setwd("D:/TKT/RImportData")
library(plm)
## Loading required package: Formula
library(foreign)
library(tidyverse)
## Loading tidyverse: ggplot2
## Loading tidyverse: tibble
## Loading tidyverse: tidyr
## Loading tidyverse: readr
## Loading tidyverse: purrr
## Loading tidyverse: dplyr
## Conflicts with tidy packages ----------------------------------------------
## between(): dplyr, plm
## filter(): dplyr, stats
## lag(): dplyr, plm, stats
## lead(): dplyr, plm
library(car)
##
## Attaching package: 'car'
## The following object is masked from 'package:dplyr':
##
## recode
## The following object is masked from 'package:purrr':
##
## some
trang = read.dta("Panel1.dta")
View(trang)
trang %>% scatterplot(C ~ t|i, reg.line = FALSE, data = .) #Hoi quy C theo t, phan lo???i theo i
cor(trang) #He so tuong quan cho cac bien so de xem xet hien tuong da cong tuyen
## i t C Q PF LF
## i 1.00000000 0.0000000 -0.7086242 -0.8679359 0.01329393 -0.3399570
## t 0.00000000 1.0000000 0.5000271 0.2711141 0.93118760 0.6001491
## C -0.70862418 0.5000271 1.0000000 0.9263269 0.47904374 0.4143377
## Q -0.86793588 0.2711141 0.9263269 1.0000000 0.22761248 0.4248100
## PF 0.01329393 0.9311876 0.4790437 0.2276125 1.00000000 0.4867001
## LF -0.33995702 0.6001491 0.4143377 0.4248100 0.48670008 1.0000000
#Mo hinh Pooled OLS
#Gia su he so goc va he so chan la khong doi theo thoi gian va khong gian
#Gia su cac bien doc lap ngoai sinh chat
#(khong phu thuoc vao gia tri qua khu, hien tai va tuong lai cua sai so ngau nhien)
#Khong tinh den cac khac biet dac trung theo khong gian va thoi gian
#ma gop cac khac biet dec trung vao sai so ngau nhien
#vi vay sai so ngau nhien co the tuong quan voi bien doc lap
trang %>% plm(data = ., C ~ Q + PF + LF, model = "pooling") %>% summary()
## Pooling Model
##
## Call:
## plm(formula = C ~ Q + PF + LF, data = ., model = "pooling")
##
## Balanced Panel: n=6, T=15, N=90
##
## Residuals :
## Min. 1st Qu. Median 3rd Qu. Max.
## -520654 -250270 37333 208690 849700
##
## Coefficients :
## Estimate Std. Error t-value Pr(>|t|)
## (Intercept) 1.1586e+06 3.6059e+05 3.2129 0.00185 **
## Q 2.0261e+06 6.1807e+04 32.7813 < 2.2e-16 ***
## PF 1.2253e+00 1.0372e-01 11.8138 < 2.2e-16 ***
## LF -3.0658e+06 6.9633e+05 -4.4027 3.058e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 1.2647e+14
## Residual Sum of Squares: 6.8177e+12
## R-Squared: 0.94609
## Adj. R-Squared: 0.94421
## F-statistic: 503.118 on 3 and 86 DF, p-value: < 2.22e-16
#Mo hinh tac dong bien gia va kiem dinh gop
#Least - Squares Dummy Variable Model)
#He so chan khong thay doi theo thoi gian nhung thay doi theo khong gian
#He so goc khong thay doi theo thoi gian va khong gian
#Mo hinh tac dong mot chieu, xet den tac dong dac trung cho tung hang
lsdv = trang %>% lm(formula = C ~ Q + PF + LF + factor(i), data = .)
summary(lsdv)
