10 Estimation
Objectives of this page
This page presents the Dynare codes for the two simplified models presented in Chapter 9:
- The RBC model in Section 10.1,
- The NK model with price rigidities in Section 10.2.
The models are solved in Dynare (version $$6, in a MATLAB environment).
Note
The codes to replicate the results of the paper are in the script/dsge folder of the weathershocks Github repository.
The model is estimated with quarterly New Zealand data (dataNZ_cubic_trend.m).
The structure of the replication folder is as follows:
RBC_q0.mod: Estimated model without weather shocks,RBC_q1.mod: Baseline estimated model with weather shocks,COMPARE.mod: Script comparing model fit across specifications,dataNZ_cubic_trend.m: Input dataset (New Zealand macroeconomic data).
You can run the notebook thenotebook.mlx in MATLAB to find the core results.
10.1 Simplified Two-Sector Weather RBC Mode
%----------------------------------------------------------------
% 0. Housekeeping (close all graphic windows)
%----------------------------------------------------------------
close all;
%----------------------------------------------------------------
% 1. Defining variables
%----------------------------------------------------------------
var y $y_t$ (long_name = 'output'),
c $c_t$ (long_name = 'consumption'),
uc $uc_t$ (long_name = 'marginal utility of consumption'),
uA $u^A_t$ (long_name = 'Marginal utility of agri labor'),
uN $u^N_t$ (long_name = 'Marginal utility in nonagri labor'),
hu $hu_t$ (long_name = 'Labor preference bundle'),
h $h_t$ (long_name = 'hours worked demand'),
m $m_t$ (long_name = 'Stochastic Discount Factor'),
y_N $y^N_t$ (long_name = 'output in non-agriculture'),
h_N $h^N_t$ (long_name = 'labor in non-agriculture'),
w_N $w^N_t$ (long_name = 'wage in non-agriculture'),
r $r_t$ (long_name = 'interest rate'),
p_N $p^N_t$ (long_name = 'relative price in non-agriculture'),
d $d_t$ (long_name = 'dividends'),
y_A $y^A_t$ (long_name = 'output in agriculture'),
h_A $h^A_t$ (long_name = 'labor in agriculture'),
w_A $w^A_t$ (long_name = 'wage in agriculture'),
p_A $p^A_t$ (long_name = 'relative price in agriculture'),
land $\ell_t$ (long_name = 'land use'),
x $x_t$ (long_name = 'Land investmen'),
gdp $GDP_t$ (long_name = 'aggregate output'),
n $n_t$ (long_name = 'Sectoral share'),
phi $\phi_t$ (long_name = 'Land cost function'),
varrho $\varrho_t$ (long_name = 'Land shadow value'),
e_z $e^z_t$ (long_name = 'TFP shock'),
e_h $e^h_t$ (long_name = 'labor shock'),
e_g $e^g_t$ (long_name = 'government spending shock'),
e_n $e^n_t$ (long_name = 'sectoral shock'),
e_s $e^s_t$ (long_name = 'supply/weather shock');
varexo eta_z $ \eta^z_t $ (long_name = 'innovation to TFP shock'),
eta_h $ \eta^h_t $ (long_name = 'innovation to labor shock'),
