Trail3 <- lm(Strict ~ GII + HDI + IHDI + MPI + HealthExp + LEI + GNIperCapita + Pop_Den, data = CleanDepInd)
print(summary(Trail3))##
## Call:
## lm(formula = Strict ~ GII + HDI + IHDI + MPI + HealthExp + LEI +
## GNIperCapita + Pop_Den, data = CleanDepInd)
##
## Residuals:
## Min 1Q Median 3Q Max
## -69.403 -6.466 1.032 9.284 22.901
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.102e+01 2.859e+01 -0.735 0.4639
## GII 5.791e+01 2.446e+01 2.368 0.0198 *
## HDI 8.769e+01 5.721e+01 1.533 0.1284
## IHDI -1.992e+01 5.212e+01 -0.382 0.7031
## MPI NA NA NA NA
## HealthExp -4.110e-01 6.616e-01 -0.621 0.5358
## LEI 3.901e+01 3.389e+01 1.151 0.2524
## GNIperCapita -2.195e-04 1.919e-04 -1.144 0.2553
## Pop_Den 2.378e-03 2.330e-03 1.020 0.3099
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15.24 on 101 degrees of freedom
## (97 observations deleted due to missingness)
## Multiple R-squared: 0.1611, Adjusted R-squared: 0.103
## F-statistic: 2.771 on 7 and 101 DF, p-value: 0.0112Loading CAGR Index and sorting low growth to high growth, ranking accordingly
CAGR <- read.csv("C:/Users/ramya.emandi/Desktop/Econ Policy/COVID Indices/index.csv")
colnames(CAGR) [3] <- "index"
View(CAGR)
I1 <- CAGR[order(CAGR$index), ]
rankI1 <- c(1:251)
I1 <- cbind(I1,rankI1)
view(I1)Ranking the stringency index
I2 <- CleanDepInd[order(CleanDepInd$Strict), ]
rankI2 <- c(1:206)
I2 <- cbind(I2,rankI2)
View(I2)merge both rankings (stringency and CAGR)
Index <- merge(x = I1, y = I2, by.x = "Countries_Confirmed.CNTRY_NAME", by.y = "Country", all.x = TRUE)
View(Index)
Index$rank <- Index$rankI1 + Index$rankI2linear regression of combined ranking index (dep) and HDR
reg <- lm(rank ~ GII + HDI + IHDI + MPI + HealthExp + LEI + GNIperCapita + Pop_Den, data = Index)
print(summary(reg))##
## Call:
## lm(formula = rank ~ GII + HDI + IHDI + MPI + HealthExp + LEI +
## GNIperCapita + Pop_Den, data = Index)
##
## Residuals:
## Min 1Q Median 3Q Max
## -131.846 -45.321 1.063 54.575 177.217
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.899e+02 1.292e+02 -1.470 0.1444
## GII 2.124e+02 1.102e+02 1.927 0.0566 .
## HDI 2.496e+02 2.538e+02 0.984 0.3275
## IHDI 3.594e+00 2.267e+02 0.016 0.9874
## MPI NA NA NA NA
## HealthExp 1.255e+00 2.919e+00 0.430 0.6682
## LEI 1.399e+02 1.524e+02 0.918 0.3605
## GNIperCapita -8.530e-04 8.453e-04 -1.009 0.3151
## Pop_Den 5.931e-03 1.014e-02 0.585 0.5599
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 70.39 on 109 degrees of freedom
## (134 observations deleted due to missingness)
## Multiple R-squared: 0.08358, Adjusted R-squared: 0.02473
## F-statistic: 1.42 on 7 and 109 DF, p-value: 0.2044new indicator testing numbers
test <- read.csv("C:/Users/ramya.emandi/Desktop/Econ Policy/COVID Indices/owid-covid-data.csv")
test$testperpop <- test$Sum.of.total_tests/ test$Average.of.population
I3 <- test[order(-test$testperpop), ]
rankI3 <- c(1:213)
I3 <- cbind(I3,rankI3)
View(I3)Merge I2, I3, I3
Index3 <- merge(x = Index, y = I3, by.x = "Countries_Confirmed.CNTRY_NAME", by.y = "Row.Labels", all.x = TRUE)
View(Index3)
Index3$rank <- Index3$rankI1 + Index3$rankI2 + Index3$rankI3checking the correlation of testing indicator to HDR variables
reg <- lm(testperpop ~ GII + HDI + IHDI + HealthExp + LEI + GNIperCapita + Pop_Den, data = Index3)
print(summary(reg))##
## Call:
## lm(formula = testperpop ~ GII + HDI + IHDI + HealthExp + LEI +
## GNIperCapita + Pop_Den, data = Index3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.1705 -0.4792 -0.1138 0.2906 7.5802
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.364e+00 3.723e+00 1.441 0.1549
