library(dplyr)
##
## Attachement du package : 'dplyr'
## Les objets suivants sont masqués depuis 'package:stats':
##
## filter, lag
## Les objets suivants sont masqués depuis 'package:base':
##
## intersect, setdiff, setequal, union
library(rmarkdown)
library(wooldridge)
paged_table(murder)
summary(lm(mrdrte ~ exec + unem + d90 + d93 , data = murder ))
##
## Call:
## lm(formula = mrdrte ~ exec + unem + d90 + d93, data = murder)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.130 -3.119 -1.211 1.379 67.810
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.8644 3.0695 -0.607 0.54452
## exec 0.1628 0.1939 0.839 0.40268
## unem 1.3908 0.4509 3.085 0.00243 **
## d90 2.6753 1.8169 1.472 0.14302
## d93 1.6073 1.7748 0.906 0.36659
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.955 on 148 degrees of freedom
## Multiple R-squared: 0.07609, Adjusted R-squared: 0.05112
## F-statistic: 3.047 on 4 and 148 DF, p-value: 0.01897
library(plm)
##
## Attachement du package : 'plm'
## Les objets suivants sont masqués depuis 'package:dplyr':
##
## between, lag, lead
data("airfare")
library(rmarkdown)
paged_table(airfare)
indexdata <- pdata.frame(airfare, index = c("id", "year"))
pdim(indexdata)
## Balanced Panel: n = 1149, T = 4, N = 4596
pvar(indexdata)
## no time variation: id dist ldist ldistsq
## no individual variation: year y98 y99 y00
poolingmodel <- plm(lpassen ~ fare + dist + passen + bmktshr + I(ldist^2) + year, data = indexdata, model = "pooling")
withinmodel <- plm(lpassen ~ fare + dist + passen + bmktshr + I(ldist^2) + year, data = indexdata, model = "within")
randommodel <- plm(lpassen ~ fare + dist + passen + bmktshr + I(ldist^2) + year, data = indexdata, model = "random")
library(stargazer)
##
## Please cite as:
## Hlavac, Marek (2022). stargazer: Well-Formatted Regression and Summary Statistics Tables.
## R package version 5.2.3. https://CRAN.R-project.org/package=stargazer
stargazer(poolingmodel, withinmodel, randommodel, type = "text", column.labels = c("OLS","RE","FE"))
##
## ===============================================================================
## Dependent variable:
## ------------------------------------------------------------------
## lpassen
## OLS RE FE
## (1) (2) (3)
## -------------------------------------------------------------------------------
## fare -0.001*** -0.004*** -0.003***
## (0.0001) (0.0001) (0.0001)
##
## dist 0.0001** 0.0003***
## (0.00004) (0.0001)
##
## passen 0.001*** 0.001*** 0.001***
## (0.00001) (0.00002) (0.00001)
##
## bmktshr 0.223*** 0.161*** 0.200***
## (0.047) (0.040) (0.038)
##
## I(ldist2) 0.001 -0.004
## (0.003) (0.006)
##
## year1998 0.004 0.015** 0.010
## (0.021) (0.006) (0.006)
##
## year1999 0.018 0.051*** 0.034***
## (0.021) (0.006) (0.006)
##
## year2000 0.041* 0.110*** 0.079***
## (0.021) (0.007) (0.007)
##
## Constant 5.370*** 5.858***
## (0.110) (0.196)
##
## -------------------------------------------------------------------------------
## Observations 4,596 4,596 4,596
## R2 0.677 0.450 0.515
## Adjusted R2 0.676 0.266 0.514
## F Statistic 1,199.361*** (df = 8; 4587) 469.900*** (df = 6; 3441) 4,875.385***
## ===============================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01