Data

Berikut Data Analisis yang akan di gunakan

library(readr)
Eviews<-read.csv("Eviews.csv",header = TRUE)
summary(Eviews)
##      Code                Year          Y.SRDI          X1.TINV      
##  Length:85          Min.   :2018   Min.   :0.0900   Min.   :0.0000  
##  Class :character   1st Qu.:2019   1st Qu.:0.2700   1st Qu.:0.5100  
##  Mode  :character   Median :2020   Median :0.3600   Median :0.5900  
##                     Mean   :2020   Mean   :0.4074   Mean   :0.5599  
##                     3rd Qu.:2021   3rd Qu.:0.5200   3rd Qu.:0.6500  
##                     Max.   :2022   Max.   :0.9000   Max.   :0.8500  
##     X2.TKAR          X3.TKON          X4.TLIN          X5.TKRE      
##  Min.   : 7.150   Min.   :0.0000   Min.   :0.0000   Min.   :0.1100  
##  1st Qu.: 7.980   1st Qu.:0.0000   1st Qu.:0.2300   1st Qu.:0.3600  
##  Median : 8.940   Median :0.3300   Median :0.3700   Median :0.5600  
##  Mean   : 9.091   Mean   :0.3406   Mean   :0.4054   Mean   :0.5534  
##  3rd Qu.:10.140   3rd Qu.:0.6700   3rd Qu.:0.6000   3rd Qu.:0.7800  
##  Max.   :12.030   Max.   :1.0000   Max.   :0.9300   Max.   :0.8900  
##     X6.TMED         X7.TAUD         X8.TPEM      
##  Min.   :2.200   Min.   :20.62   Min.   :0.0000  
##  1st Qu.:5.900   1st Qu.:22.08   1st Qu.:0.0000  
##  Median :6.920   Median :22.61   Median :0.0000  
##  Mean   :6.652   Mean   :22.59   Mean   :0.2053  
##  3rd Qu.:7.530   3rd Qu.:23.19   3rd Qu.:0.5700  
##  Max.   :9.010   Max.   :24.51   Max.   :0.6500

Analisis Common Effects (CEM) atau Pooling

CEM adalah metode yang mengasumsikan efek tetap (fixed effects) pada variabel individu. Pooling adalah metode yang mengabaikan efek tetap dan menganggap semua individu sebagai satu kelompok.

# Analisis CEM
library("plm")
cem_model <- plm(Eviews$Y.SRDI ~ Eviews$X1, data = Eviews, model = "within")
plot(cem_model)
pooling_model <- plm(Eviews$Y.SRDI ~ Eviews$X1, data = Eviews, model = "pooling")
plot(pooling_model)

## Analisis Fixed Effects (FEM) atau Within: FEM adalah metode yang memperhitungkan efek tetap pada variabel individu. Anda dapat menggunakan perintah berikut untuk melakukan analisis FEM

fem_model <- plm(Eviews$Y.SRDI ~ Eviews$X1, data = Eviews, model = "fd")
plot(fem_model)

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