R Codes

# load the library
library(margins)
library(dplyr)
library(knitr)
library(stargazer)
# Setting up the Stata engine
library(Statamarkdown)
options(width = 100)
# call the data mtcars from base R
data("mtcars")
# fit a model
fit1 <- lm(mpg ~ cyl + hp + wt, data = mtcars)
# print the marginal effects in a table
summary(margins(fit1)) %>%
  knitr::kable(caption = 'Summary of marginal effects of OLS without interactions in R')
Summary of marginal effects of OLS without interactions in R
factor AME SE z p lower upper
cyl -0.9416168 0.5509168 -1.709181 0.0874173 -2.0213939 0.1381603
hp -0.0180381 0.0118763 -1.518838 0.1288033 -0.0413151 0.0052389
wt -3.1669731 0.7405770 -4.276359 0.0000190 -4.6184774 -1.7154688

Stata Codes

* clear the memory
clear all
cls
* load the data
insheet using "F:\mtcars.csv", comma clear
* create a log file
* log using homework3, replace
quietly reg mpg cyl hp wt
margins, dydx(*)
. * clear the mem. clear all

. cls

. * load the data
. insheet using "F:\mtcars.csv", comma clear
(12 vars, 32 obs)

. * create a log file
. * log using homework3, replace
. quietly reg mpg cyl hp wt

. margins, dydx(*)

Average marginal effects                                    Number of obs = 32
Model VCE: OLS

Expression: Linear prediction, predict()
dy/dx wrt:  cyl hp wt

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         cyl |  -.9416166   .5509165    -1.71   0.098    -2.070118    .1868846
          hp |  -.0180381   .0118763    -1.52   0.140    -.0423655    .0062893
          wt |  -3.166973    .740576    -4.28   0.000    -4.683975   -1.649972
------------------------------------------------------------------------------