Hi all,
I am running the following equation on reghdfe:
however, some of the observations (a lot of them actually) are excluded from the regression. To put this into numbers I have almost 358000 observations and only 142000 are used for the reghdfe.
Below you can see may dataset with the reg_obs variable taking into account the variables adopted and not adopted for the regression:
As you can see there are some values that are excluded from the regression even if they have all the variables (with variability within the cluster, like, e.g..
)
and others that, quite counterintuitive to me are included like:
Why is this like this?
Thank you
I am running the following equation on reghdfe:
Code:
reghdfe import_starter l.c1_prop_importing l.s1_prop_importing , a( eu#year i.niu#i.year ) vce(cluster i.niu#i.year )
Below you can see may dataset with the reg_obs variable taking into account the variables adopted and not adopted for the regression:
Code:
* Example generated by -dataex-. For more info, type help dataex clear input float(import_starter niu_eu reg_obs) double niu int year float(c1_prop_importing s1_prop_importing importingeu2_dprop importingnoneu2_dprop importingeu2_uprop importingnoneu2_uprop) byte eu 0 1 0 1002001163 2010 .875 .4210528 .50021863 .3001381 .4799981 .25936222 0 0 1 0 1002001163 2011 .625 .526316 .52926433 .33035585 .5106906 .27024272 0 0 1 0 1002001163 2012 .625 .4210528 .5308992 .3189881 .5148405 .26588085 0 0 1 0 1002001163 2013 .875 .4736844 .5618814 .3448819 .51349205 .27985746 0 0 1 0 1002001163 2014 .75 .5789476 .56052655 .3380097 .5691549 .28085756 0 1 2 0 1002001163 2010 .625 .6842108 .50021863 .3001381 .4799981 .25936222 1 . 2 0 1002001163 2011 .75 .526316 .52926433 .33035585 .5106906 .27024272 1 . 2 0 1002001163 2012 .625 .6842108 .5308992 .3189881 .5148405 .26588085 1 . 2 0 1002001163 2013 .75 .7368424 .5618814 .3448819 .51349205 .27985746 1 . 2 0 1002001163 2014 .5 .6842108 .56052655 .3380097 .5691549 .28085756 1 0 3 0 1900147223 2010 0 .2499999 .4573724 .3022724 .4696848 .2794978 0 0 3 1 1900147223 2011 0 .2499999 .4775886 .3248783 .5018109 .41699785 0 0 3 1 1900147223 2012 0 .2499999 .482752 .3216156 .5018109 .3482478 0 0 3 1 1900147223 2013 0 .0833333 .5281956 .3962154 .517874 .4330609 0 0 3 1 1900147223 2014 0 .3333332 .5329283 .315779 .5018109 .3482478 0 0 4 0 1900147223 2010 0 .3333332 .4573724 .3022724 .4696848 .2794978 1 0 4 1 1900147223 2011 0 .4166665 .4775886 .3248783 .5018109 .41699785 1 0 4 1 1900147223 2012 0 .4166665 .482752 .3216156 .5018109 .3482478 1 0 4 1 1900147223 2013 .25 .4999998 .5281956 .3962154 .517874 .4330609 1 0 4 1 1900147223 2014 0 .3333332 .5329283 .315779 .5018109 .3482478 1 0 5 0 1900338297 2010 .571428 0 1 1 .44249925 .24996364 0 0 5 0 1900338297 2011 .428571 0 1 1 .4855799 .305008 0 0 5 0 1900338297 2012 .428571 1 1 1 .4963517 .2613976 0 0 5 0 1900338297 2013 .428571 1 1 1 .5319293 .3857464 0 0 5 0 1900338297 2014 .714285 0 1 1 .52018857 .3474298 0 . 6 0 1900338297 2010 .571428 0 1 1 .44249925 .24996364 1 . 6 0 1900338297 2011 .714285 0 1 1 .4855799 .305008 1 . 6 0 1900338297 2012 .714285 0 1 1 .4963517 .2613976 1 . 6 0 1900338297 2013 .571428 1 1 1 .5319293 .3857464 1 . 6 0 1900338297 2014 .571428 0 1 1 .52018857 .3474298 1 . 7 0 1900354062 2010 .588236 .619047 .3744791 .2386279 .3782731 .24953753 0 . 