library(plm)
library(readxl)
#read data
df <- read_excel("Pak Indra Data Panel.xlsx")
head(df)
#data panel
df_p <- pdata.frame(df, index = c("Perusahaan", "Tahun"))
head(df_p)
#regresi panel
pooling_ecik <- plm(Profit ~ Ekonomi + Coal + Inflasi + Kurs,
data = df_p, model = "pooling")
model_fe_ecik <- plm(Profit ~ Ekonomi + Coal + Inflasi + Kurs,
data = df_p, model = "within")
model_re_ecik <- plm(Profit ~ Ekonomi + Coal + Inflasi + Kurs,
data = df_p, model = "random")
#model regresi panel
summary(pooling_ecik)
## Pooling Model
##
## Call:
## plm(formula = Profit ~ Ekonomi + Coal + Inflasi + Kurs, data = df_p,
## model = "pooling")
##
## Unbalanced Panel: n = 8, T = 4-16, N = 76
##
## Residuals:
## Min. 1st Qu. Median 3rd Qu. Max.
## -433.745 -77.401 -17.035 88.993 405.676
##
## Coefficients:
## Estimate Std. Error t-value Pr(>|t|)
## (Intercept) -88.4625513 188.1835804 -0.4701 0.639734
## Ekonomi 1.1038282 10.1311916 0.1090 0.913547
## Coal 3.1767717 0.8660966 3.6679 0.000469 ***
## Inflasi 5.1658485 11.1143632 0.4648 0.643504
## Kurs -0.0041918 0.0133722 -0.3135 0.754842
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 2147800
## Residual Sum of Squares: 1631900
## R-Squared: 0.24018
## Adj. R-Squared: 0.19737
## F-statistic: 5.61069 on 4 and 71 DF, p-value: 0.00055491
summary(model_fe_ecik)
## Oneway (individual) effect Within Model
##
## Call:
## plm(formula = Profit ~ Ekonomi + Coal + Inflasi + Kurs, data = df_p,
## model = "within")
##
## Unbalanced Panel: n = 8, T = 4-16, N = 76
##
## Residuals:
## Min. 1st Qu. Median 3rd Qu. Max.
## -427.5695 -63.6005 -5.7678 67.6231 340.6014
##
## Coefficients:
## Estimate Std. Error t-value Pr(>|t|)
## Ekonomi -1.4272950 10.0751238 -0.1417 0.8877894
## Coal 3.5747440 0.8860670 4.0344 0.0001485 ***
## Inflasi 5.6961722 10.9628114 0.5196 0.6051415
## Kurs -0.0066245 0.0134170 -0.4937 0.6231798
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 1964200
## Residual Sum of Squares: 1408900
## R-Squared: 0.28269
## Adj. R-Squared: 0.1594
## F-statistic: 6.3056 on 4 and 64 DF, p-value: 0.00024243
summary(model_re_ecik)
## Oneway (individual) effect Random Effect Model
## (Swamy-Arora's transformation)
##
## Call:
## plm(formula = Profit ~ Ekonomi + Coal + Inflasi + Kurs, data = df_p,
## model = "random")
##
## Unbalanced Panel: n = 8, T = 4-16, N = 76
##
## Effects:
## var std.dev share
## idiosyncratic 22014.4 148.4 1
## individual 0.0 0.0 0
## theta:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0 0 0 0 0 0
##
## Residuals:
## Min. 1st Qu. Median 3rd Qu. Max.
## -433.745 -77.401 -17.035 88.993 405.676
##
## Coefficients:
## Estimate Std. Error z-value Pr(>|z|)
## (Intercept) -88.4625513 188.1835804 -0.4701 0.6382933
## Ekonomi 1.1038282 10.1311916 0.1090 0.9132394
## Coal 3.1767717 0.8660966 3.6679 0.0002445 ***
## Inflasi 5.1658485 11.1143632 0.4648 0.6420816
## Kurs -0.0041918 0.0133722 -0.3135 0.7539228
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 2147800
## Residual Sum of Squares: 1631900
## R-Squared: 0.24018
## Adj. R-Squared: 0.19737
## Chisq: 22.4428 on 4 DF, p-value: 0.00016358
#uji model
phtest(model_fe_ecik, model_re_ecik)
##
## Hausman Test
##
## data: Profit ~ Ekonomi + Coal + Inflasi + Kurs
## chisq = 12.12, df = 4, p-value = 0.01648
## alternative hypothesis: one model is inconsistent
pFtest(model_fe_ecik, pooling_ecik)
##
## F test for individual effects
##
## data: Profit ~ Ekonomi + Coal + Inflasi + Kurs
## F = 1.4471, df1 = 7, df2 = 64, p-value = 0.2024
## alternative hypothesis: significant effects
plmtest(pooling_ecik, type = "bp")
##
## Lagrange Multiplier Test - (Breusch-Pagan)
##
## data: Profit ~ Ekonomi + Coal + Inflasi + Kurs
## chisq = 0.099892, df = 1, p-value = 0.752
## alternative hypothesis: significant effects