library(plm)
## Warning: package 'plm' was built under R version 4.2.2
library(wooldridge)
library(rmarkdown)
data("airfare")
paged_table(airfare)
time <- pdata.frame(airfare, index = c("id","year" ) )
pdim(time)
## Balanced Panel: n = 1149, T = 4, N = 4596
pooling <- plm(lpassen ~ fare + dist + passen + bmktshr + I(ldist^2) + year, data = time , model = "pooling" )
within <- plm(lpassen ~ fare + dist + passen + bmktshr + I(ldist^2) + year, data = time, model = "within" )
random <- plm(lpassen ~ fare + dist + passen + bmktshr + I(ldist^2) + year, data = time, 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(pooling, within, random, type = "text" )
## 
## ===============================================================================
##                                     Dependent variable:                        
##              ------------------------------------------------------------------
##                                           lpassen                              
##                          (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
phtest(random, within)
## 
##  Hausman Test
## 
## data:  lpassen ~ fare + dist + passen + bmktshr + I(ldist^2) + year
## chisq = 253.23, df = 6, p-value < 2.2e-16
## alternative hypothesis: one model is inconsistent
data("murder")
paged_table(murder)
library(plm)
individual <- pdata.frame(murder, index = c("state", "year" ) )
pvar(individual)
## no time variation:       id state cmrdrte cexec cunem cexec_1 cunem_1 
## no individual variation: year d90 d93 
## all NA in time dimension for at least one individual:  cmrdrte cexec cunem cexec_1 cunem_1 
## all NA in ind. dimension for at least one time period: cmrdrte cexec cunem cexec_1 cunem_1
poolingmurder <- plm(mrdrte ~ exec + unem + d90 + d93 + I(cexec^2) + year, data = individual , model = "pooling")
withinmurder <- plm(mrdrte ~ exec + unem + d90 + d93 + I(cexec^2) + year, data = individual , model = "within")
randommurder <- plm(mrdrte ~ exec + unem + d90 + d93 + I(cexec^2) + year, data = individual , model = "random")
stargazer(poolingmurder, withinmurder, randommurder, type = "text" )
## 
## ==============================================================
##                             Dependent variable:               
##              -------------------------------------------------
##                                   mrdrte                      
##                      (1)                  (2)           (3)   
## --------------------------------------------------------------
## exec                0.324               -0.004         0.006  
##                    (0.647)              (0.125)       (0.127) 
##                                                               
## unem               2.519***             -0.072         -0.019 
##                    (0.786)              (0.159)       (0.161) 
##                                                               
## d90                 2.066               -0.403*       -0.352* 
##                    (2.154)              (0.210)       (0.214) 
##                                                               
## I(cexec2)           -0.015              -0.006         -0.007 
##                    (0.047)              (0.008)       (0.008) 
##                                                               
## Constant            -7.400                            8.921***
##                    (5.119)                            (1.789) 
##                                                               
## --------------------------------------------------------------
## Observations         102                  102           102   
## R2                  0.103                0.178         0.088  
## Adjusted R2         0.066               -0.767         0.050  
## F Statistic  2.773** (df = 4; 97) 2.543* (df = 4; 47)  9.358* 
## ==============================================================
## Note:                              *p<0.1; **p<0.05; ***p<0.01
phtest(withinmurder,randommurder)
## 
##  Hausman Test
## 
## data:  mrdrte ~ exec + unem + d90 + d93 + I(cexec^2) + year
## chisq = 6.0219, df = 4, p-value = 0.1975
## alternative hypothesis: one model is inconsistent