Cross-Sectional Models (vce, beta options and coefficient visualization) | Stata Tutorials Topic 48
Stata Tutorials Topic 48: Cross-Sectional Models (Options and Coefficient Visualization) | Regression Analysis and Estimation Methods Using Stata
Hi, I am Bob. Welcome to the Stata course on regression analysis and estimation methods. We have learned basic Stata commands for the OLS regressions and commonly used estimation approaches. Today, we will look at some options for the OLS models we haven't discussed in previous topics, such as the variance-covariance option for standard errors and the standardized coefficient option. We will also graph the estimated coefficient plots. We can plot the coefficients from different models in a diagram. It gives us a straightforward comparison of the estimates.
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#Stata #vce #beta #crosssection #margins #marginsplot #coefplot #RegressionAnalysisandEstimationMethods #tutorial
The Stata commands in this video:
*OLS
regress lwage schooling c.age##c.age ib5.health i.married i.female i.race
estimates store OLS
*Robust Option
regress lwage schooling c.age##c.age ib5.health i.married i.female i.race, vce(robust)
estimates store OLS_robust
esttab OLS OLS_robust, label mtitle b(%7.4f) se(%7.4f) varwidth(28) keep(schooling age 1.health 2.health 1.married 1.female 2.race 3.race) title("OLS Estimates") star(* 0.1 * 0.05 ** 0.01)
*Beta Option
regress lwage schooling c.age##c.age ib5.health i.married i.female i.race, vce(robust) beta
*Plot the Coefficient Estimates
regress lwage schooling age ib5.health i.married i.female i.race, vce(robust)
margins, dydx(*)
marginsplot, recast(scatter) yline(0)
margins, dydx(schooling age 1.health 2.health 1.married 1.female)
marginsplot, recast(scatter) yline(0)
*Plot Coefficients using coefplot
ssc install coefplot, replace
help coefplot
coefplot, xline(0)
coefplot, xline(0) keep(schooling age 1.health 2.health 1.married 1.female)
*Compare Estimates from Two Models
regress lwage schooling age ib5.health i.married i.race if female==1, vce(robust)
estimates store Female
regress lwage schooling age ib5.health i.married i.race if female==0, vce(robust)
estimates store Male
coefplot Female Male, xline(0) keep(schooling 1.married 2.race)
coefplot (Female, msymbol(T) mcolor(blue)) (Male, msymbol(S) mcolor(orange)), xline(0) keep(schooling 1.married 2.race) title(The Marginal Effects on Log(wage))
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