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Heckman_2_Step_method.do
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Heckman_2_Step_method.do
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* dependent varaible: ROA
* independent varaibles: LnTA GenderIndex NationalityIndex AgeIndex SkillsIndex BoardSize pFemale dFemale
********************************************************************************************************
* Fixed Effect regression
********************************************************************************************************
xtreg ROA LnTA GenderIndex NationalityIndex AgeIndex SkillsIndex BoardSize pFemale dFemale, fe
xtreg ROA LnTA GenderIndex NationalityIndex AgeIndex SkillsIndex BoardSize pFemale dFemale, fe
* storing estimates
estimates store fixed
********************************************************************************************************
* Random Effect regression
********************************************************************************************************
xtreg ROA LnTA GenderIndex NationalityIndex AgeIndex SkillsIndex BoardSize pFemale dFemale, re
xtreg ROA LnTA GenderIndex NationalityIndex AgeIndex SkillsIndex BoardSize pFemale dFemale, re
* storing estimates
estimates store random
********************************************************************************************************
* Heckman 2-Step for solving selection bias
********************************************************************************************************
heckman ROA (LnTA GenderIndex NationalityIndex AgeIndex SkillsIndex BoardSize pFemale dFemale), select (dy = (LnTA GenderIndex NationalityIndex AgeIndex SkillsIndex BoardSize pFemale dFemale)) twostep
margins, dydx(x) atmeans predict(e(0,.))