I was not able to upload the mod file of the code. Here goes its content:
% The model replicates Ascari Ropele JMCB (2010), but using varobs and shocks from Smets and Wouters (2007).
% The model also uses Schmitt-Grohe and Uribe (2005) NBER WP 11417.
% Ascari and Ropele (2010) is a medium scale non log-linearized new Keynesian model. The model was used
% in simulations in the respective paper and in Ascari and Ropele (2012), using Christiano, Eichembaun and Evans (2005) calibration.
% As long as we know, neither Ascari and Ropele or any othe author have made a Bayseian estimation of those parameters, and
% this is the purpose of the current code.
% The code uses 27 AR ENDOGENOUS VARIABLES + 7 variables of the autocorrelated processes for Bayesian estimation + 3 variables for simulations
var
u % capacity utilization
c % consumption
h % hours worked
invest % capital investment
k % capital stock
lamb % Lagrange multiplier household budget constraint
pi % gross quarterly inflation
w % real wage
mutil % (inverse of) Lagrange multiplier labor supply AR (14)
q % market value capital
rk % rental price capital
div % dividends
f1 % term for recursive expression for wage
f2 % term for recursive expression for wage
wtil % real wage optimizing firm
hd % worker hours demanded
y % output
mc % real marginal cost
x1 % term for recursive expression for price
x2 % term for recursive expression for price
ptil % relative price optimizing firm
s % cross section price dispersion
stil % cross section wage dispersion
tau % lump sum tax
R % nominal gross quarterly interest rate
g % government spending
z % Productivity
yd % % deviation of y from new steady state
pi_y % annual inflation (%)
pi_q % quarterly inflation (%)
zs % productivity shock process
bs % risk premium shock process
gs % spending shock process
qs % investment shock process
ms % Monetary policy shock process
spinf % price markup shock process
sw % wage markup shock process
;
% EXOGENOUS VARIABLES
varexo
ez ${\eta^a}$ (long_name='productivity shock')
eb ${\eta^b}$ (long_name='risk premium shock')
eg ${\eta^g}$ (long_name='Spending shock')
eqs ${\eta^i}$ (long_name='Investment-specific technology shock')
em ${\eta^m}$ (long_name='Monetary policy shock')
epinf ${\eta^{p}}$ (long_name='Price markup shock')
ew ${\eta^{w}}$ (long_name='Wage markup shock')
;
% PARAMETERS
parameters
beta % discount rate
b % habit parameter
phi0 % preference parameter labor
eta % elasticity substitution differianted good
etatil % elasticity substitution labor types
delt % capital depreciation rate
kap % investment adj cost function
gam1 % cap utilization function
gam2 % cap utilization function
alphtil % Calvo prob not reset wages
chitil % wage indexation degree
theta % capital share production function
ksi % firm fixed cost
alph % Calvo prob not reset prices
chi % price indexation degree
g_ss % steady state government spending
pi_tar % ss inflation inflation target in SW
R_tar % ss interest rate target
% phi % monetary policy parameter