##
## Call:
## lm(formula = C ~ Q + PF + LF + factor(i), data = .)
##
## Residuals:
## Min 1Q Median 3Q Max
## -551783 -159259 1796 137226 499296
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.312e+05 3.508e+05 -0.374 0.709
## Q 3.319e+06 1.714e+05 19.369 < 2e-16 ***
## PF 7.731e-01 9.732e-02 7.944 9.70e-12 ***
## LF -3.797e+06 6.138e+05 -6.187 2.37e-08 ***
## factor(i)2 6.017e+05 1.009e+05 5.964 6.17e-08 ***
## factor(i)3 1.337e+06 1.862e+05 7.183 2.99e-10 ***
## factor(i)4 1.778e+06 2.132e+05 8.339 1.61e-12 ***
## factor(i)5 1.828e+06 2.312e+05 7.907 1.15e-11 ***
## factor(i)6 1.706e+06 2.283e+05 7.475 8.07e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 210400 on 81 degrees of freedom
## Multiple R-squared: 0.9716, Adjusted R-squared: 0.9688
## F-statistic: 346.9 on 8 and 81 DF, p-value: < 2.2e-16
#it nhat mot gia tri p - value nho hon 0.05 cho thay tinh hop li cua mo hinh LSDV
#Pr(>F) co the bac bo gia thuyet H0
#Mo hinh khong tinh den tac dong dac trung cua thoi gian
#Mo hinh khong the hien tac dong cua cac bien khong thay doi theo thoi gian
#Mo hinh tac dong co dinh khong co bien gia FEM (Fix Effects Model)
library(plm)
FEM = trang %>% plm(C ~ Q + PF + LF, data = ., index = c("i", "t"), model = "within")
summary(FEM)
## Oneway (individual) effect Within Model
##
## Call:
## plm(formula = C ~ Q + PF + LF, data = ., model = "within", index = c("i",
## "t"))
##
## Balanced Panel: n=6, T=15, N=90
##
## Residuals :
## Min. 1st Qu. Median 3rd Qu. Max.
## -551783.1 -159258.6 1796.2 137225.9 499296.0
##
## Coefficients :
## Estimate Std. Error t-value Pr(>|t|)
## Q 3.3190e+06 1.7135e+05 19.3694 < 2.2e-16 ***
## PF 7.7307e-01 9.7319e-02 7.9437 9.698e-12 ***
## LF -3.7974e+06 6.1377e+05 -6.1869 2.375e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 5.0776e+13
## Residual Sum of Squares: 3.5865e+12
## R-Squared: 0.92937
## Adj. R-Squared: 0.92239
## F-statistic: 355.254 on 3 and 81 DF, p-value: < 2.22e-16
#He so chan rieng cua tung hang trong mo hinh FEM
fixef(FEM)
## 1 2 3 4 5 6
## -131236.0 470497.3 1205944.6 1646356.2 1697016.5 1575238.4
#Mo hinh tac dong ngau nhien (Random Effects Model)
#hay mo hinh sai so bo phan ECM (Error Components Model)
#Bieu dien he so chan thanh hai bo phan trung binh va sai so ngau nhien
#bieu dien lai khien sai so ngau nhien co hai bo phan:
#sai so ngau nhien dac trung cho tung ca the va sai so ngau nhien ket hop khong gian va thoi gian
#Neu bo phan sai so ngau nhien dac trung cho tung ca the co phuong sai bang 0, tuc la hang so
#thi co the thuc hien hoi quy gop FEM cho cac ca the
#Tuong quan cua sai so ngau nhien doi voi mot ca the la khong doi trong mot khoang thoi gian nhat dinh,
#tuonq quan nay la nhu nhau doi voi moi ca the
REM = trang %>% plm(C ~ Q + PF + LF, data =., index = c("i", "t"), model = "random")
summary(REM)
## Oneway (individual) effect Random Effect Model
## (Swamy-Arora's transformation)
##
## Call:
## plm(formula = C ~ Q + PF + LF, data = ., model = "random", index = c("i",
## "t"))
##
## Balanced Panel: n=6, T=15, N=90
##
## Effects:
## var std.dev share
## idiosyncratic 4.428e+10 2.104e+05 0.906
## individual 4.615e+09 6.793e+04 0.094
## theta: 0.3754
##
## Residuals :
## Min. 1st Qu. Median 3rd Qu. Max.
## -530516 -241650 50248 203965 783397
##
## Coefficients :
## Estimate Std. Error t-value Pr(>|t|)
## (Intercept) 1.0952e+06 3.7697e+05 2.9052 0.004665 **
## Q 2.1446e+06 8.8171e+04 24.3228 < 2.2e-16 ***
## PF 1.1757e+00 1.0356e-01 11.3531 < 2.2e-16 ***
## LF -3.0261e+06 7.2713e+05 -4.1616 7.466e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 8.0306e+13
## Residual Sum of Squares: 6.2698e+12
## R-Squared: 0.92193
## Adj. R-Squared: 0.9192
## F-statistic: 338.508 on 3 and 86 DF, p-value: < 2.22e-16
#So sanh 2 mo hinh FEM va REM
library(stargazer)
