Hi!
I want to increase the number of observations and for that I like to include more observations of my dependent variable, emission score for 2 more years (2018 and 2019) in my regression model.
I am missing the data of the independent variables for these tweo years, but since the data of my dependent variable are forwarded this should work?
But now I don't know how to adjust my regression command to achieve this? Can anyone give me a hint on this? Thanks a lot!
The regression contains some further variables just put some in for clarification
I want to increase the number of observations and for that I like to include more observations of my dependent variable, emission score for 2 more years (2018 and 2019) in my regression model.
I am missing the data of the independent variables for these tweo years, but since the data of my dependent variable are forwarded this should work?
But now I don't know how to adjust my regression command to achieve this? Can anyone give me a hint on this? Thanks a lot!
The regression contains some further variables just put some in for clarification

Code:
* Example generated by -dataex-. To install: ssc install dataex clear xtreg f. ClimateEmission firm_age firm_size mean_roa tot_sales i.year, fe vce(robust) input str10 ds_code double(year ClimateEmissions) long tot_sales "130298" 2012 1128000 1198 "130298" 2013 1140000 1077 "130298" 2014 909000 925 "130298" 2015 640199.612 1848 "130298" 2016 656334.2 1427 "130298" 2017 1050000 1449 "130298" 2018 960000 . "130298" 2019 902000 . "130298" 2020 935000 . "130775" 2012 5158458.052 2426 "130775" 2013 . 2251 "130775" 2014 6224214.242 2445 "130775" 2015 6471558.22 2809 "130775" 2016 . 2693 "130775" 2017 8948204 2558 "130775" 2018 . . "130775" 2019 8438042 . "130775" 2020 32450104.45 . "13466Q" 2012 7218.959 2334 "13466Q" 2013 . 2538 "13466Q" 2014 9403.199 2685 "13466Q" 2015 12161.928 3136 "13466Q" 2016 15115.7 43 "13466Q" 2017 46319 390 "13466Q" 2018 64592.272 . "13466Q" 2019 82965.247 . "13466Q" 2020 98896.958 . "13471D" 2012 7855.531 892 "13471D" 2013 7939.2 939 "13471D" 2014 7939.2 987 "13471D" 2015 8520.96 1417 "13471D" 2016 17270.4 1989 "13471D" 2017 21101 1858 "13471D" 2018 23211.365 . "13471D" 2019 50642.978 . "13471D" 2020 45832 .