UKL20_TECHP Model

# Cut-and-Paste Code Below into Window Above and Run

#

# UKL20 TECHP Model   

# UKL20 = (Growth-CO2-LU) (CO2+E-Q)    (L+N+LU+EF-HDI)

# TECHP = (e+q-l-co2) (e+co2-l) (Overall growth)

#

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

require(dse)

require(matlab)

#

#Measurement Matrix 

#        co2=CO2/N e=ENERGY/N    q=GDP/N      l=L/N

#

#[1,] -0.511  0.182  0.616 -0.571

#[2,]  0.496  0.792 -0.129 -0.331

#[3,]  0.184  0.269  0.681  0.656

#

# Fraction of Variance 

#[1] 0.601 0.961 0.992 1.000

#

f <- matrix( c( 0.982134462, 0.011382523, -0.03559453,  0.101058476,

                      -0.110664748, 1.012314665,  0.20213095,  0.001913643,

                        0.006302377, 0.002529411,  0.66432950, -0.038675917,

0.00000000,  0.0000000,  0.0000000,  1.0000000000

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

#

# To destabilize the system, uncomment the following line

# f[1,1] <- 1.03; f[2,1] <- f[1,3] <- 0

#

h <- eye(3,4)

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

UK_TECHP <- SS(F=f,H=h,K=k,z0=c(0.101058476,  0.001913643, -0.038675917,  1.0000000000),

              output.names=c("TECHP1","TECHP2","TECHP3"))

print(UK_TECHP)

is.SS(UK_TECHP)

stability(m <- SS(F=f[1:3,1:3,drop=FALSE],H=eye(3),Q=eye(3,3),R=eye(3),

               output.names=c("UK1","UK2","UK3")))

shockDecomposition(m)

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

tfplot(UK_TECHP.data)

#

#

# Measurement Matrix UKL20 UK1=(Growth-CO2-LU),   UK2=(CO2+E-Q),     UK2=(L+N+LU+EF-HDI)

#     EN.ATM.CO2E.KT EG.USE.COMM.KT.OE NY.GDP.MKTP.KD SL.TLF.TOTL.IN SP.POP.TOTL SL.UEM.TOTL.ZS     KOF

#[1,]         -0.319             0.211         0.4169          0.315      0.4042         -0.324  0.3864

#[2,]          0.392             0.558         0.0249         -0.321     -0.0222         -0.126  0.0656

#[3,]         -0.127             0.225         0.0473          0.417      0.3184          0.712 -0.2282

 #        EF    HDI

#[1,] 0.0113  0.403

#[2,] 0.6356  0.083

#[3,] 0.2818 -0.128

#

# Fraction of Variance 

#[1] 0.634 0.880 0.934 0.977 0.989 0.997 0.999 1.000 1.000

#

f <- matrix( c(   0.47864950, -0.002664639, -0.121149,  0.06639632,

                        -0.08049853,  0.259398765, -0.1348599, -0.02547381,

                          0.54809994, -0.176075545,  1.0811257,  0.13816548,

0.00000000,        0.0000000,  0.0000000,  1.0000000000

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

g <- matrix( c(0.7910857, -0.2303096,  0.5810965,

                       0.2197815 , 0.8920518,  0.5610796,

                      -0.7546816,  0.3954853, -0.4266993,

                       0.0000000,  0.0000000,  0.0000000

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

h <- eye(3,4)

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

UKL20 <- SS(F=f,H=h,K=k,G=g,z0=c(-1.797932, -2.080600,  1.658209,  1.0000000000),

               output.names=c("UK1","UK2","UK3"))

print(UKL20)

is.SS(UKL20)

stability(m <- SS(F=f[1:3,1:3,drop=FALSE],H=eye(3),Q=eye(3,3),R=eye(3),

               output.names=c("UK1","UK2","UK3")))

shockDecomposition(m)

# tfplot(simulate(UKL20,sampleT=150))

UKL20.data <- simulate(UKL20,sampleT=150,noise=matrix(0,150,3),input=outputData(UK_TECHP.data))

AIC(m2 <- l(UKL20,UKL20.data))

tfplot(m2)