library(plm)
## Warning: package 'plm' was built under R version 3.2.5
## Loading required package: Formula
mydata <- read.csv("C:\\Users\\t420\\Desktop\\R.csv")
attach(mydata)
Y <- cbind(lnrealgdp)
X <- cbind(expgdp, gospegdp,debtgdp,bmoneygdp,remigdp,conspendgdp, lnfdinflow,ginigini )
#Set Data as Panel Data
pdata <- plm.data(mydata, index=c("country","year"))
#Descriptive Statistics
summary(Y)
##    lnrealgdp    
##  Min.   :5.637  
##  1st Qu.:6.525  
##  Median :7.155  
##  Mean   :7.200  
##  3rd Qu.:7.772  
##  Max.   :9.260
summary(X)
##      expgdp          gospegdp         debtgdp          bmoneygdp     
##  Min.   : -3.30   Min.   : 5.203   Min.   : -0.188   Min.   :  1.95  
##  1st Qu.: 18.23   1st Qu.:13.275   1st Qu.: 37.153   1st Qu.: 30.38  
##  Median : 32.20   Median :16.221   Median : 51.603   Median : 45.25  
##  Mean   : 38.19   Mean   :16.580   Mean   : 56.017   Mean   : 52.78  
##  3rd Qu.: 52.25   3rd Qu.:19.525   3rd Qu.: 70.025   3rd Qu.: 63.55  
##  Max.   :121.00   Max.   :31.800   Max.   :211.000   Max.   :140.00  
##     remigdp            conspendgdp       lnfdinflow       ginigini     
##  Min.   :-1.000e+00   Min.   :  2.16   Min.   :13.81   Min.   : 718.2  
##  1st Qu.: 1.000e+00   1st Qu.: 52.55   1st Qu.:18.88   1st Qu.:1075.8  
##  Median : 3.000e+00   Median : 71.40   Median :20.65   Median :1265.6  
##  Mean   : 1.003e+09   Mean   : 63.63   Mean   :20.23   Mean   :1374.3  
##  3rd Qu.: 8.000e+00   3rd Qu.: 77.10   3rd Qu.:22.00   3rd Qu.:1622.1  
##  Max.   : 2.870e+10   Max.   :138.50   Max.   :24.49   Max.   :2510.0
#Pooled Estimator
pooling <- plm(Y~X, data=pdata, model="pooling")
summary(pooling)
## Oneway (individual) effect Pooling Model
## 
## Call:
## plm(formula = Y ~ X, data = pdata, model = "pooling")
## 
## Balanced Panel: n=13, T=24, N=312
## 
## Residuals :
##    Min. 1st Qu.  Median 3rd Qu.    Max. 
## -1.1500 -0.3410  0.0493  0.2930  1.0500 
## 
## Coefficients :
##                 Estimate  Std. Error t-value  Pr(>|t|)    
## (Intercept)   4.3146e+00  4.0081e-01 10.7646 < 2.2e-16 ***
## Xexpgdp       1.0107e-02  1.6660e-03  6.0667 3.888e-09 ***
## Xgospegdp     1.6906e-02  5.5032e-03  3.0720 0.0023193 ** 
## Xdebtgdp      3.6908e-03  1.0600e-03  3.4818 0.0005714 ***
## Xbmoneygdp    3.9606e-03  1.3046e-03  3.0359 0.0026062 ** 
## Xremigdp      6.2750e-12  7.4009e-12  0.8479 0.3971796    
## Xconspendgdp -6.1832e-03  1.4786e-03 -4.1819 3.789e-05 ***
## Xlnfdinflow   7.4206e-02  1.6249e-02  4.5667 7.216e-06 ***
## Xginigini     5.0187e-04  1.0123e-04  4.9577 1.189e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    222.72
## Residual Sum of Squares: 63.837
## R-Squared:      0.71338
## Adj. R-Squared: 0.6928
## F-statistic: 94.2678 on 8 and 303 DF, p-value: < 2.22e-16
#Between Estimator
between <- plm(Y~X, data=pdata, model="between")
summary(between)
## Oneway (individual) effect Between Model
## 
## Call:
## plm(formula = Y ~ X, data = pdata, model = "between")
## 
## Balanced Panel: n=13, T=24, N=312
## 
## Residuals :
##    Min. 1st Qu.  Median 3rd Qu.    Max. 
## -0.5360 -0.3290  0.0219  0.1530  0.5670 
## 
## Coefficients :
##                 Estimate  Std. Error t-value Pr(>|t|)
## (Intercept)   3.9081e+00  3.9928e+00  0.9788   0.3831
## Xexpgdp       2.3814e-02  2.1080e-02  1.1297   0.3218
## Xgospegdp    -1.8953e-02  6.0551e-02 -0.3130   0.7699
## Xdebtgdp      2.0959e-02  1.5655e-02  1.3388   0.2516
## Xbmoneygdp    3.4642e-03  1.5139e-02  0.2288   0.8302
## Xremigdp     -2.1675e-13  9.0874e-11 -0.0024   0.9982
## Xconspendgdp -2.0061e-03  1.4211e-02 -0.1412   0.8946
## Xlnfdinflow   4.8326e-02  1.5793e-01  0.3060   0.7749
## Xginigini     3.5686e-04  1.6851e-03  0.2118   0.8426
## 
## Total Sum of Squares:    8.2835
## Residual Sum of Squares: 1.4876
## R-Squared:      0.82041
## Adj. R-Squared: 0.25244
## F-statistic: 2.2842 on 8 and 4 DF, p-value: 0.22153
#First Difference Estimator
firstdiff <- plm(Y~X, data=pdata, model="fd")
summary(firstdiff)