7 0 1900354062 2011 .588236 .666666 .3891732 .2334122 .3995861 .28697857 0 . 7 0 1900354062 2012 .5588242 .619047 .4054865 .23574243 .3927215 .2657595 0 . 7 0 1900354062 2013 .6470596 .714285 .4220624 .24268155 .4215259 .3297136 0 . 7 0 1900354062 2014 .735295 .714285 .4304704 .2162187 .475047 .28102913 0 1 8 0 1900354062 2010 .588236 .809523 .3744791 .2386279 .3782731 .24953753 1 . 8 0 1900354062 2011 .6470596 .761904 .3891732 .2334122 .3995861 .28697857 1 . 8 0 1900354062 2012 .6470596 .714285 .4054865 .23574243 .3927215 .2657595 1 . 8 0 1900354062 2013 .6176478 .7380945 .4220624 .24268155 .4215259 .3297136 1 . 8 0 1900354062 2014 .588236 .761904 .4304704 .2162187 .475047 .28102913 1 0 9 0 2000001243 2010 .272727 .4482764 .4576761 .28908548 .4521937 .27172717 0 0 9 0 2000001243 2011 .363636 .4827592 .5204781 .3210406 .4473028 .33797115 0 0 9 0 2000001243 2012 .272727 .4827592 .526156 .3093448 .4600987 .29378185 0 0 9 0 2000001243 2013 .272727 .517242 .5280846 .3119616 .4540525 .2628305 0 0 9 0 2000001243 2014 .272727 .517242 .5272788 .3344246 .46768275 .28368175 0 1 10 0 2000001243 2010 .454545 .5862076 .4576761 .28908548 .4521937 .27172717 1 . 10 0 2000001243 2011 .4999995 .5862076 .5204781 .3210406 .4473028 .33797115 1 . 10 0 2000001243 2012 .454545 .6206904 .526156 .3093448 .4600987 .29378185 1 . 10 0 2000001243 2013 .454545 .5862076 .5280846 .3119616 .4540525 .2628305 1 . 10 0 2000001243 2014 .4090905 .5517248 .5272788 .3344246 .46768275 .28368175 1 . 11 0 2000005885 2010 1 0 0 0 .4470046 .3870968 0 . 11 0 2000005885 2011 1 0 0 0 .4239631 .3410138 0 . 11 0 2000005885 2012 1 0 0 0 .41013825 .2764977 0 . 11 0 2000005885 2013 1 0 .3333333 .3333333 .4009217 .20737328 0 . 11 0 2000005885 2014 1 0 .3333333 .3333333 .3686636 .22580644 0 0 12 0 2000005885 2010 1 0 0 0 .4470046 .3870968 1 0 12 0 2000005885 2011 1 0 0 0 .4239631 .3410138 1 0 12 0 2000005885 2012 1 0 0 0 .41013825 .2764977 1 0 12 0 2000005885 2013 1 0 .3333333 .3333333 .4009217 .20737328 1 0 12 0 2000005885 2014 1 0 .3333333 .3333333 .3686636 .22580644 1 0 13 0 2000023046 2010 1 .333333 .31250015 .25000012 .4470046 .3870968 0 0 13 1 2000023046 2011 1 .333333 .31250015 .25000012 .4239631 .3410138 0 0 13 1 2000023046 2012 1 .333333 .31250015 .28125015 .41013825 .2764977 0 0 13 1 2000023046 2013 1 .333333 .47916675 .4166667 .4009217 .20737328 0 0 13 1 2000023046 2014 1 .333333 .47916675 .4166667 .3686636 .22580644 0 0 14 0 2000023046 2010 1 .333333 .31250015 .25000012 .4470046 .3870968 1 0 14 1 2000023046 2011 1 .333333 .31250015 .25000012 .4239631 .3410138 1 0 14 1 2000023046 2012 1 .333333 .31250015 .28125015 .41013825 .2764977 1 0 14 1 2000023046 2013 1 .333333 .47916675 .4166667 .4009217 .20737328 1 0 14 1 2000023046 2014 1 .333333 .47916675 .4166667 .3686636 .22580644 1 0 15 0 2000023691 2010 .333333 .818181 .53193665 .4204828 .58913636 .4303619 0 0 15 1 2000023691 2011 0 .90909 .560728 .4409811 .58913636 .4401112 0 0 15 1 2000023691 2012 .666666 .8636355 .55894816 .47266835 .6629525 .4846794 0 0 15 1 2000023691 2013 .333333 .8636355 .58659935 .4515955 .6378828 .56406665 0 0 15 1 2000023691 2014 .333333 .8636355 .58065873 .4420311 .7075208 .4944287 0 0 16 0 2000023691 2010 0 .818181 .53193665 .4204828 .58913636 .4303619 1 0 16 1 2000023691 2011 .333333 .8636355 .560728 .4409811 .58913636 .4401112 