eta_g $ \eta^g_t $ (long_name = 'innovation to government spending shock'),
eta_n $ \eta^n_t $ (long_name = 'innovation to sectoral shock'),
eta_s $ \eta^s_t $ (long_name = 'innovation to supply or weather shock');
parameters
beta $ \beta $ (long_name = 'discount factor'),
delta_K $ \delta_K $ (long_name = 'capital depreciation rate'),
alpha $ \alpha $ (long_name = 'share of capital in output'),
sigmaC $ \sigma_C $ (long_name = 'inverse elasticity of intertemporal substitution'),
sigmaH $ \sigma_H $ (long_name = 'inverse Frisch elasticity of labor supply'),
chi $ \chi $ (long_name = 'labor disutility parameter'),
gy $ g_y $ (long_name = 'government spending to output ratio'),
b $ b $ (long_name = 'Habits degree'),
iota $ \iota $ (long_name = 'Labor supply substitution'),
varphi $ \varphi $ (long_name = 'share of agricultural goods in consumption'),
mu $ \mu $ (long_name = 'Goods substitution in CES'),
gamma $ \gamma $ (long_name = 'Share of nonricardian households'),
Hss $ \bar{H} $ (long_name = 'Steady state Hours'),
omega $ \omega $ (long_name = 'Land intensity in technology'),
tau $ \tau $ (long_name = 'Scale in land cost'),
kappa_A $ \kappa_A $ (long_name = 'Scale TFP in agriculture'),
Lss $ L^{ss} $ (long_name = 'steady-state land supply'),
delta_L $ \delta_L $ (long_name = 'land depreciation or adjustment cost'),
psi $ \psi $ (long_name = 'Land cost parameter'),
theta1 $ \theta_1 $ (long_name = 'Weather shock elasticity lag 0'),
sig_z $ \sigma_z $ (long_name = 'std. dev. of TFP shock'),
sig_h $ \sigma_h $ (long_name = 'std. dev. of labor shock'),
sig_g $ \sigma_g $ (long_name = 'std. dev. of government spending shock'),
sig_n $ \sigma_n $ (long_name = 'std. dev. of sectoral shock'),
sig_s $ \sigma_s $ (long_name = 'std. dev. of weather or supply shock'),
rho_z $ \rho_z $ (long_name = 'persistence of TFP shock'),
rho_h $ \rho_h $ (long_name = 'persistence of labor shock'),
rho_g $ \rho_g $ (long_name = 'persistence of government spending shock'),
rho_n $ \rho_n $ (long_name = 'persistence of sectoral shock')
rho_s $ \rho_s $ (long_name = 'persistence of weather shock')
;
%----------------------------------------------------------------
% 2. Calibration
%----------------------------------------------------------------
alpha = 0.33; % share of capital in ouput
beta = .9883; % discount factor
delta_K = 0.025; % depreciation of capital
sigmaC = 1.64; % risk aversion consumption
sigmaH = 3.87; % labor disutility
gy = 0.22; % share of public spendings in gdp
b = 0.4; % habits in consumption
iota = 2.89; % substitution cost across labor types
Lss = .4; % ss land per capita
Hss = 1/3; % ss Labor
psi = 1.5; % shape of the land cost function
varphi = 0.15; % share of agricultural goods in consumption
mu = 6.32; % substitution non-agriculture vs agriculture
omega = 0.10; % share of land in agriculture
