# Leading Economic Indicator 
# __________________________


#1. VAR Model with 2 Lags
#________________________

# mydata <- read.csv("K:/AIMS South Africa 2019/Data/Macro Data SA.csv", header=TRUE)
# mydata <- read.csv("/media/guest/Lexar/AIMS South Africa 2019/Data/Macro Data SA.csv",header=TRUE)
mydata <- read.csv("../data/Macro Data SA.csv", header=TRUE)

head(mydata)      # Shows the top of the data file.
attach(mydata)    # Variables in the datafile can be directly accessed 
# using their names. 

GDPts <- ts(GDP,frequency=4,start=c(1960,1))
SPIts <- ts(SPI,frequency=4,start=c(1960,1))
CPIts <- ts(CPI,frequency=4,start=c(1960,1))

plot(GDPts, type = "l")
plot(SPIts, type = "l")
plot(CPIts, type = "l")

GDPlnd <- diff(log(GDPts))
SPIlnd <- diff(log(SPIts))
CPIlnd <- diff(log(CPIts))

plot(GDPlnd, type = "l")
abline(0,0)
plot(SPIlnd, type = "l")
abline(0,0)
plot(CPIlnd, type = "l")
abline(0,0)

newdata <- data.frame(GDPlnd, SPIlnd)
head(newdata)

library(vars)

varmodel <- VAR(newdata,2)
summary(varmodel)

par(cex.axis=1.2, cex.lab = 1.2, cex.main=1.3, cex.sub=1)

impulse.SPIGDP <- irf(varmodel, impulse = "SPIlnd", 
      response = "GDPlnd", cumulative = "true")
plot(impulse.SPIGDP)

impulse.GDPSPI <- irf(varmodel, impulse = "GDPlnd", 
      response = "SPIlnd", cumulative = "true")
plot(impulse.GDPSPI)
  

# 2. VAR Model with Optimal Lag Length
# ____________________________________

# Remove all ojects from the workspace and all plots. 

# mydata <- read.csv("K:/AIMS South Africa 2019/Data/Macro Data SA.csv", header=TRUE)
# mydata <- read.csv("/media/guest/Lexar/AIMS South Africa 2019/Data/Macro Data SA.csv",header=TRUE)
mydata <- read.csv("../data/Macro Data SA.csv", header=TRUE)
head(mydata)      # Shows the top of the data file.
attach(mydata)    # Variables in the datafile can be directly accessed 
# using their names. 

GDPts <- ts(GDP,frequency=4,start=c(1960,1))
SPIts <- ts(SPI,frequency=4,start=c(1960,1))
CPIts <- ts(CPI,frequency=4,start=c(1960,1))

plot(GDPts, type = "l")
plot(SPIts, type = "l")
plot(CPIts, type = "l")

GDPlnd <- diff(log(GDPts))
SPIlnd <- diff(log(SPIts))
CPIlnd <- diff(log(CPIts))

plot(GDPlnd, type = "l")
abline(0,0)
plot(SPIlnd, type = "l")
abline(0,0)
plot(CPIlnd, type = "l")
abline(0,0)

newdata <- data.frame(GDPlnd, SPIlnd)
head(newdata)

library(vars)

varmodel.AIC <- VAR(newdata, lag.max=5, ic = "AIC")
summary(varmodel.AIC)

impulse.SPIGDP <- irf(varmodel.AIC, impulse = "SPIlnd", 
          response = "GDPlnd", cumulative = "true")
plot(impulse.SPIGDP)

impulse.GDPSPI <- irf(varmodel.AIC, impulse = "GDPlnd", 
          response = "SPIlnd", cumulative = "true")
plot(impulse.GDPSPI)