## Oneway (individual) effect First-Difference Model
## 
## Call:
## plm(formula = Y ~ X, data = pdata, model = "fd")
## 
## Balanced Panel: n=13, T=24, N=312
## 
## Residuals :
##     Min.  1st Qu.   Median  3rd Qu.     Max. 
## -0.19800 -0.01400  0.00307  0.01690  0.12100 
## 
## Coefficients :
##                 Estimate  Std. Error t-value  Pr(>|t|)    
## (intercept)   3.5935e-02  1.9309e-03 18.6105 < 2.2e-16 ***
## Xexpgdp      -2.5085e-04  3.5197e-04 -0.7127 0.4766037    
## Xgospegdp    -7.2190e-04  1.1890e-03 -0.6072 0.5442183    
## Xdebtgdp     -1.0793e-03  2.8096e-04 -3.8413 0.0001503 ***
## Xbmoneygdp    2.3501e-04  3.2536e-04  0.7223 0.4706775    
## Xremigdp     -1.1426e-12  4.2525e-12 -0.2687 0.7883639    
## Xconspendgdp -8.7997e-05  4.9966e-04 -0.1761 0.8603274    
## Xlnfdinflow   7.6214e-03  2.3087e-03  3.3012 0.0010832 ** 
## Xginigini     3.4632e-05  2.4073e-05  1.4386 0.1513291    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    0.29026
## Residual Sum of Squares: 0.25982
## R-Squared:      0.10487
## Adj. R-Squared: 0.10171
## F-statistic: 4.24685 on 8 and 290 DF, p-value: 7.7155e-05
#Fixed Effects or Within Estimator
fixed <- plm(Y~X, data=pdata, model="within")
summary(fixed)
## Oneway (individual) effect Within Model
## 
## Call:
## plm(formula = Y ~ X, data = pdata, model = "within")
## 
## Balanced Panel: n=13, T=24, N=312
## 
## Residuals :
##      Min.   1st Qu.    Median   3rd Qu.      Max. 
## -0.304000 -0.086100 -0.000298  0.084000  0.422000 
## 
## Coefficients :
##                 Estimate  Std. Error t-value  Pr(>|t|)    
## Xexpgdp       3.6486e-05  9.4116e-04  0.0388  0.969103    
## Xgospegdp    -2.3746e-03  2.9443e-03 -0.8065  0.420611    
## Xdebtgdp     -1.9105e-03  3.8767e-04 -4.9280 1.397e-06 ***
## Xbmoneygdp    8.2976e-03  7.2089e-04 11.5101 < 2.2e-16 ***
## Xremigdp      9.4759e-12  3.3653e-12  2.8158  0.005198 ** 
## Xconspendgdp -6.7660e-03  1.1002e-03 -6.1495 2.560e-09 ***
## Xlnfdinflow   9.0888e-02  6.6726e-03 13.6211 < 2.2e-16 ***
## Xginigini    -4.0698e-06  4.6070e-05 -0.0883  0.929667    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Total Sum of Squares:    23.921
## Residual Sum of Squares: 5.0367
## R-Squared:      0.78944
## Adj. R-Squared: 0.7363
## F-statistic: 136.379 on 8 and 291 DF, p-value: < 2.22e-16
#Random Effects or Between Estimator
random <- plm(Y~X, data=pdata, model="between")
summary(random)
## Oneway (individual) effect Between Model
## 
## Call:
## plm(formula = Y ~ X, data = pdata, model = "between")
## 
## Balanced Panel: n=13, T=24, N=312
## 
## Residuals :
##    Min. 1st Qu.  Median 3rd Qu.    Max. 
## -0.5360 -0.3290  0.0219  0.1530  0.5670 
## 
## Coefficients :
##                 Estimate  Std. Error t-value Pr(>|t|)
## (Intercept)   3.9081e+00  3.9928e+00  0.9788   0.3831
## Xexpgdp       2.3814e-02  2.1080e-02  1.1297   0.3218
## Xgospegdp    -1.8953e-02  6.0551e-02 -0.3130   0.7699
## Xdebtgdp      2.0959e-02  1.5655e-02  1.3388   0.2516
## Xbmoneygdp    3.4642e-03  1.5139e-02  0.2288   0.8302
## Xremigdp     -2.1675e-13  9.0874e-11 -0.0024   0.9982
## Xconspendgdp -2.0061e-03  1.4211e-02 -0.1412   0.8946
## Xlnfdinflow   4.8326e-02  1.5793e-01  0.3060   0.7749
## Xginigini     3.5686e-04  1.6851e-03  0.2118   0.8426
## 
## Total Sum of Squares:    8.2835
## Residual Sum of Squares: 1.4876
## R-Squared:      0.82041
## Adj. R-Squared: 0.25244
## F-statistic: 2.2842 on 8 and 4 DF, p-value: 0.22153
#LM test for random effects VS Pooling
plmtest(pooling)
## 
##  Lagrange Multiplier Test - (Honda)
## 
## data:  Y ~ X
## normal = 45.798, p-value < 2.2e-16
## alternative hypothesis: significant effects
#LM test for fixed effets VS pooling
pFtest(fixed,pooling)
## 
##  F test for individual effects
## 
## data:  Y ~ X
## F = 283.1, df1 = 12, df2 = 291, p-value < 2.2e-16
## alternative hypothesis: significant effects
pbgtest(fixed)
## 
##  Breusch-Godfrey/Wooldridge test for serial correlation in panel
##  models
## 
## data:  Y ~ X
## chisq = 168.71, df = 24, p-value < 2.2e-16
## alternative hypothesis: serial correlation in idiosyncratic errors