .000078  .043829 .361261 5.30551 2.68216  .322453 -.036451  1.00265 .000152
16 2012 .110535 .399638   .01814 .274676 4.24947 7.64293 .950872 .026246 -2.81426 .000207  .038986 .368171 5.33219 2.68017  .322872  .032534  4.60732 .000335
16 2013 .093913 .379565 -.049294 .309077 4.13975 8.52213 1.00938 .029943 -10.3913 .000382  .035934 .363288 5.37037 2.97152 -.007452  .032772 -.021548 .000281
16 2014 .111645 .414848   .00629 .267881 4.18931 7.31746 1.00938 .028449  5.08067 .000212  .014215 .362595 5.40894 2.86368  .325408  .032401  1.00265 .000197
16 2015 .093913 .440635 -.016319 .266833  4.1164 8.52213 1.00938 .030666 -7.03124 .000058 -.006981 .355084 5.48528 3.09713 -.007452 -.003254  .003655 .000169
16 2016 .124229  .39232 -.100327 .294615 3.92029  7.4009 1.00938 .036081 -17.8079 .000238    .0475 .347378 5.52918 3.56181  .305068 -.003254 -1.02486 .000183
17 2011  .48863  .39247  .051833   .3949  7.7274 .899015 .020751 .010372  3.75742 .000171  .043748  .36065 5.29694 2.70811  .327718 -.036451  1.00265 .000152
17 2012 .434256 .397767  .010753 .426112  7.7274 1.18709 .020751 .010737 -7.75055 .000573  .039028 .367295 5.30994 2.69528 -.005217  .032623  4.63602 .000333
17 2013 .501407 .377169  .011829 .443645  7.7274 .883292 .021727 .011619 -8.60779 .000254  .035581  .36251   5.348 3.05715  .321985  .032822 -.021548 .000282
17 2014 .560524 .412254 -.000633 .456185  7.7274 .912113 .022884 .012535 -5.04054 .000158  .014255 .361506 5.38715  2.9007  .330657  .032493  1.00265 .000198
end

[Wessel de Kroo]

Hey Muhammed,

Maybe it is an idea to start defining exactly what you are trying to do here for yourself and for others. It is quite hard to give you any help without this.

I am guessing your dataset is already divided in subsamples so to speak since companies are divided in to groups following companyid.

again I am unsure of what definitions you use?

A leader company i.e. a company that quite possible invest alot in R&D (research and development). vs a group of company that does not.

maybe try

summarize yourvarhere, detail

for different groupids to get a better sense of what your data is telling you.

good luck

[muhammad ayaz]

Thank you so much Dear Wessel de Kroo for your response. Additionally, i divided my sample using the following command. However, this give me 1,2 and 3 in yearwise. For instance, for year 2011 and 2012, this generated 1, for year 2013 and 14, it assigned 2 and for year 2015-2016 this assigned 3. However, i want 1,2 and 3 by id not by year.

xtile newpsize = Wpsize, nq(3)
xtile newprof = prof, nq(3)

[Wessel de Kroo]

your post:
" Additionally, i divided my sample using the following command." what command exactly?

" However, this give me 1,2 and 3 in yearwise." please give readers an example using dataex. install it using: ssc install dataex.

you can use dataex your_relevant_variables here, in order specifiy relevant variables

your objective:
" however, i want 1,2 and 3 by id not by year." okay but why?

in your first post you state: " My basic objectives are to divide my data into sub-sample and create leader and follower firms based on size, prof and goa."

so you should think about how to define leader and follower. Maybe you can use summary statistic to determine this? Stata has a tab named: Statistics --> summaries.

xtile newpsize = Wpsize, nq(3)

on itself not very usefull here.

This thread here will give you a better understanding: https://www.stata.com/statalist/arch.../msg00494.html


Obtaining you with deciles for size for your firms. only you can decide what suits your objective though.