##
## Please cite as:
## Hlavac, Marek (2015). stargazer: Well-Formatted Regression and Summary Statistics Tables.
## R package version 5.2. http://CRAN.R-project.org/package=stargazer
stargazer(FEM, REM, title = "So sanh 2 mo hinh FEM và REM", type = "text")
##
## So sanh 2 mo hinh FEM và REM
## ============================================================
## Dependent variable:
## -----------------------------------------------
## C
## (1) (2)
## ------------------------------------------------------------
## Q 3,319,023.000*** 2,144,561.000***
## (171,354.100) (88,170.630)
##
## PF 0.773*** 1.176***
## (0.097) (0.104)
##
## LF -3,797,368.000*** -3,026,060.000***
## (613,773.100) (727,130.000)
##
## Constant 1,095,172.000***
## (376,967.000)
##
## ------------------------------------------------------------
## Observations 90 90
## R2 0.929 0.922
## Adjusted R2 0.922 0.919
## F Statistic 355.254*** (df = 3; 81) 338.508*** (df = 3; 86)
## ============================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
#Mo hinh tac dong ngau nhien hai chieu
#Tac dong ngau nhien theo ca chieu khong gian va thoi gian
#Theo phuong phap tiep can cua Amemiya
REM2chieu = trang %>% plm(C ~ Q + PF + LF, data = ., index = c("i", "t"),
model = "random",
random.method = "amemiya",
effect = "twoways")
summary(REM2chieu)
## Twoways effects Random Effect Model
## (Amemiya's transformation)
##
## Call:
## plm(formula = C ~ Q + PF + LF, data = ., effect = "twoways",
## model = "random", random.method = "amemiya", index = c("i",
## "t"))
##
## Balanced Panel: n=6, T=15, N=90
##
## Effects:
## var std.dev share
## idiosyncratic 4.732e+10 2.175e+05 0.061
## individual 6.536e+11 8.084e+05 0.837
## time 7.977e+10 2.824e+05 0.102
## theta : 0.9307 (id) 0.7 (time) 0.6984 (total)
##
## Residuals :
## Min. 1st Qu. Median 3rd Qu. Max.
## -554575 -153985 -11270 144817 453530
##
## Coefficients :
## Estimate Std. Error t-value Pr(>|t|)
## (Intercept) 7.9910e+05 5.7947e+05 1.3790 0.171468
## Q 3.2787e+06 1.7583e+05 18.6462 < 2.2e-16 ***
## PF 7.5411e-01 2.3730e-01 3.1779 0.002062 **
## LF -3.2458e+06 9.0000e+05 -3.6064 0.000520 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Total Sum of Squares: 2.1117e+13
## Residual Sum of Squares: 3.5633e+12
## R-Squared: 0.83126
## Adj. R-Squared: 0.82537
## F-statistic: 141.216 on 3 and 86 DF, p-value: < 2.22e-16
#Kiem dinh lua chon mo hinh Pooled OLS, FEM, REM
#Kiem dinh F, Wald test: neu cac he so chan cua tung ca the coi nhu bang 0 thi su dung Pooled OLS
#Kiem dinh Hausman de lua chon giua hai mo hinh REM va FEM
#Neu bac bo H0 thi FEM phu hop hon, H0: Ket qua giua hai phuong phap la khong khac biet
phtest(FEM, REM)
##
## Hausman Test
##
## data: C ~ Q + PF + LF
## chisq = 63.785, df = 3, p-value = 9.126e-14
## alternative hypothesis: one model is inconsistent
#Kiem dinh Breusch - Pagan de lua chon REM va Pooled OLS
ols = trang %>% plm(data = ., C ~ Q + PF + LF, model = "pooling")
plmtest(ols, type = "bp")
##
## Lagrange Multiplier Test - (Breusch-Pagan) for balanced panels
##
## data: C ~ Q + PF + LF
## chisq = 0.61309, df = 1, p-value = 0.4336
## alternative hypothesis: significant effects
#Neu p - value nho hon 0.05 thi phuong phap REM phu hop hon
#Kiem dinh tuong quan phan du
pcdtest(FEM, test = c("lm"))
##
## Breusch-Pagan LM test for cross-sectional dependence in panels
##
## data: C ~ Q + PF + LF
## chisq = 70.675, df = 15, p-value = 3.386e-09
## alternative hypothesis: cross-sectional dependence
#H0 la phan du giua cac ca the khong tuong quan