US1_W_Input

#

# USL201 World  Model Input (requires WL20.fx)

#

merge.forecast <- function (fx,n=1) {

x <- splice(fx$pred,fx$forecast[[n]])

colnames(x) <- seriesNames(fx$data$output)

return(x)

}

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

require(dse)

require(matlab)

#

# WL20 World  Model

#

f <- matrix( c(1.000000000,  0.00000000,  0.00000000,  0.00000000,

                      0.210941578,  1.01169571, -0.02519461, -0.09358484,

                     -0.003862528, -0.01360718,  0.96330129, -0.05250691,

                       0.018115378,  0.02303607, -0.03631204,  0.93554760

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

#

# Growth-and-Collapse Model

# To create a high-level steady state, uncomment next line

# f[2,2] <- 0.90

#

h <- matrix(c(0,    1,    0,    0,

0,    0,    1,    0,

                     0,    0,    0,    1

),byrow=TRUE,nrow=3,ncol=4)

k <- (f[,2:4,drop=FALSE])

WL20 <- SS(F=f,H=h,K=k,z0=c(1.0000000, -5.3541066, -0.7239263,  0.7703831),

              output.names=c("W1","W2","W3"))

WL20.data <- simulate(WL20,sampleT=150,noise=matrix(0,150,3),start=1950)

WL20.f <- forecast(l(WL20,WL20.data),horizon=50)

WL20.fx <- merge.forecast(WL20.f)

#

# USL201 World  Model Input (requires WL20.fx)

#

#

# Measurement Matrix (Growth)

#     L.US.E. L.US.U. GDP.US.  GDP.C.  GDP.I.  GDP.X.  GDP.G.

#[1,]  0.1955   0.138  0.1978  0.1972  0.1961 -0.1402  0.1976

#     P.US.TBILL. P.CPAPER. P.FED.FUNDS.  P.CPI. P.GDP. P.SP500.

#[1,]     0.00429  -0.01554       0.0127 0.19773 0.1967   0.1868

#     V.NYSE. P.S.P.DPR. P.S.P.EPR. Q.H.Starts.   K.US.      M1

#[1,]   0.166     -0.146     -0.112     -0.0202  0.1974  0.1953

#          M2 P.WPI.    Q.A.    Q.I.   O.B. P.FUELS. P.W.AG. P.W.MFG.

#[1,]  0.1979 0.1932  0.1918  0.1967 -0.173   0.1834  0.1983   0.1990

#     Q.OIL.   N.US. IMM.US.   U.US.   CAPU     EF Globalization

#[1,] -0.113  0.1951  0.1440  0.1967 -0.141 0.1867        0.0818

#        CO2 Q.FOSSIL.

#[1,]  0.180     0.129

#

# Fraction of Variance 

# [1] 0.698 0.854 0.900 0.935 0.955 0.972 0.981 0.987 0.991 0.995 0.997

#

f <- matrix( c(  0.8591446, 0.2138536,

                        0.0000000, 1.0000000

),byrow=TRUE,nrow=2,ncol=2)

h <- eye(1,2)

k <- f[1:2,1,drop=FALSE]

g <- matrix(c(0.2246092, -0.152583, 0.1470327,

                      0.0000000,  0.000000, 0.0000000

),byrow=TRUE,nrow=2,ncol=3)                      

US1 <- SS(F=f,H=h,K=k,G=g,z0=c( -0.7710952,  1.0000000),

              output.names=c("US1"),input.names=c("W1","W2","W3"))

print(US1)

tfplot(simulate(US1,sampleT=150,noise=matrix(0,150,1),start=1950,input=WL20.fx))

#