I have difficulty in adjusting endogeneity after using -probit-. According to the results of Probit, some key independent variables are statistically insignificant like larinstitinv, top5institown and tobinq. But I need most of them to be statistically significant. I have no idea about testing and addressing endogeneity issues. Could anyone tell me how to do that? I would be very grateful for your help.
Below is the data sample and probit result.
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input double permno str10 deal_no float(larinstitinv top5institown totinstitown) double deal_value float(firm_size roa leverage tobinq listar cashpay sharepay fincri cross) 81553 "1642835020" 12.879892 43.6682 78.38927 29 6.329557 .13019961 .3565647 .6251571 0 0 0 0 0 45583 "1652279020" 17.0584 43.51479 89.13196 45 5.666264 .07870138 .23612836 1.1347183 0 1 0 0 0 72961 "1656540040" 6.781873 28.285944 84.72234 38.642 6.418923 .14030671 .04348471 1.0054287 0 0 0 0 1 65226 "1658390020" 6.12166 24.462437 93.58447 29 7.546181 .10109966 .38566875 1.0022842 0 1 0 0 0 63125 "1663476020" 8.642229 23.28393 83.72404 28 6.703382 .0614065 .0731441 .7682497 0 0 0 0 0 11903 "1671237020" 6.991612 23.39074 25.96103 9.8 . .19178738 .0830828 2.6839936 0 1 0 0 0 81061 "1673459040" 12.79749 37.693024 84.89115 95.392 9.840281 .05940879 .06447403 .6662623 1 0 0 0 1 88867 "1673507040" 5.932497 24.273085 84.87262 3.734 5.060143 .2833015 .04826378 . 0 0 0 0 1 24097 "1673733020" .7716496 2.075638 2.2552416 46.413 3.667298 .17375977 .08246053 1.924844 1 0 1 0 0 65330 "1674569020" 7.170807 21.473536 79.95611 800 9.014261 .0822599 .12570418 1.1652516 0 0 0 0 0 65402 "1674815040" 10.55149 32.235672 92.83104 341.469 7.164488 .11835693 .1309662 .9567543 1 1 0 0 1 77862 "1675860020" 12.948956 48.36299 88.49156 104.814 5.502808 .13450159 .2445187 1.1959064 0 0 0 0 0 80098 "1677795020" 7.674511 17.711124 35.937748 53.4 7.04052 .13053194 .1999219 .6190646 0 1 0 0 0 81061 "1678384020" 12.227973 37.693024 84.89115 212.236 9.840281 .05940879 .06447403 .6662623 1 1 0 0 0 80185 "1678411020" 12.501595 30.153524 93.10918 166 6.19017 .27979687 .006004972 3.785605 0 1 0 0 0 41355 "1683537040" 10.37872 28.690155 82.08459 448.868 8.839126 .16121355 .14065683 1.2165036 1 1 0 0 1 11873 "1683658020" 5.470759 19.60468 35.888397 8 4.319965 .10736042 .019232305 1.565377 0 1 0 0 0 22825 "1683949020" 8.634252 25.813786 42.1837 86.138 5.101937 .1871486 .1026652 1.701409 0 0 0 0 0 77392 "1684671020" 9.195432 35.127193 94.48351 55 5.901928 .24728633 .010012522 2.4348536 0 1 0 0 0 79721 "1687223020" 1.4853896 2.818773 2.818773 26.04 4.534898 -.004548673 .30504 .6579587 0 0 0 0 0 84721 "1687968020" 14.100945 24.07376 57.33063 205.681 7.761487 .10292736 .3324199 1.7766986 1 1 0 0 0 80167 "1688185020" 8.22961 19.18696 67.39301 34.248 6.561223 .0907435 .13443242 1.1441286 1 0 0 0 0 88873 "1692225040" 9.025189 28.82276 98.90736 67.2 6.749352 .24502844 .073103264 3.24765 0 1 0 0 1 10104 "1692716020" 2.947121 