## GII -5.546e+00 3.030e+00 -1.830 0.0724 .
## HDI -2.134e+00 7.434e+00 -0.287 0.7751
## IHDI -1.592e+00 6.188e+00 -0.257 0.7979
## HealthExp -1.372e-01 8.060e-02 -1.702 0.0941 .
## LEI 1.443e-01 4.465e+00 0.032 0.9743
## GNIperCapita 3.621e-05 2.128e-05 1.702 0.0941 .
## Pop_Den -4.761e-04 2.148e-04 -2.217 0.0306 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.311 on 58 degrees of freedom
## (185 observations deleted due to missingness)
## Multiple R-squared: 0.3577, Adjusted R-squared: 0.2802
## F-statistic: 4.615 on 7 and 58 DF, p-value: 0.0003724checking the correlation of hospital beds indicator to HDR variables
reg <- lm(Average.of.hospital_beds_per_thousand ~ GII + HDI + IHDI + HealthExp + LEI + GNIperCapita + Pop_Den, data = Index3)
print(summary(reg))##
## Call:
## lm(formula = Average.of.hospital_beds_per_thousand ~ GII + HDI +
## IHDI + HealthExp + LEI + GNIperCapita + Pop_Den, data = Index3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.7647 -0.8919 -0.1348 0.6387 8.0483
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.701e+00 3.100e+00 2.484 0.014636 *
## GII -3.173e+00 2.569e+00 -1.235 0.219742
## HDI -5.227e+00 6.137e+00 -0.852 0.396463
## IHDI 2.227e+01 5.364e+00 4.152 6.94e-05 ***
## HealthExp 3.126e-02 7.810e-02 0.400 0.689791
## LEI -1.544e+01 4.058e+00 -3.805 0.000244 ***
## GNIperCapita -5.742e-05 1.955e-05 -2.937 0.004112 **
## Pop_Den 2.163e-04 2.383e-04 0.908 0.366182
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.573 on 100 degrees of freedom
## (143 observations deleted due to missingness)
## Multiple R-squared: 0.5551, Adjusted R-squared: 0.5239
## F-statistic: 17.82 on 7 and 100 DF, p-value: 3.597e-15Linear regression of rank (stringency, CAGR and testing per population) to HDR indicators
reg <- lm(rank ~ GII + HDI + IHDI + HealthExp + LEI + GNIperCapita + Pop_Den, data = Index3)
print(summary(reg))##
## Call:
## lm(formula = rank ~ GII + HDI + IHDI + HealthExp + LEI + GNIperCapita +
## Pop_Den, data = Index3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -151.38 -50.63 -12.59 42.25 262.92
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.467e+02 1.435e+02 -1.023 0.308730
## GII 4.200e+02 1.225e+02 3.430 0.000855 ***
## HDI 2.089e+01 2.819e+02 0.074 0.941061
## IHDI 2.756e+02 2.519e+02 1.094 0.276236
## HealthExp 3.271e+00 3.243e+00 1.009 0.315349
## LEI 1.063e+02 1.693e+02 0.628 0.531416
## GNIperCapita -1.572e-03 9.390e-04 -1.674 0.096935 .
## Pop_Den 1.409e-02 1.126e-02 1.251 0.213622
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 78.19 on 109 degrees of freedom
## (134 observations deleted due to missingness)
## Multiple R-squared: 0.2471, Adjusted R-squared: 0.1987
## F-statistic: 5.11 on 7 and 109 DF, p-value: 4.774e-05######author: “Ramya Emandi”