delta_L = 0.06; % land decay rate
theta1 = 29.0; % damage current
% shock persistence
rho_z = 0.95;
rho_h = 0.95;
rho_g = 0.95;
rho_i = 0.95;
rho_n = 0.38;
rho_s = 0.38;
rho_e = 0.00;
% shock std
sig_z = 0.00;
sig_h = 0.00;
sig_g = 0.00;
sig_i = 0.00;
sig_n = 0.00;
sig_s = 0.81;
sig_c = 0.00;
sig_e = 0.00;
%----------------------------------------------------------------
% 3. Model
%----------------------------------------------------------------
model;
%% Household
[name='FOC home asset']
m(+1)*r=1;
[name='labor disutility index']
hu = (h_N^(1+iota)+h_A^(1+iota))^(1/(1+iota));
[name='FOC h_N']
w_N*uc = uN;
[name='FOC h_A']
w_A*uc = uA;
[name='stochastic discount factor']
m = beta*uc/uc(-1);
[name='Marginal utility of consumption']
uc = (c-b*c(-1))^-sigmaC;
[name='Marginal disutility of labor h_N']
uN = e_h*chi*hu^sigmaH*(h_N/hu)^iota;
[name='Marginal disutility of labor h_A']
uA = e_h*chi*hu^sigmaH*(h_A/hu)^iota;
% Firms
[name='Production y_N']
y_N = e_z*h_N^(1-alpha);
[name='Production y_A']
y_A = (d*land(-1))^omega * (e_z*kappa_A*h_A^(1-alpha))^(1-omega);
[name='labor cost minimization N']
w_N = (1-alpha)*p_N*y_N/h_N;
[name='labor cost minimization A']
w_A = (1-omega)*(1-alpha)*p_A*y_A/h_A;
[name='FOC land']
varrho = m(+1)*(omega*p_A(+1)*y_A(+1)/land + ((1-delta_L)*d(+1)*varrho(+1)+phi(+1)/land));
[name='FOC x']
p_N = tau*x^(psi-1)*varrho*d*land(-1);
[name='land cost']
phi = tau/(psi)*x^(psi)*d*land(-1);
[name='Land']
land = (1-delta_L)*d*land(-1) + phi;
[name='Damage function']
d = e_s^-theta1;
%%% AGGREGATION
[name='total prod']
y = (1-n)*p_N*y_N + n*p_A*y_A;
h = (1-n)*h_N + n*h_A;
[name='Reallocation shock']
n = steady_state(n)*e_n;
[name='Ressources Constraint']
(1-n)*y_N = (1-varphi)*p_N^-mu*c + n*x + gy*steady_state(y_N)*e_g ;
n*y_A = varphi*p_A^-mu*c;
[name='Gross Domestic Product']
gdp = y - n*p_N*x;
[name='relative price']
1 = (1-varphi) * p_N^(1-mu) + varphi * p_A^(1-mu);
[name='shocks']
log(e_z) = rho_z*log(e_z(-1))+sig_z*eta_z/100;
log(e_h) = rho_h*log(e_h(-1))+sig_h*eta_h/100;
log(e_g) = rho_g*log(e_g(-1))+sig_g*eta_g/100;
log(e_n) = rho_n*log(e_n(-1))+sig_n*eta_n/100;
log(e_s) = rho_s*log(e_s(-1))+sig_s*eta_s/100;
end;
%----------------------------------------------------------------
% 4. Computation
%----------------------------------------------------------------
steady_state_model;
e_z = 1; e_h = 1; e_g = 1; e_i = 1; e_n = 1; e_s = 1;
r = 1/beta;
m = beta;
h_N = Hss;
h_A = h_N;
hu = (h_N^(1+iota)+h_A^(1+iota))^(1/(1+iota));
p_N = 1; p_A = 1;
q_N = 1; q_A = 1;
y_N = h_N^(1-alpha);
w_N = (1-alpha)*y_N/h_N;
w_A = w_N;
y_A = h_A*w_A/((1-omega)*(1-alpha));
land = Lss;
phi = delta_L*land;
varrho = (omega*y_A/land + phi/land)/(1/m-(1-delta_L));
x = psi*phi*varrho;
tau = 1/(x^(psi-1)*varrho*land);
kappa_A = (y_A/(land^omega*(h_A^(1-alpha))^(1-omega)))^(1/(1-omega));
