ZA_20 Model

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#                  Cut-and-Paste Code below into window above and Run

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# ZA20 (South Africa) BAU Model

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

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#     EN.ATM.CO2E.KT EG.USE.COMM.KT.OE NY.GDP.MKTP.KD SL.TLF.TOTL.IN

#[1,]          0.360             0.352          0.368        0.36952

#[2,]         -0.128             0.194         -0.103        0.07516

#[3,]         -0.332             0.370          0.134        0.00362

#     SP.POP.TOTL SL.UEM.TOTL.ZS SL.UEM.TOTL.NE.ZS    KOF     EF HDI

#[1,]      0.3708          0.343             0.334  0.304 -0.126   0

#[2,]      0.0294          0.210             0.360 -0.386  0.778   0

#[3,]      0.0879         -0.485            -0.170  0.576  0.363   0

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# Fraction of Variance 

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

require(dse)

require(matlab)

f <- matrix( c(1.01675133, -0.004626103, -0.01453521,  0.165772597,

                     -0.03542798,  0.971611702, -0.16541610,  0.007325817,

                     -0.01614396,  0.072011756,  1.01788049, -0.033273933,

0.00000000,  0.0000000,  0.0000000,  1.0000000000

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

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# To stabilize model, Uncomment next Line

# f[1,1] <- 0.99651798; f[2,2] <- 0.952276629; f[3,3] <-  0.99762467

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h <- eye(3,4)

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

ZA20 <- SS(F=f,H=h,K=k,z0=c( 0.165772597,  0.007325817, -0.033273933,  1.0000000000),

              output.names=c("ZA1","ZA2","ZA3"))

print(ZA20)

is.SS(ZA20)

stability(ZA20)

# tfplot(simulate(ZA20,sampleT=100))

ZA20.data <- simulate(ZA20,sampleT=100,noise=matrix(0,100,3),start=1950)

ZA20.f <- forecast(l(ZA20,ZA20.data),horizon=100)

tfplot(ZA20.f)

AIC(l(ZA20,ZA20.data))

ZA20x <- SS(F=f,H=h,Q=eye(4,3),R=eye(3,3),z0=c( 0.165772597,  0.007325817, -0.033273933,  1.0000000000),

              output.names=c("ZA1","ZA2","ZA3"))

shockDecomposition(ZA20x)

#          LCI Parameter       UCI P>=T[1] P< T[1] Std. Dev.    Bias

 #[1,]  1.00531  1.016751  1.031027    0.29    0.71  0.010009 0.00341

# [2,] -0.04364 -0.035428 -0.028557    0.42    0.58  0.006743 1.05413

# [3,] -0.02682 -0.016144 -0.008613    0.59    0.41  0.007626 1.03246

# [4,] -0.03624 -0.004626  0.021394    0.56    0.44  0.021052 1.02001

# [5,]  0.95355  0.971612  0.988376    0.23    0.77  0.012605 0.05474

# [6,]  0.05507  0.072012  0.094564    0.50    0.50  0.014750 0.94304

# [7,] -0.09647 -0.014535  0.060314    0.63    0.37  0.063817 1.01286

# [8,] -0.23248 -0.165416 -0.106910    0.65    0.35  0.054894 1.17959

# [9,]  0.97022  1.017880  1.064831    0.28    0.72  0.040578 0.02518

#[10,]  0.15525  0.165773  0.179095    0.69    0.31  0.011726 0.84493

#[11,] -0.02283  0.007326  0.029121    0.62    0.38  0.022194 1.00763

#[12,] -0.05148 -0.033274 -0.018334    0.51    0.49  0.013260 1.05205

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