1 0 16 1 2000023691 2012 .666666 .8636355 .55894816 .47266835 .6629525 .4846794 1 0 16 1 2000023691 2013 .666666 .90909 .58659935 .4515955 .6378828 .56406665 1 0 16 1 2000023691 2014 .666666 .8636355 .58065873 .4420311 .7075208 .4944287 1 0 17 0 2002903476 2010 0 .5 .4229295 .20778796 .1590909 .03409091 0 0 17 1 2002903476 2011 0 .5 .42218485 .20769487 .2159091 .03409091 0 0 17 1 2002903476 2012 0 .5 .4230226 .18528993 .1931818 .03409091 0 0 17 1 2002903476 2013 0 .5 .3790505 .2063917 .17045455 .03409091 0 0 17 1 2002903476 2014 1 .5 .4022932 .229169 .1590909 .05681818 0 0 18 0 2002903476 2010 1 .5 .4229295 .20778796 .1590909 .03409091 1 0 18 1 2002903476 2011 1 .5 .42218485 .20769487 .2159091 .03409091 1 0 18 1 2002903476 2012 1 .5 .4230226 .18528993 .1931818 .03409091 1 0 18 1 2002903476 2013 1 .5 .3790505 .2063917 .17045455 .03409091 1 0 18 1 2002903476 2014 1 .5 .4022932 .229169 .1590909 .05681818 1 . 19 0 2900026825 2010 0 .428571 .5677139 .4868784 .5416667 .5208334 0 . 19 0 2900026825 2011 .166667 .714285 .6166499 .5010668 .5416667 .5416667 0 . 19 0 2900026825 2012 0 .714285 .6447643 .5488552 .5208334 .5416667 0 . 19 0 2900026825 2013 0 .714285 .6706166 .4983225 .5416667 .5416667 0 . 19 0 2900026825 2014 0 .714285 .680166 .59563017 .5416667 .56250006 0 0 20 0 2900026825 2010 0 .714285 .5677139 .4868784 .5416667 .5208334 1 0 20 0 2900026825 2011 0 .571428 .6166499 .5010668 .5416667 .5416667 1 0 20 0 2900026825 2012 .166667 .714285 .6447643 .5488552 .5208334 .5416667 1 0 20 0 2900026825 2013 0 .571428 .6706166 .4983225 .5416667 .5416667 1 0 20 0 2900026825 2014 0 .571428 .680166 .59563017 .5416667 .56250006 1 end label values eu _merge label def _merge 0 "Original observation", modify label def _merge 1 "Duplicated observation", modify
Code:
0 1 0 1002001163 2010 .875 .4210528 .50021863 .3001381 .4799981 .25936222 0 0 1 0 1002001163 2011 .625 .526316 .52926433 .33035585 .5106906 .27024272 0 0 1 0 1002001163 2012 .625 .4210528 .5308992 .3189881 .5148405 .26588085 0 0 1 0 1002001163 2013 .875 .4736844 .5618814 .3448819 .51349205 .27985746 0 0 1 0 1002001163 2014 .75 .5789476 .56052655 .3380097 .5691549 .28085756 0 1 2 0 1002001163 2010 .625 .6842108 .50021863 .3001381 .4799981 .25936222 1 . 2 0 1002001163 2011 .75 .526316 .52926433 .33035585 .5106906 .27024272 1 . 2 0 1002001163 2012 .625 .6842108 .5308992 .3189881 .5148405 .26588085 1 . 2 0 1002001163 2013 .75 .7368424 .5618814 .3448819 .51349205 .27985746 1 . 2 0 1002001163 2014 .5 .6842108 .56052655 .3380097 .5691549 .28085756 1
and others that, quite counterintuitive to me are included like:
Code:
0 3 0 1900147223 2010 0 .2499999 .4573724 .3022724 .4696848 .2794978 0 0 3 1 1900147223 2011 0 .2499999 .4775886 .3248783 .5018109 .41699785 0 0 3 1 1900147223 2012 0 .2499999 .482752 .3216156 .5018109 .3482478 0 0 3 1 1900147223 2013 0 .0833333 .5281956 .3962154 .517874 .4330609 0 0 3 1 1900147223 2014 0 .3333332 .5329283 .315779 .5018109 .3482478 0 0 4 0 1900147223 2010 0 .3333332 .4573724 .3022724 .4696848 .2794978 1 0 4 1 1900147223 2011 0 .4166665 .4775886 .3248783 .5018109 .41699785 1 0 4 1 1900147223 2012 0 .4166665 .482752 .3216156 .5018109 .3482478 1 0 4 1 1900147223 2013 .25 .4999998 .5281956 .3962154 .517874 .4330609 1 0 4 1 1900147223 2014 0 .3333332 .5329283 .315779 .5018109 .3482478 1
Thank you
Comment