Argentina

#

# ARL20 BAU Model (Cut-and-paste following code into window above and Run (Cmd-Enter))

#

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

#

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

#[1,]          0.344             0.349          0.345        0.35265

#[2,]         -0.194            -0.141         -0.178       -0.00772

#[3,]          0.352            -0.124          0.139        0.10226

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

#[1,]       0.350          0.286  0.331 -0.288 0.3457

#[2,]       0.109          0.656  0.323  0.600 0.0583

#[3,]       0.146         -0.238 -0.456  0.559 0.4827

#

# Fraction of Variance 

#[1] 0.883 0.968 0.988 0.995 0.997 0.999 0.999 1.000 1.000

#

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

require(dse)

require(matlab)

f <- matrix( c( 1.02363961, -0.01940207, -0.01209545,  0.20427418,

                     -0.03587959,  1.01618492,  0.07421950, -0.05457570,

                     -0.01008192, -0.01054417,  0.87855680,  0.01145055,

0.00000000,  0.0000000,  0.0000000,  1.0000000000

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

#

# Stabilize (un-comment following line

# f[1,1] <- 0.91 ; f[2,2] <- 0.75 ; f[3,3] <- 0.66 #  World-System Input

# f[1,1] <- 0.90 ; f[2,2] <- 0.99 ; f[3,3] <- 0.66 #  US Input

# f[1,1] <- 0.67 ; f[2,2] <- 0.48 ; f[3,3] <- 0.74 #  LAC Input

# f[1,1] <- 0.97 ; f[2,2] <- 0.96 ; f[3,3] <- 0.83 #  Steady State

# f[1,1] <- f[2,2] <- f[3,3] <- 1                  #  Random Walk w/fb drift

#

#        f[2,3] <- 0.5 ; f[3,2] <- -0.5              #  Improbable Feedback Effects

# f[2,3] <- 0.1534126 ; f[3,2] <- -0.0260649   #  Probable Feedback        

# 

h <- eye(3,4)

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

ARL20 <- SS(F=f,H=h,K=k,z0=c( 0.20427418, -0.05457570,  0.01145055,  1.0000000000),

              output.names=c("AR1","AR2","AR"))

print(ARL20 )

is.SS(ARL20 )

stability(m0 <- SS(F=f[1:3,1:3,drop=FALSE],H=eye(3),Q=eye(3),R=eye(3),output.names=c("AR1","AR2","AR3")) )

#

# Uncomment for RW or N(0,1) Error

# tfplot(ARL20.data <- simulate(ARL20 ,sampleT=100, start=1960))

#

# Comment out following line for RW or N(0,1) Error

ARL20.data <- simulate(ARL20 ,sampleT=100,noise=matrix(0,100,3),start=1960)

ARL20.f <- forecast(l(ARL20 ,ARL20.data),horizon=100)

tfplot(ARL20.f)

AIC(m <- l(ARL20 ,ARL20.data))

shockDecomposition(m0)

#

# Bootstrap Confidence Intervals on System Matrix Coefficients

#

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

# [1,]  1.0050314   1.02364  1.0446273    0.33    0.67  0.017197 0.003241

# [2,] -0.0523717  -0.03588 -0.0234874    0.53    0.47  0.018435 1.061632

# [3,] -0.0194893  -0.01008 -0.0043789    0.46    0.54  0.006085 1.035892

# [4,] -0.0998499  -0.01940  0.0446680    0.73    0.27  0.066414 1.020095

# [5,]  0.9595890   1.01618  1.0898815    0.24    0.76  0.083708 0.032752

# [6,] -0.0260649  -0.01054  0.0007147    0.38    0.62  0.012116 1.036701

# [7,] -0.1192665  -0.01210  0.0802624    0.41    0.59  0.074696 1.047748

# [8,]  0.0004819   0.07422  0.1534126    0.73    0.27  0.062934 0.911983

# [9,]  0.8056733   0.87856  0.9258109    0.45    0.55  0.045288 0.160712

#[10,]  0.1883736   0.20427  0.2300371    0.54    0.46  0.019603 0.812596

#[11,] -0.0860795  -0.05458 -0.0279077    0.52    0.48  0.029330 1.078579

#[12,] -0.0014950   0.01145  0.0255517    0.57    0.43  0.011638 1.008999

#