model{
for(t in 1:T) {
C[t] <- CONS[t]
Y[t] <- INC[t]}

for(t in p+1:T){
C[t] ~ dnorm(C.mu[t], C.tau)
Y[t] ~ dnorm(Y.mu[t], Y.tau)
C.mu[t] <- alp1+Clag1[t]+Ylag1[t]
Y.mu[t] <- alp2+Ylag2[t]+Clag2[t]
Clag1[t] <-  rho1[1]*C[t-1]+ rho1[2]*C[t-2]+ rho1[3]*C[t-3]+ rho1[4]*C[t-4]
Ylag1[t] <- beta1[1]*Y[t-1]+beta1[2]*Y[t-2]+beta1[3]*Y[t-3]+beta1[4]*Y[t-4]
Ylag2[t] <-  rho2[1]*Y[t-1]+ rho2[2]*Y[t-2]+ rho2[3]*Y[t-3]+ rho2[4]*Y[t-4]
Clag2[t] <- beta2[1]*C[t-1]+beta2[2]*C[t-2]+beta2[3]*C[t-3]+beta2[4]*C[t-4]}

alp1 ~ dnorm(0,0.001)
alp2 ~ dnorm(0,0.001)

for(m in 1:p){
rho1[m] ~ dnorm(0,0.01)
rho2[m] ~ dnorm(0,0.01)
beta1[m] ~ dnorm(0,0.01)
beta2[m] ~ dnorm(0,0.01)}

C.tau ~ dgamma(0.001,0.001)
Y.tau ~ dgamma(0.001,0.001)}