crpi % Taylor rule inflation feedback
cry % Taylor rule output feedback
crdy % Taylor rule output growth feedback
crr % interest rate persistence
crhoz ${\rho_a}$ (long_name='persistence productivity shock')
cmaz % MA parameter in the productivity process
crhob ${\rho_b}$ (long_name='persistence risk premium shock')
crhog ${\rho_g}$ (long_name='persistence spending shock')
cgy % parameter relating output with spending process
crhoqs ${\rho_i}$ (long_name='persistence risk premium shock')
crhoms ${\rho_r}$ (long_name='persistence monetary policy shock')
crhopinf ${\rho_p}$ (long_name='persistence price markup shock')
cmap % MA parameter in the price markup process
crhow ${\rho_w}$ (long_name='persistence wage markup shock')
cmaw % MA parameter in the wage markup process
;
% PARAMETER CALIBRATION
// fixed parameters % %
% 1) PREFERENCES
b = 0.63; % degree of habit persistence
beta = 1.03^(-1/4); % subjective discount factor
phi0 = 1.1196 ; % preference parameter labor
% 2) ELASTICITIES OF SUBSTITUTION
eta = 6; % price-elasticity of demand for a differianted good
etatil = 21; % elasticity substitution labor types
% 3) TECHNOLOGY
delt = 0.025; % depreciation rate
theta = 0.36; % share of capital
kap = 2.48; % investment adj cost function
gam1 = 0.032417; % cap utilization function
gam2 = 0.000324; % cap utilization function
ksi = 0.5827; % firm fixed cost
% MODEL
model;
% capital accumulation AR Eq (15)
k = (1-delt)*k(-1) + invest - invest*(kap/2)*(((invest/invest(-1))-1)^2);
% HOUSEHOLD FIRST ORDER CONDITIONS
% household consumption Euler AR Eq (16)
(1/(c-b*c(-1))) - b*beta*(1/(c(+1)-b*c)) + gs = lamb;
% household labor decision AR Eq (17)
phi0*h = lamb*w/mutil;
% household capital decision AR Eq (18)
lamb*q = beta*lamb(+1)*((1-delt)*q(+1) + rk(+1)*u(+1) - gam1*(u(+1)-1) - (gam2/2)*((u(+1)-1)^2)) + bs;
% household investment decision AR Eq (19)
lamb = qs + lamb*q*(1 - (kap/2)*(((invest/invest(-1))-1)^2) - kap*(invest/invest(-1))*((invest/invest(-1))-1)) + beta*lamb(+1)*q(+1)*kap*((invest(+1)/invest)^2)*((invest(+1)/invest)-1);
% household capital utilization decision AR Eq (20)
gam1 + gam2*(u-1) = rk;
% household borrowing/lending Euler SGU Eq (20)
lamb = beta*R*(lamb(+1)/pi(+1));
% WAGE SETTING SGU Eqs (17)-(19)
f1 = ((etatil-1)/etatil)*wtil*lamb*((w/wtil)^etatil)*hd + alphtil*beta*((pi(+1)/(pi^chitil))^(etatil-1))*((wtil(+1)/wtil)^(etatil-1))*f1(+1);
f2 = phi0*h*((w/wtil)^etatil)*hd + alphtil*beta*((pi(+1)/(pi^chitil))^(etatil))*((wtil(+1)/wtil)^(etatil))*f2(+1);
f1 = f2;
% aggregate demand AR Eq (24)
y = c + invest + g + (gam1*(u-1) + (gam2/2)*((u-1)^2))*k(-1);
% FIRMS' DECISIONS
% firms' demand for capital services AR Eq (26)
mc*z*theta*((u*k(-1))^(theta-1))*(hd^(1-theta)) = rk;
% firms' demand for labor AR Eq (27)
mc*z*(1-theta)*((u*k(-1))^theta)*(hd^(-theta)) = w;
% PRICE SETTING SGU Eqs (29)-(31)
x1 = y*mc*(ptil^(-1-eta)) + alph*beta*(lamb(+1)/lamb)*((ptil(+1)/ptil)^(1+eta))*((pi(+1)/(pi^chi))^eta)*x1(+1);