10.955528 44.46104 5946.507 9.937261 .23212646 .13786437 3.321313 1 0 0 0 0 24097 "1694877020" .7698978 2.075638 2.2552416 12.38 3.667298 .17375977 .08246053 1.924844 1 0 1 0 0 80568 "1695309020" 4.957831 18.83521 84.80095 34 6.471354 .12026926 .27074778 1.413486 0 1 0 0 0 65226 "1695629020" 5.288666 24.462437 93.58447 1852.057 7.546181 .10109966 .38566875 1.0022842 1 0 0 0 0 84255 "1696511040" 18.650494 44.11008 97.98711 22.4 5.358024 .09218813 .0009844328 2.1800828 0 1 0 0 1 64899 "1696779040" 6.645437 23.904034 80.52334 1323.234 8.962414 .09259535 .4214766 1.1726292 1 1 0 0 1 80569 "1704748020" 1.341467 4.862891 5.815122 7.6 6.671857 .021512646 .24582046 .4253166 0 0 0 0 0 53640 "1710031020" 6.499226 22.260765 96.50764 136.016 5.705717 .24316573 .010958777 5.406816 1 0 0 0 0 90532 "1710776020" 2.461546 .8044251 .8044251 4 3.2090275 .14082004 .12587357 1.2415997 0 0 0 0 0 75261 "1711994020" 35.63094 . 91.14706 4572.7 7.643237 .16140527 .07390413 1.3981036 1 0 0 0 0 89181 "1713101020" 8.861531 24.677784 56.62741 33.5 4.90423 .24303903 .01285046 3.0054324 0 1 0 0 0 61807 "1713991020" . 32.270428 86.05929 24 7.172676 .11008135 .26769722 1.143245 0 0 1 0 0 85900 "1716324020" 17.650417 38.39873 87.88174 170.5 6.94901 .1234956 .4772137 1.1599381 0 1 0 0 0 86580 "1720445040" 11.597057 14.858617 55.66696 48.394 7.395437 .12563002 .0005256255 2.3521488 1 1 0 0 1 20512 "1722865020" 10.190647 28.472683 96.5083 145 7.093537 .15014783 .28775412 1.8609844 0 1 0 0 0 47511 "1725059020" 6.428599 20.277657 40.40029 1.2 6.209085 .10190932 .2695728 1.1426606 0 0 0 0 0 76392 "1725662040" 14.989653 36.423237 72.71584 3 5.08912 .18524225 . 2.032474 0 1 0 0 1 66181 "1726780020" 5.382356 19.08136 63.14908 3475.355 10.56893 .2376179 .0554913 2.3726346 1 1 0 0 0 84607 "1727838020" 7.672452 20.79885 53.70712 4.8 5.329268 -.019744337 .4656571 1.8897815 0 0 1 0 0 79094 "1728337040" 7.615555 26.89435 90.60084 185 8.313181 .1244693 .08026318 1.5568042 0 1 0 0 1 80864 "1728510020" 7.994303 26.475813 75.741585 682.55 7.478209 .229511 .2017167 1.345607 1 0 0 0 0 26403 "1728815020" 3.361132 15.472085 65.91328 7531.739 10.881024 .1024493 .2415629 1.1526908 1 0 1 0 0 77780 "1728933020" 6.850841 24.427977 95.82795 287 6.962574 .11334228 .30583075 1.218842 0 0 0 0 0 89614 "1729243020" 8.996272 22.17081 72.31243 8 8.604224 .025489977 .447884 .625711 0 0 1 0 0 76367 "1729826020" 6.226701 22.09291 34.488113 58.33 4.4478493 -.17115504 .2400665 1.2451183 0 0 0 0 0 89743 "1729897020" 5.191266 15.740778 20.464153 10.1 4.90529 .172153 .467919 1.7629976 0 1 0 0 0 83596 "1730322040" 12.78261 40.78517 94.48737 382.854 9.746073 .08690818 .19037865 .9265989 1 1 0 0 1 85991 "1730768020" 18.803642 55.22 79.65611 137 9.021235 .05654223 .7276791 1.0112352 0 0 0 0 0 90377 "1730769020" 9.640486 32.240833 50.35661 78.8 4.914858 -.01649303 .02187821 1.0703081 0 0 0 0 0 86574 "1731085020" 7.817961 17.526278 30.67802 72.219 7.823623 .01965151 .2093209 .3301209 1 0 0 0 0 78213 "1731127040" 9.709722 