n = ((1-gy)*y_N)/((1-varphi)/varphi*y_A+y_N+x);
c = n*y_A/varphi;
c_star = c;
y = (1-n)*p_N*y_N + n*p_A*y_A;
h = (1-n)*h_N + n*h_A;
gdp = y - n*x;
m_star = beta;
d = 1;
c_N = c; c_R = c;
uc = ((c-b*c)^-sigmaC);
chi = w_N*uc/(hu^sigmaH*(h_N/hu)^iota);
uN = e_h*chi*hu^sigmaH*(h_N/hu)^iota;
uA = e_h*chi*hu^sigmaH*(h_A/hu)^iota;
end;
M_.Sigma_e = eye(M_.exo_nbr);
resid;
%steady;
check;
stoch_simul(order=1);
varnames = char('gdp','p_N','p_A','y_A','y_N','land'); % Grapher variables agrégées (4 premières à changer)
nx = 2; ny = 3;
ix = strmatch('eta_s',M_.exo_names,'exact');
figure;
for iy=1:size(varnames,1)
subplot(nx,ny,iy)
idx=strmatch(deblank(varnames(iy,:)),M_.endo_names,'exact');
yx = eval(['oo_.irfs.' deblank(varnames(iy,:)) '_' M_.exo_names{ix}]);
if oo_.dr.ys(idx) ~=0 || oo_.dr.ys(idx) ~=1
yx = 100*yx/oo_.dr.ys(idx);
else
ys = 100*yx;
end
plot(yx,'linewidth',1,'Color',[235, 64, 52]/255,'Linewidth',1.5)
title([M_.endo_names_long{idx} ' - ' M_.endo_names_tex{idx}])
grid on
end10.2 Two Sector New Keynesian Model with Weather Shocks and Land
%----------------------------------------------------------------
% 0. Housekeeping (close all graphic windows)
%----------------------------------------------------------------
close all;
%----------------------------------------------------------------
% 1. Defining variables
%----------------------------------------------------------------
var y $y_t$ (long_name = 'output'),
c $c_t$ (long_name = 'consumption'),
uc $uc_t$ (long_name = 'marginal utility of consumption'),
uA $u^A_t$ (long_name = 'Marginal utility of agri labor'),
uN $u^N_t$ (long_name = 'Marginal utility in nonagri labor'),
hu $hu_t$ (long_name = 'Labor preference bundle'),
h $h_t$ (long_name = 'hours worked demand'),
m $m_t$ (long_name = 'Stochastic Discount Factor'),
y_N $y^N_t$ (long_name = 'output in non-agriculture'),
h_N $h^N_t$ (long_name = 'labor in non-agriculture'),
w_N $w^N_t$ (long_name = 'wage in non-agriculture'),
r $r_t$ (long_name = 'interest rate'),
p_N $p^N_t$ (long_name = 'relative price in non-agriculture'),
d $d_t$ (long_name = 'dividends'),
y_A $y^A_t$ (long_name = 'output in agriculture'),
h_A $h^A_t$ (long_name = 'labor in agriculture'),
w_A $w^A_t$ (long_name = 'wage in agriculture'),
p_A $p^A_t$ (long_name = 'relative price in agriculture'),
land $\ell_t$ (long_name = 'land use'),
x $x_t$ (long_name = 'Land investmen'),
gdp $GDP_t$ (long_name = 'aggregate output'),
n $n_t$ (long_name = 'Sectoral share'),
phi $\phi_t$ (long_name = 'Land cost function'),
varrho $\varrho_t$ (long_name = 'Land shadow value'),
r $r_t$ (long_name = 'Nominal interest rate'),
pi $\pi_t$ (long_name = 'Aggregate inflation'),
pi_A $\pi^A_t$ (long_name = 'Inflation in agriculture'),
pi_N $\pi^N_t$ (long_name = 'Inflation in non agriculture'),
