#X0=sp.array([[-.1,0.]]) X0=sp.array([[kss*0.9,0.]]) Z0=-math.sqrt(.004) Y0=0 Xbar=sp.mat([[ks,ls]]) Zbar=0 Mu=0 Var=.0004 alpha=.4 delta=.1 reps=1000 T=250 GDP,I,C= MonteCarlo(PP,QQ,RR,SS,NN,X0,Y0,Z0,Xbar,Zbar,Mu,Var,alpha,delta,reps,T) X0=sp.array([[0.,0.]]) shock=-.005 Y0=0 Xbar=sp.mat([[ks,ls]]) Zbar=0 alpha=.4 delta=.1 T=40 GDP_s, invest_s, consumption_s=impulseResponse(PP,QQ,RR,SS,NN,X0,Y0,shock,Xbar,Zbar,alpha,delta,T) Autocorr(GDP,I,C) Corr(GDP,I,C)
C[i] = Y[i] - I[i] return Y, I, C # Setup for Problems 13-14 #X0=sp.array([[-.1,0.]]) global X0, Z0, Y0, Xbar, Zbar, Mu, Var, reps, T_monte global shock, T_irf X0_m = sp.array([[-.1,0.]]) Z0 = -math.sqrt(.004) Y0 = 0 Xbar = sp.mat([[ks,ls]]) Zbar = 0 Mu = 0 Var = .0004 reps = 1000 T_monte = 250 GDP_monte,I_monte,C_monte= MonteCarlo(PP,QQ,RR,SS,NN,X0_m,Y0,Z0,Xbar,Zbar,Mu, Var,alpha,delta,reps,T_monte, YICgen) X0_irf = sp.array([[0,0]]) shock = -.005 T_irf = 40 GDP_irf, invest_irf, consumption_irf=impulseResponse(PP, QQ, RR, SS, NN, X0_irf, Y0, YICgen, shock, Xbar, Zbar, alpha, delta, T_irf)