34.12807 63.41633 4.2 4.3914447 .002600394 .09584308 2.286712 0 0 0 0 1 84283 "1731568020" 3.242239 14.409318 41.41772 511.587 7.312328 .24975945 .17383505 2.13466 1 1 0 0 0 91040 "1731949020" 5.192837 12.806868 31.240137 26 6.208504 .24448393 .25532794 1.6116037 0 0 0 0 0 86709 "1732422040" 7.93836 27.673115 68.72569 11 5.938016 .1084387 .06080721 1.0987972 0 0 0 0 1 83139 "1732588020" 7.112106 21.14558 34.683487 15 5.211184 .0802516 .2410439 1.2337993 0 0 0 0 0 76331 "1732681020" 9.292545 25.119 50.55806 21.66 7.599471 .027927464 .08534713 .27992728 1 0 0 0 0 10709 "1732695020" 2.982859 4.405824 4.431348 11.457 3.632336 .06272321 .02928494 1.0862062 0 0 0 0 0 22103 "1732813020" 4.373944 16.819036 72.58697 459.141 9.754233 .18122715 .2378824 1.949429 1 1 0 0 0 79922 "1733282020" 6.24243 17.382158 43.38095 516.803 7.044158 .2112178 .08724907 1.3847677 1 1 0 0 1 84283 "1733433020" 3.242239 14.409318 41.41772 157.142 7.312328 .24975945 .17383505 2.13466 1 1 0 0 0 89821 "1733468020" 2.6176605 3.0637155 3.0637155 29.175 6.387805 .016809352 .11194517 . 1 0 1 0 0 89397 "1733970040" 4.344704 13.276873 38.97729 5.8 6.412734 .03759773 .0021737062 1.936354 0 1 0 0 1 87267 "1734958020" 8.907758 23.11981 55.19898 9487.4 7.521859 .2009973 .1373328 3.894275 0 0 1 0 0 87478 "1735275020" 7.26054 29.66661 55.90702 61.005 5.063917 -.05319546 .002863301 1.2585547 1 0 0 0 0 90241 "1735869020" 14.76868 47.83927 68.47627 5.5 5.67517 .10941627 .604844 1.0528226 0 0 0 0 0 89752 "1736293020" 22.9342 49.43479 74.446815 5.041 6.885556 .13190906 .22552234 1.7484412 1 1 0 0 0 41443 "1736913020" 9.5081005 19.778873 71.61327 160 10.086355 .1520087 .2493639 1.2573777 0 1 0 0 0 78495 "1738104040" 10.512073 27.23999 56.16467 1010.547 6.580916 .12534665 .11092623 5.137457 1 0 1 0 1 83189 "1738316020" 10.901765 32.26022 . 1122.692 7.28815 .17883505 .3394811 1.3682798 1 1 0 0 0 79502 "1738846020" 9.4001255 31.84179 91.64678 7.6 7.38559 .10569963 .5071975 .8648703 0 0 0 0 0 85860 "1738965020" 8.529675 34.41192 76.77576 16.2 7.702874 .02083529 .19132353 .58096427 0 1 0 0 0 24459 "1739364040" 5.805533 25.22263 79.2235 40.999 9.270624 .14074713 .443197 1.344998 0 0 0 0 1 76127 "1739772020" 8.590772 27.914846 99.41363 15 6.58872 .14226319 .216372 1.6763017 0 1 0 0 0 80223 "1739947020" 6.931577 21.43519 81.47558 44 8.5436535 .02297166 .13700235 .3431969 0 0 0 0 0 66093 "1739992020" 7.876937 20.554 57.81506 72670.997 11.888838 .09645545 .20991266 .8618634 1 0 0 0 0 46931 "1740442020" 9.950427 36.675117 51.96564 9.155 4.4898715 .1917293 .19067445 1.2631646 0 0 0 0 0 53613 "1741256020" 11.733908 40.60383 91.55278 889.649 8.987996 .1846398 .1518785 1.0685129 1 0 0 0 0 85914 "1742837040" 17.170979 31.06348 75.2016 180 9.381264 .1783547 .05023601 2.2524762 0 0 0 0 1 80254 "1743051020" 8.001868 31.01099 88.71101 52.5 6.558137 .12593392 .4377359 1.4670846 0 1 0 0 0 90377 "1743084020" 9.640486 32.240833 50.35661 7 4.914858 -.01649303 .02187821 1.0703081 0 1 0 0 0 39693 "1743272040" 16.15781 