mc_N $mc^N_t$ (long_name = 'Real marginal cost in non agriculture'),
mc_A $mc^A_t$ (long_name = 'Real marginal cost in agriculture'),
e_z $e^z_t$ (long_name = 'TFP shock'),
e_h $e^h_t$ (long_name = 'labor shock'),
e_g $e^g_t$ (long_name = 'government spending shock'),
e_n $e^n_t$ (long_name = 'sectoral shock'),
e_s $e^s_t$ (long_name = 'supply/weather shock');
varexo eta_z $ \eta^z_t $ (long_name = 'innovation to TFP shock'),
eta_h $ \eta^h_t $ (long_name = 'innovation to labor shock'),
eta_g $ \eta^g_t $ (long_name = 'innovation to government spending shock'),
eta_n $ \eta^n_t $ (long_name = 'innovation to sectoral shock'),
eta_s $ \eta^s_t $ (long_name = 'innovation to supply or weather shock');
parameters
beta $ \beta $ (long_name = 'discount factor'),
delta_K $ \delta_K $ (long_name = 'capital depreciation rate'),
alpha $ \alpha $ (long_name = 'share of capital in output'),
sigmaC $ \sigma_C $ (long_name = 'inverse elasticity of intertemporal substitution'),
sigmaH $ \sigma_H $ (long_name = 'inverse Frisch elasticity of labor supply'),
chi $ \chi $ (long_name = 'labor disutility parameter'),
gy $ g_y $ (long_name = 'government spending to output ratio'),
b $ b $ (long_name = 'Habits degree'),
iota $ \iota $ (long_name = 'Labor supply substitution'),
varphi $ \varphi $ (long_name = 'share of agricultural goods in consumption'),
mu $ \mu $ (long_name = 'Goods substitution in CES'),
gamma $ \gamma $ (long_name = 'Share of nonricardian households'),
Hss $ \bar{H} $ (long_name = 'Steady state Hours'),
omega $ \omega $ (long_name = 'Land intensity in technology'),
tau $ \tau $ (long_name = 'Scale in land cost'),
kappa_A $ \kappa_A $ (long_name = 'Scale TFP in agriculture'),
Lss $ L^{ss} $ (long_name = 'steady-state land supply'),
delta_L $ \delta_L $ (long_name = 'land depreciation or adjustment cost'),
psi $ \psi $ (long_name = 'Land cost parameter'),
theta1 $ \theta_1 $ (long_name = 'Weather shock elasticity lag 0'),
sig_z $ \sigma_z $ (long_name = 'std. dev. of TFP shock'),
sig_h $ \sigma_h $ (long_name = 'std. dev. of labor shock'),
sig_g $ \sigma_g $ (long_name = 'std. dev. of government spending shock'),
sig_n $ \sigma_n $ (long_name = 'std. dev. of sectoral shock'),
sig_s $ \sigma_s $ (long_name = 'std. dev. of weather or supply shock'),
epsilon_A $\varepsilon_A$ (long_name = 'Elasticity of substitution in agriculture'),
epsilon_N $\varepsilon_N$ (long_name = 'Elasticity of substitution in non agriculture'),
rho $\rho$ (long_name = 'Interest rate smoothing parameter'),
phi_y $\phi_y$ (long_name = 'Output coefficient in Taylor rule'),
phi_pi $\phi_\pi$ (long_name = 'Inflation coefficient in Taylor rule'),
kappa_N $\kappa_N$ (long_name = 'Price adjustment cost parameter in non agriculture'),
kappa_A $\kappa_A$ (long_name = 'Price adjustment cost parameter in agriculture'),