x2 = y*(ptil^(-eta)) + alph*beta*(lamb(+1)/lamb)*((ptil(+1)/ptil)^eta)*((pi(+1)/(pi^chi))^(eta-1))*x2(+1);
eta*x1 = (eta-1)*x2;
% government constraint AR Eq (29)
g = tau;
% aggregate price SGU Eq (38)
1 = alph*(pi^(eta-1))*((pi(-1)^chi)^(1-eta)) + (1-alph)*(ptil^(1-eta)) + spinf;
% aggregate wage SGU Eq (47)
(w^(1-etatil)) = (1-alphtil)*(wtil^(1-etatil)) + alphtil*(w(-1)^(1-etatil))*(((pi(-1)^chitil)/pi)^(1-etatil)) +sw;
% dividends SGU Eq (48)
div = y - rk*u*k(-1) - w*hd;
% EQUILIBRIUM
% labor market SGU Rq (45)
h = stil*hd;
% Resource constraint SGU Eq (40)
z*((u*k(-1))^theta)*(hd^(1-theta)) - ksi = y*s;
% PRICE AND WAGE DISPERSION
% Price dispersion dynamics SGU Eq (41)
s = (1-alph)*(ptil^(-eta)) + alph*((pi/(pi(-1)^chi))^eta)*s(-1);
% Wage dispersion dynamics SGU Eq (46)
stil = (1-alphtil)*((w/wtil)^etatil) + alphtil*((w/w(-1))^etatil)*((pi/(pi(-1)^chitil))^etatil)*stil(-1);
% MONETARY POLICY
%(R/R_tar) = (pi/pi_tar)^phi;
% MONETARY POLICY
R/R_tar = ((1-crr)*((pi/pi_tar)^(crpi)))
+(1-crr)*(y-2.9135)*cry
+(1-crr)*(y-y(-1))*crdy
+crr*R(-1)/R_tar + ms;
% government spending
g = g_ss;
% Productivity
z = 1+zs;
[name='Law of motion for productivity']
zs = crhoz*zs(-1) + ez +cmaz*ez(-1);
[name='Law of motion for risk premium']
bs = crhob*bs(-1) + eb;
[name='Law of motion for spending process']
gs = crhog*(gs(-1)) + eg + cgy*ez;
[name='Law of motion for investment specific technology shock process']
qs = crhoqs*qs(-1) + eqs;
[name='Law of motion for monetary policy shock process']
ms = crhoms*ms(-1) + em;
[name='Law of motion for price markup shock process']
spinf = crhopinf*spinf(-1) + epinf - cmap*epinf(-1);
[name='Law of motion for wage markup shock process']
sw = crhow*sw(-1) + ew - cmaw*ew(-1) ;
% variables generated for the simulations
yd = 100*(y-2.9135)/2.9135; % steady state output is 2.9135
pi_y = 100*((pi^4)-1);
pi_q = 100*(pi-1);
end;
steady_state_model;
% EXACT STEADY STATE VALUES
u = 1; % capacity utilization
pi_tar = 1.007; % ss inflation inflation target in SW
pi = pi_tar; % gross inflation
q = 1; % market value capital
rk = gam1; % rental price capital
div = 0; % dividends
R_tar = pi_tar/beta; % nominal interest rate target in AR
R = R_tar; % nominal gross interest rate
z = 1;
% 3) CALVO PARAMETERS
alphtil = 0.64; % on wages
alph = 0.60; % on prices
% 4) INDEXATION
chitil = 1; % on wages
chi = 1; % on prices
% 5) MONETARY POLICY
crpi = 1.5; % monetary policy parameter pi
crr = 0.85; % monetary policy parameter r
cry = 0.05; % monetary policy parameter y
crdy = 0.2; % monetary policy parameter dy
% 6) STEADY STATE
g_ss = 0.498777018; % ss government spending (residual)
% persistence shocks
crhoz= 0.9977;
cmaz= 0;
crhob= 0.5799;
crhog= 0.9957;
cgy= 0.51;
crhoqs= 0.7165;
crhoms=0;
crhopinf=0;
cmap = 0;
crhow=0;
cmaw = 0;
ptil = ((1/(1-alph))*(1-alph*pi^(-(eta-1)*(1-chi))))^(1/(1-eta)); % relative price optimizing firm
s = ((1-alph)*ptil)/(1-alph*pi^(eta*(1-chi))); % cross section price dispersion
mc = ((eta-1)/eta)*ptil*((1-alph*beta*pi^(eta*(1-chi)))/(1-alph*beta*pi^(-(1-eta)*(1-chi)))); % marginal cost