41.62298 76.32452 124.623 6.907663 .11817187 .2860513 1.0782562 0 0 0 0 1 84176 "1743372040" 9.359533 28.114355 71.997856 366.702 8.302174 .1583486 .2047734 2.1536508 0 1 0 0 1 10785 "1743518020" 9.599111 28.387264 63.67007 8 4.0548587 .11994383 .0032942074 1.894954 0 1 0 0 0 73139 "1744390040" 3.245326 12.043897 44.47099 140 8.50595 .2365648 .04684371 3.688161 0 1 0 0 1 18729 "1744801020" 6.677524 16.842442 68.026695 100 9.048656 .3173702 .4050969 3.733138 0 0 0 0 0 28222 "1745101020" 7.876719 23.442595 81.77579 116 9.250407 .16177657 .2452444 1.4207412 0 0 0 0 0 11976 "1746350040" 13.762606 42.46059 90.32993 150 8.101163 .05903041 .003971743 1.0076706 0 1 0 0 1 90597 "1747715020" 7.608595 14.40282 15.780938 93 5.267698 .12209683 .17417216 1.7754734 0 1 0 0 0 89418 "1748204020" 12.73904 35.486805 64.1298 44.3 5.654683 .15685546 .19956167 1.7041743 0 1 0 0 0 51625 "1748540020" 14.951595 38.32568 69.22112 809.379 8.92861 .036321323 .16000503 .47963545 1 1 0 0 0 12217 "1748658020" 15.74334 38.22267 70.13188 14 5.026666 .13734058 .17720306 2.573909 0 1 0 0 0 76215 "1748698020" 8.171618 20.388664 42.62305 101.313 5.381021 .08349597 .4562566 2.1140008 1 0 0 0 0 87242 "1748702040" 6.942284 24.944496 58.23642 40.052 5.346288 .036067635 . 1.1605072 0 1 0 0 1 24459 "1748879020" 5.842854 25.22263 79.2235 67 9.270624 .14074713 .443197 1.344998 0 1 0 0 0 84420 "1748903020" 5.484814 23.559454 57.49706 125 4.873027 -.1732152 .7650173 1.4846798 1 0 0 0 0 76624 "1748972020" 12.815978 40.44864 91.59586 300 6.597076 .06461159 .3069791 2.2610688 0 0 1 0 0 90532 "1749742020" 2.696425 2.920601 2.9328046 9.5 3.2090275 .14082004 .12587357 1.2415997 0 0 0 0 0 end
Iteration 0: log likelihood = -1175.8548
Iteration 1: log likelihood = -1141.7252
Iteration 2: log likelihood = -1141.4575
Iteration 3: log likelihood = -1141.4575
Probit regression Number of obs = 2,169
LR chi2(11) = 68.79
Prob > chi2 = 0.0000
Log likelihood = -1141.4575 Pseudo R2 = 0.0293
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cross | Coef. Std. Err. z P>|z| [95% Conf. Interval]
--------------+----------------------------------------------------------------
larinstitinv | .0047034 .0091793 0.51 0.608 -.0132877 .0226946
top5institown | -.0046513 .0064633 -0.72 0.472 -.0173192 .0080166
totinstitown | .0058695 .0022333 2.63 0.009 .0014924 .0102466
firm_size | .0533325 .0197543 2.70 0.007 .0146148 .0920503
roa | -.1606951 .3697687 -0.43 0.664 -.8854285 .5640382
leverage | -.638889 .1914703 -3.34 0.001 -1.014164 -.263614
tobinq | .0375907 .0314943 1.19 0.233 -.0241369 .0993183
listar | -.2984842 .0689512 -4.33 0.000 -.433626 -.1633424
cashpay | .0661437 .0650047 1.02 0.309 -.0612632 .1935506
sharepay | -.2645316 .1485917 -1.78 0.075 -.5557661 .0267029
fincri | -.0807493 .0794607 -1.02 0.310 -.2364894 .0749907
_cons | -1.269006 .1774141 -7.15 0.000 -1.616731 -.9212803
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Best wishes,
Wenyu
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