rho_z $ \rho_z $ (long_name = 'persistence of TFP shock'),
rho_h $ \rho_h $ (long_name = 'persistence of labor shock'),
rho_g $ \rho_g $ (long_name = 'persistence of government spending shock'),
rho_n $ \rho_n $ (long_name = 'persistence of sectoral shock')
rho_s $ \rho_s $ (long_name = 'persistence of weather shock')
;
%----------------------------------------------------------------
% 2. Calibration
%----------------------------------------------------------------
alpha = 0.33; % share of capital in ouput
beta = .9883; % discount factor
delta_K = 0.025; % depreciation of capital
sigmaC = 1.64; % risk aversion consumption
sigmaH = 3.87; % labor disutility
gy = 0.22; % share of public spendings in gdp
b = 0.4; % habits in consumption
iota = 2.89; % substitution cost across labor types
Lss = .4; % ss land per capita
Hss = 1/3; % ss Labor
psi = 1.5; % shape of the land cost function
varphi = 0.15; % share of agricultural goods in consumption
mu = 6.32; % substitution non-agriculture vs agriculture
omega = 0.10; % share of land in agriculture
delta_L = 0.06; % land decay rate
theta1 = 29.0; % damage current
epsilon_A = 10;
epsilon_N = 10;
rho = 0.8;
phi_y = .2;
phi_pi = 1.5;
kappa_N = 100;
kappa_A = 100;
% shock persistence
rho_z = 0.95;
rho_h = 0.95;
rho_g = 0.95;
rho_i = 0.95;
rho_n = 0.38;
rho_s = 0.38;
rho_e = 0.00;
% shock std
sig_z = 0.00;
sig_h = 0.00;
sig_g = 0.00;
sig_i = 0.00;
sig_n = 0.00;
sig_s = 0.81;
sig_c = 0.00;
sig_e = 0.00;
%----------------------------------------------------------------
% 3. Model
%----------------------------------------------------------------
model;
%% Household
[name='FOC home asset']
m(+1)*r/pi(+1)=1;
[name='labor disutility index']
hu = (h_N^(1+iota)+h_A^(1+iota))^(1/(1+iota));
[name='FOC h_N']
w_N*uc = uN;
[name='FOC h_A']
w_A*uc = uA;
[name='stochastic discount factor']
m = beta*uc/uc(-1);
[name='Marginal utility of consumption']
uc = (c-b*c(-1))^-sigmaC;
[name='Marginal disutility of labor h_N']
uN = e_h*chi*hu^sigmaH*(h_N/hu)^iota;
[name='Marginal disutility of labor h_A']
uA = e_h*chi*hu^sigmaH*(h_A/hu)^iota;
% Firms
[name='Production y_N']
y_N = e_z*h_N^(1-alpha);
[name='Production y_A']
y_A = (d*land(-1))^omega * (e_z*kappa_A*h_A^(1-alpha))^(1-omega);
[name='labor cost minimization N']
w_N = mc_N*(1-alpha)*p_N*y_N/h_N;
[name='labor cost minimization A']
w_A = mc_A*(1-omega)*(1-alpha)*p_A*y_A/h_A;
[name='NKPC N']
(1-epsilon_N)*p_N*y_N + epsilon_N*mc_N*y_N - kappa_N*p_N*pi_N*(pi_N-1)*y_N + kappa_N*m(+1)*p_N(+1)*pi_N(+1)*(pi_N(+1)-1)*y_N(+1);
[name='NKPC A']
(1-epsilon_A)*p_A*y_A + epsilon_A*mc_A*y_A - kappa_A*p_N*pi_A*(pi_A-1)*y_A + kappa_A*m(+1)*p_N(+1)*pi_A(+1)*(pi_A(+1)-1)*y_A(+1);
[name='FOC land']
varrho = m(+1)*(mc_A*omega*p_A(+1)*y_A(+1)/land + ((1-delta_L)*d(+1)*varrho(+1)+phi(+1)/land));
