We use data to estimate a wage equation for men. We use three methods: pooled OLS,...

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We use data to estimate a wage equation for men. We use three methods: pooled OLS, random effects, and fixed effects. The estimated models are shown in the table below. The time varying variables are exper, exper square, union and married. Three Different Estimators of a Wage Equation Independent Variables educ black hispan exper exper married union Dependent Variable: log(wage) Random Effects Pooled OLS .091 (.005) <--139 (024) .016 (021) 067 (014) -.0024 (.0008) .108 (.016) .182 (017) ,092 (011) -.139 (.048) 022 (.043) .106 (015) -.0047 (.0007) .064 (.017) .106 (.018) Fixed Effects -.0052 (.0007) .047 (.018) .080 (.019) (i) Written down the three estimated equations. (ii) Explain how married variable effects dependent variable in each model. Does married variable have a statistically significant effect on wage in each model? We use data to estimate a wage equation for men. We use three methods: pooled OLS, random effects, and fixed effects. The estimated models are shown in the table below. The time varying variables are exper, exper square, union and married. Three Different Estimators of a Wage Equation Independent Variables educ black hispan exper exper married union Dependent Variable: log(wage) Random Effects Pooled OLS .091 (.005) <--139 (024) .016 (021) 067 (014) -.0024 (.0008) .108 (.016) .182 (017) ,092 (011) -.139 (.048) 022 (.043) .106 (015) -.0047 (.0007) .064 (.017) .106 (.018) Fixed Effects -.0052 (.0007) .047 (.018) .080 (.019) (i) Written down the three estimated equations. (ii) Explain how married variable effects dependent variable in each model. Does married variable have a statistically significant effect on wage in each model?