# GRO3.yaml Model definition file for the stochastic growth model with recursive preferences and stochastic volatility # Copyright (C) 2011-2013 Christophe Gouel # Licensed under the Expat license, see LICENSE.txt declarations: states: [K, Z, Sigma] controls: [C, L, Uc, U, Y, V, Vt] expectations: [EC, EVt] shocks: [Epsilon, Omega] parameters: [tau, delta, beta, rhoZ, alpha, theta, rhoSig, SigmaBar, eta, nu, Psi] equations: arbitrage: - Uc = beta*EVt^(1/nu-1)*EC | -inf <= C <= inf - (1-theta)*C = theta*(1-alpha)*Y*(1/L-1) | -inf <= L <= inf - Uc = (theta*(1-tau)/nu)*U^(1/nu)/C | -inf <= Uc <= inf - U = (C^theta*(1-L)^(1-theta))^(1-tau) | -inf <= U <= inf - Y = exp(Z)*K^alpha*L^(1-alpha) | -inf <= Y <= inf - Vt^(1/nu) = (1-beta)*U^(1/nu) + beta*EVt^(1/nu) | -inf <= V <= inf - Vt = V^(1-tau) | -inf <= Vt <= inf transition: - K = Y(-1)+(1-delta)*K(-1)-C(-1) - Z = rhoZ*Z(-1)+exp((1-rhoSig)*SigmaBar+rhoSig*Sigma(-1)+eta*Omega)*Epsilon - Sigma = (1-rhoSig)*SigmaBar+rhoSig*Sigma(-1)+eta*Omega expectation: - EC = Vt(1)^((nu-1)/nu)*Uc(1)*(1-delta+alpha*Y(1)/K(1)) - EVt = Vt(1) calibration: parameters: tau : 0.5 delta : 0.0196 beta : 0.991 rhoZ : 0.95 alpha : 0.3 theta : 0.357 rhoSig : 0.9 SigmaBar : log(0.007) eta : 0.06 nu : (1-tau)/(1-1/Psi) Psi : 1/tau steady_state: Z : 0 K : 9 Sigma : SigmaBar C : 0.7 L : 0.3 U : (C^theta*(1-L)^(1-theta))^(1-tau) Uc : (theta*(1-tau)/nu)*U^(1/nu)/C Y : exp(Z)*K^alpha*L^(1-alpha) V : (1-beta)*U Vt : V^(1-tau)