[name='FOC x']
p_N = tau*x^(psi-1)*varrho*d*land(-1);
[name='land cost']
phi = tau/(psi)*x^(psi)*d*land(-1);
[name='Land']
land = (1-delta_L)*d*land(-1) + phi;
[name='Damage function']
d = e_s^-theta1;
%%% AGGREGATION
[name='total prod']
y = (1-n)*p_N*y_N + n*p_A*y_A;
h = (1-n)*h_N + n*h_A;
[name='Reallocation shock']
n = steady_state(n)*e_n;
[name='Ressources Constraint']
(1-n)*y_N = (1-varphi)*p_N^-mu*c + n*x + gy*steady_state(y_N)*e_g + kappa_N/2*(pi_N-1)^2*y_N + kappa_A/2*(pi_A-1)^2*y_A;
n*y_A = varphi*p_A^-mu*c;
[name='Gross Domestic Product']
gdp = y - n*p_N*x;
[name='relative price']
1 = (1-varphi) * p_N^(1-mu) + varphi * p_A^(1-mu);
p_N/p_N(-1) = pi_N/pi;
p_A/p_A(-1) = pi_A/pi;
[name='Monetary policy']
log(r/STEADY_STATE(r)) = rho*log(r(-1)/STEADY_STATE(r)) + (1-rho)*(phi_y*log(gdp/STEADY_STATE(gdp)) + phi_pi*log(pi));
[name='shocks']
log(e_z) = rho_z*log(e_z(-1))+sig_z*eta_z/100;
log(e_h) = rho_h*log(e_h(-1))+sig_h*eta_h/100;
log(e_g) = rho_g*log(e_g(-1))+sig_g*eta_g/100;
log(e_n) = rho_n*log(e_n(-1))+sig_n*eta_n/100;
log(e_s) = rho_s*log(e_s(-1))+sig_s*eta_s/100;
end;
%----------------------------------------------------------------
% 4. Computation
%----------------------------------------------------------------
steady_state_model;
pi = 1; pi_A = 1; pi_N = 1;
mc_N = (epsilon_N-1)/ epsilon_N;
mc_A = (epsilon_A-1)/ epsilon_A;
e_z = 1; e_h = 1; e_g = 1; e_i = 1; e_n = 1; e_s = 1;
r = 1/beta;
m = beta;
h_N = Hss;
h_A = h_N;
hu = (h_N^(1+iota)+h_A^(1+iota))^(1/(1+iota));
p_N = 1; p_A = 1;
q_N = 1; q_A = 1;
y_N = h_N^(1-alpha);
w_N = mc_N*(1-alpha)*y_N/h_N;
w_A = w_N;
y_A = h_A*w_A/(mc_A*(1-omega)*(1-alpha));
land = Lss;
phi = delta_L*land;
varrho = (mc_A*omega*y_A/land + phi/land)/(1/m-(1-delta_L));
x = psi*phi*varrho;
tau = 1/(x^(psi-1)*varrho*land);
kappa_A = (y_A/(land^omega*(h_A^(1-alpha))^(1-omega)))^(1/(1-omega));
n = ((1-gy)*y_N)/((1-varphi)/varphi*y_A+y_N+x);
c = n*y_A/varphi;
c_star = c;
y = (1-n)*p_N*y_N + n*p_A*y_A;
h = (1-n)*h_N + n*h_A;
gdp = y - n*x;
m_star = beta;
d = 1;
c_N = c; c_R = c;
uc = ((c-b*c)^-sigmaC);
chi = w_N*uc/(hu^sigmaH*(h_N/hu)^iota);
uN = e_h*chi*hu^sigmaH*(h_N/hu)^iota;
uA = e_h*chi*hu^sigmaH*(h_A/hu)^iota;
end;
M_.Sigma_e = eye(M_.exo_nbr);
resid;
%steady;
check;
stoch_simul(order=1);
varnames = char('gdp','p_N','p_A','y_A','y_N','land','pi','pi_A','r');
nx = 3; ny = 3;
ix = strmatch('eta_s',M_.exo_names,'exact');
figure;
for iy=1:size(varnames,1)
subplot(nx,ny,iy)
idx=strmatch(deblank(varnames(iy,:)),M_.endo_names,'exact');
yx = eval(['oo_.irfs.' deblank(varnames(iy,:)) '_' M_.exo_names{ix}]);
if oo_.dr.ys(idx) ~=0 || oo_.dr.ys(idx) ~=1
yx = 100*yx/oo_.dr.ys(idx);
else
ys = 100*yx;
end
plot(yx,'linewidth',1,'Color',[235, 64, 52]/255,'Linewidth',1.5)
title([M_.endo_names_long{idx} ' - ' M_.endo_names_tex{idx}])
grid on
end