w = (1-theta)*(mc^(1/(1-theta)))*((theta/rk)^(theta/(1-theta))); % real wage
wtil = w*(((1/(1-alphtil))*(1 - alphtil*(pi^(-(1-chitil)*(1-etatil)))))^(1/(1-etatil))); % real wage optimizing firm
stil = ((1-alphtil)*((w/wtil)^etatil))/(1-alphtil*pi^(etatil*(1-chitil))); % cross section wage dispersion
y = (mc*ksi)/(1-mc*s); % output
x1 = (y*mc*ptil^(-(1+eta)))/(1 - alph*beta*(pi^(eta*(1-chi))));
x2 = x1*(eta/(eta-1));
k = (theta*mc*(y*s + ksi))/(u*rk); % capital stock
hd = ((1-theta)*mc*(y*s + ksi))/(w); % worker hours demanded
h = stil*hd; % hours worked
invest = delt*k; % capital investment
f2 = (phi0*stil*(hd^2)*((w/wtil)^etatil))/(1-alphtil*beta*(pi^((1-chitil)*etatil))); % term for recursive expression for wage
f1 = f2; % term for recursive expression for wage
lamb = (f1*(1-alphtil*beta*(pi^((1-chitil)*(etatil-1)))))/(((etatil-1)/etatil)*wtil*hd*((w/wtil)^etatil)); % Lagrange multiplier household budget constraint
mutil = (lamb*w)/(phi0*h); % (inverse of) Lagrange multiplier labor supply AR (14)
c = (1-b*beta)/(lamb*(1-b)); % consumption
g = g_ss;
tau = g; % lump sum tax
yd = 100*(y-2.9135)/2.9135;
pi_y = 100*((pi^4)-1);
pi_q = 100*(pi-1);
zs = 0;
bs = 0;
gs = 0;
qs = 0;
ms = 0;
spinf = 0;
sw = 0;
end;
//check the starting values for the steady state
resid;
// compute steady state given the starting values
steady;
// check Blanchard-Kahn-conditions
check;
varobs c invest y h pi w R;
estimated_params;
// PARAM NAME, INITVAL, LB, UB, PRIOR_SHAPE, PRIOR_P1, PRIOR_P2, PRIOR_P3, PRIOR_P4, JSCALE
// PRIOR_SHAPE: BETA_PDF, GAMMA_PDF, NORMAL_PDF, INV_GAMMA_PDF
stderr ez,0.4618,0.01,3,INV_GAMMA_PDF,0.1,2;
stderr eb,0.1818513,0.025,5,INV_GAMMA_PDF,0.1,2;
stderr eg,0.6090,0.01,3,INV_GAMMA_PDF,0.1,2;
stderr eqs,0.46017,0.01,3,INV_GAMMA_PDF,0.1,2;
stderr em,0.2397,0.01,3,INV_GAMMA_PDF,0.1,2;
stderr epinf,0.1455,0.01,3,INV_GAMMA_PDF,0.1,2;
stderr ew,0.2089,0.01,3,INV_GAMMA_PDF,0.1,2;
crhoz,.9676 ,.01,.9999,BETA_PDF,0.5,0.20;
crhob,.2703,.01,.9999,BETA_PDF,0.5,0.20;
crhog,.9930,.01,.9999,BETA_PDF,0.5,0.20;
cgy,0.05,0.01,2.0,NORMAL_PDF,0.5,0.25;
crhoqs,0.5724,.01,.9999,BETA_PDF,0.5,0.20;
crhoms,.3,0.01,.9999,BETA_PDF,0.5,0.20;
crhopinf,0.8692,0.01,0.9999,BETA_PDF,0.5,0.20;
crhow,0.9546,0.001,0.9999,BETA_PDF,0.5,0.20;
cmaz, 0.5, 0, 0.9999, BETA_PDF, 0.5,0.2;
cmap,0.7652,0.01,0.9999,BETA_PDF,0.5,0.2;
g_ss, 0.498777018, 0, 1, NORMAL_PDF, 0.5, 0.15;
alphtil,0.64,0.3,0.95,BETA_PDF,0.64,0.1;
alph,0.6,0.3,0.95,BETA_PDF,0.6,0.10;
chitil,0.9,0.15,1.00,BETA_PDF,0.9,0.01;
chi,0.9,0.15,1.00,BETA_PDF,0.9,0.01;
crpi,1.7985,1.0,3,NORMAL_PDF,1.5,0.25;
crr,0.8258,0.5,0.975,BETA_PDF,0.75,0.10;
cry,0.05,0.001,0.5,NORMAL_PDF,0.05,0.05;
crdy,0.2239,0.001,0.5,NORMAL_PDF,0.2,0.05;
pi_tar,1.007,1.001,1.01,GAMMA_PDF,1.00625,0.002;
end;
estimated_params_init(use_calibration);
end;
estimation (optim=('MaxIter',200),datafile=AR_data_lineardetrendc,mode_compute=6,first_obs=1,mh_nblocks=2,mh_jscale=0.20,mh_drop=0.2, nograph, nodiagnostic, tex) w sw pi_y h y zs;
write_latex_prior_table;
