If the causal effect is different for different people, then the population regression equation for a binary treatment variable Xi, can be written as a. $Y _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + u _ { i }$.
b. $Y _ { i } = \beta _ { 0 } + \beta _ { 1 i } X _ { i } + u _ { i }$.
c. $Y _ { i } = \beta _ { 0 i } + \beta _ { 1 i } X _ { i } + u _ { i }$.
d. $Y _ { i } = \beta _ { 0 } + \beta _ { 1 } G _ { i } + \beta _ { 2 } D _ { t } + u _ { i }$.

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The Answer of If the causal effect is different for different people, then the population regression equation for a binary treatment variable Xi, can be written as a. $Y _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + u _ { i }$.
b. $Y _ { i } = \beta _ { 0 } + \beta _ { 1 i } X _ { i } + u _ { i }$.
c. $Y _ { i } = \beta _ { 0 i } + \beta _ { 1 i } X _ { i } + u _ { i }$.
d. $Y _ { i } = \beta _ { 0 } + \beta _ { 1 } G _ { i } + \beta _ { 2 } D _ { t } + u _ { i }$.

If the Causal Effect Is Different for Different People, Then Yi=β0+β1Xi+uiY _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + u _ { i }Yi​=β0​+β1​Xi​+ui​

If the Causal Effect Is Different for Different People, Then $Y _ { i } = \beta _ { 0 } + \beta _ { 1 } X _ { i } + u _ { i }$