Venezuela

#

# VEL20 BAU Model

#

AIC <- function(model) {informationTestsCalculations(model)[3]}

require(dse)

require(matlab)

# Measurement Matrix                    Growth, (LU-GDP), (EF+HDI-CO2-E)

#     EN.ATM.CO2E.KT EG.USE.COMM.KT.OE SL.TLF.TOTL.IN SP.POP.TOTL

#[1,]         0.3356            0.3346         0.3476      0.3495

#[2,]         0.0463            0.0144        -0.1485     -0.0859

#[3,]        -0.4995           -0.3229        -0.0869     -0.0911

#     SL.UEM.TOTL.ZS NY.GDP.MKTP.KD    KOF    EF    HDI

#[1,]          0.297          0.331  0.332 0.333  0.337

#[2,]          0.791         -0.479  0.141 0.106 -0.287

#[3,]          0.182          0.114 -0.259 0.608  0.384

#

# Fraction of Variance 

#[1] 0.902 0.951 0.976 0.989 0.996 0.999 0.999 1.000 1.000

#

f <- matrix( c(0.999861788, -0.015893040, 0.08759642,  0.168215354,

                     -0.007373528,  0.919408815, 0.11661879, -0.036413151,

                     -0.008284316, -0.004304076, 0.92326951,  0.002922896,

0.00000000,  0.0000000,  0.0000000,  1.0000000000

),byrow=TRUE,nrow=4,ncol=4)

h <- eye(3,4)

k <- (f[,1:3,drop=FALSE])

VEL20 <- SS(F=f,H=h,K=k,z0=c(0.168215354, -0.036413151,  0.002922896,  1.0000000000),

              output.names=c("VE1","VE2","VE3"))

print(VEL20)

is.SS(VEL20)

stability(m0 <- SS(F=f[1:3,1:3,drop=FALSE],H=eye(3),Q=eye(3),R=eye(3),output.names=c("VE1","VE2","VE3")))

# tfplot(simulate(VEL20,sampleT=150))

VEL20.data <- simulate(VEL20,sampleT=150,noise=matrix(0,150,3),start=1960)

VEL20.f <- forecast(m <- l(VEL20,VEL20.data),horizon=150)

tfplot(VEL20.f)

AIC(m)

#

# Negative Shock (change shock=1 for positive)

#

shockDecomposition(m0,shock=-1)