Dear all,
I'm investigating the relationship between patenting on the return of investment and look whether there is a difference between normal and acquired firms. I use ROI as a dependent variable and patens per year (pat_year -> number of granted patents granted per year per firm) and ma active (maactive -> is 0 in the year before acquisition, or in all years if never acquisition and 1 in the year from first acquisition and the years after that measured per firm and year) as independent variables. My control variables are firm size (measured as number of employees (emp) and total assets (ta)) and industry (measured as SIC code (SIC)). I want to use the total of acquisitions made by a firm (matotal) as a variable for a robustness check. I just ran a regression analysis just to quickly test if the results look okay or strange. And in this case, the results look far from correct to me. All variables are far from significant and the R2 is really really low. So my question is, what could be the problem here? Is my data incorrect or did I just ran the analysis in an incorrect way?
Thanks in advance!
I'm investigating the relationship between patenting on the return of investment and look whether there is a difference between normal and acquired firms. I use ROI as a dependent variable and patens per year (pat_year -> number of granted patents granted per year per firm) and ma active (maactive -> is 0 in the year before acquisition, or in all years if never acquisition and 1 in the year from first acquisition and the years after that measured per firm and year) as independent variables. My control variables are firm size (measured as number of employees (emp) and total assets (ta)) and industry (measured as SIC code (SIC)). I want to use the total of acquisitions made by a firm (matotal) as a variable for a robustness check. I just ran a regression analysis just to quickly test if the results look okay or strange. And in this case, the results look far from correct to me. All variables are far from significant and the R2 is really really low. So my question is, what could be the problem here? Is my data incorrect or did I just ran the analysis in an incorrect way?
Thanks in advance!
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input long gvkey double fyear float ROI double pat_yr float(maactive totalma) double(emp at) int sic 1078 1997 .4801397 195.5 0 14 54.487 12061.068 3845 1078 1998 .4420482 172.5 0 14 56.236 13216.213 3845 1078 1999 .3803547 152.5 1 14 57.1 14471.044 3845 1078 2000 .3381337 130.5 1 14 60.571 15283.254 3845 1078 2001 .2641248 136 1 14 71.426 23296.423 3845 1078 2002 .26380387 134.5 1 14 71.819 24259.102 3845 1078 2003 .25203487 128.5 1 14 72.181 26715.342 3845 1078 2004 .23309574 99.5 1 14 60.6 28767.494 3845 1078 2005 .25467196 64.5 1 14 59.735 29141.203 3845 1078 2006 .23073745 178 1 14 66.663 36178.172 3845 1078 2007 .2025775 153.5 1 14 68 39713.924 3845 1078 2008 .2472846 170.5 1 14 69 42419.204 3845 1078 2009 .20207043 212.5 1 14 73 52416.623 3845 1078 2010 .2296796 480 1 14 90 59462.266 3845 1078 2011 .24603337 630 1 14 91 60276.893 3845 1078 2012 .21790276 692.5 1 14 91 67234.944 3845 1078 2013 .09331705 674 1 14 69 42953 3845 1078 2014 .1168603 573.5 1 14 77 41275 3845 1078 2015 .12398426 465.5 1 14 74 41247 3845 1084 2001 .4526495 1 0 0 .001 .006 7370 1084 2002 -.012389752 0 0 0 .001 .013 7370 1084 2003 .00586807 0 0 0 .001 .002 7370 1084 2004 .006047966 0 0 0 .001 .002 7370 1084 2005 .0029711374 0 0 0 .001 .003 7370 1084 2006 .01033485 0 0 0 .001 .002 7370 1084 2007 .3193658 0 0 0 .001 .346 7370 1084 2008 .19756925 0 0 0 .001 .174 7370 1084 2009 .186853 1 0 0 .001 .004 7370 1084 2010 .18327183 0 0 0 .001 .402 7370 1084 2011 .5365622 0 0 0 .001 .279 7370 1084 2012 .5060827 2 0 0 .001 .237 7370 1084 2013 .992004 1 0 0 .001 .328 7370 1084 2014 .1772372 1 0 0 .001 .028 7370 1084 2015 .1495527 1 0 0 .001 .026 7370 1104 1997 .04386884 0 0 5 .433 29.857 3420 1104 1998 -.07722916 0 0 5 .312 28.896 3420 1104 1999 .05071249 0 0 5 .172 20.767 3420 1104 2000 .1895139 1 0 5 .134 21.118 3420 1104 2001 .21390837 1 0 5 .121 20.173 3420 1104 2002 .1055936 0 0 5 .1 17.614 3420 1104 2003 .19225118 2 0 5 .09 20.023 3420 1104 2004 .3971646 0 1 5 .103 23.009 3420 1104 2005 .3483861 1 1 5 .116 28.194 3420 1104 2006 .2367985 2 1 5 .12 35.021 3420 1104 2007 .20317155 0 1 5 .126 42.222 3420 1104 2008 .1985969 0 1 5 .137 45.424 3420 1104 2009 .08983529 1 1 5 .134 42.309 3420 1104 2010 .07665792 0 1 5 .132 49.581 3420 1104 2011 .09723662 5 1 5 .157 55.222 3420 1104 2012 .0971442 3 1 5 .171 67.828 3420 1104 2013 .10150733 0 1 5 .18 68.079 3420 1104 2014 .12102242 6 1 5 .303 79.308 3420 1104 2015 .11211774 0 1 5 .342 81.421 3420 1161 1997 -.03367206 273.5 0 4 12.8 3515.271 3674 1161 1998 -.04845113 556 0 4 13.8 4252.968 3674 1161 1999 -.08298296 830 0 4 13.387 4377.698 3674 1161 2000 .20479487 1053 0 4 14.696 5767.735 3674 1161 2001 .008975402 1091.5 0 4 14.415 5647.242 3674 1161 2002 -.20079833 1153.8333740234375 1 4 12.146 5619.181 3674 1161 2003 -.04891127 908 1 4 14.3 7094.345 3674 1161 2004 .04147957 812.5 1 4 15.9 7844.21 3674 1161 2005 .05039897 539.5 1 4 9.86 7287.779 3674 1161 2006 .04114087 510 1 4 16.5 13147 3674 1161 2007 -.14615013 339.5 1 4 16.42 11550 3674 1161 2008 -.2021299 235 1 4 14.7 7675 3674 1161 2009 -.08584338 246.5 1 4 13.4 9078 3674 1161 2010 .15370196 230.8333282470703 1 4 11.1 4964 3674 1161 2011 .15880655 253 1 4 11.093 4954 3674 1161 2012 .012038835 262 1 4 10.34 4000 3674 1161 2013 .03343824 287 1 4 10.671 4337 3674 1161 2014 .06705671 297.8333282470703 1 4 9.687 3767 3674 1161 2015 -.1969136 246 1 4 9.139 3109 3674 1209 1997 .13899349 72.5 1 14 16.4 7244.1 2810 1209 1998 .1646835 82 1 14 16.7 7489.6 2810 1209 1999 .14267895 87 1 14 17.4 8235.5 2810 1209 2000 .15012787 105 1 14 17.5 8270.5 2810 1209 2001 .15262887 87 1 14 17.8 8084.1 2810 1209 2002 .1340005 77 1 14 17.2 8495 2810 1209 2003 .1173117 105.5 1 14 18.5 9431.9 2810 1209 2004 .12459674 77 1 14 19.9 10040.4 2810 1209 2005 .14033335 61.5 1 14 20.2 10408.8 2810 1209 2006 .1372897 71.5 1 14 20.7 11180.7 2810 1209 2007 .1547853 73.5 1 14 22.1 12659.5 2810 1209 2008 .1716711 74 1 14 21.1 12571.3 2810 1209 2009 .13350144 62 1 14 18.9 13029.1 2810 1209 2010 .1542095 62 1 14 18.3 13505.9 2810 1209 2011 .1650078 58.5 1 14 18.9 14290.7 2810 1209 2012 .1284138 87 1 14 21.3 16941.8 2810 1209 2013 .11941256 92 1 14 21.6 17850.1 2810 1209 2014 .1269443 81 1 14 21.2 17779.1 2810 1209 2015 .1650721 63 1 14 19.7 17438.1 2810 1228 1997 -.110242 2 0 3 .066 16.959 4950 1228 1998 .08948132 1 0 3 .063 9.658 4950 1228 1999 .016587678 0 0 3 .055 8.156 4950 1228 2000 -.19897448 0 0 3 .05 11.434 4950 1228 2001 -.4556905 0 1 3 .054 9.781 4950 1228 2002 -.2894567 0 1 3 .036 9.862 4950 1228 2003 -.323962 0 1 3 .037 10.319 4950 1228 2004 -.2985118 0 1 3 .044 11.586 4950 1228 2005 -.4198913 0 1 3 .042 10.544 4950 end
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