stepan
/
dynare
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge branch 'discretion' of git.dynare.org:JohannesPfeifer/dynare

time-shift
Sébastien Villemot 2020-12-22 12:29:38 +01:00
parent 3d912401d5 0e9b8c33f9
commit 5deaca993b
No known key found for this signature in database
GPG Key ID: 2CECE9350ECEBE4A
9 changed files with 425 additions and 26 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
doc/manual/source/the-model-file.rst
View File

@ -8941,11 +8941,6 @@ Optimal policy under commitment (Ramsey)
optimal policy for the first time and committing not to
re-optimize in the future.
Because it entails computing at least a second order approximation, the
computation of the planner objective value is skipped with a message when
the model is too large (more than 180 state variables, including lagged
Lagrange multipliers).
.. command:: ramsey_policy [VARIABLE_NAME...];
ramsey_policy (OPTIONS...) [VARIABLE_NAME...];
@ -9030,8 +9025,9 @@ Optimal policy under discretion
under discretion. The algorithm implemented is essentially an LQ
solver, and is described by *Dennis (2007)*.
You should ensure that your model is linear and your objective is
quadratic. Also, you should set the ``linear`` option of the
You must ensure that your objective is quadratic. Regarding the model, it must
either be linear or solved at first order with an analytical steady state provided.
In the first case, you should set the ``linear`` option of the
``model`` block.
It is possible to use the :comm:`estimation` command after the

3
matlab/discretionary_policy/discretionary_policy.m
View File

@ -36,6 +36,8 @@ options_.discretionary_policy = 1;
options_.order = 1;
[info, oo_, options_, M_] = stoch_simul(M_, options_, oo_, var_list);
oo_.steady_state = oo_.dr.ys;
if ~options_.noprint
disp_steady_state(M_,oo_)
for i=M_.orig_endo_nbr:M_.endo_nbr
@ -44,7 +46,6 @@ if ~options_.noprint
end
end
end
oo_.planner_objective_value = evaluate_planner_objective(M_,options_,oo_);
options_.order = origorder;

24
matlab/discretionary_policy/discretionary_policy_1.m
View File

@ -41,11 +41,13 @@ beta = get_optimal_policy_discount_factor(M_.params, M_.param_names);
%call steady_state_file if present to update parameters
if options_.steadystate_flag
% explicit steady state file
[~,M_.params,info] = evaluate_steady_state_file(oo_.steady_state,[oo_.exo_steady_state; oo_.exo_det_steady_state],M_, ...
[ys,M_.params,info] = evaluate_steady_state_file(oo_.steady_state,[oo_.exo_steady_state; oo_.exo_det_steady_state],M_, ...
options_,false);
if info(1)
return;
end
else
ys=zeros(M_.endo_nbr,1);
end
[U,Uy,W] = feval([M_.fname,'.objective.static'],zeros(M_.endo_nbr,1),[], M_.params);
if any(any(isnan(Uy)))
@ -73,8 +75,10 @@ W=reshape(W,M_.endo_nbr,M_.endo_nbr);
klen = M_.maximum_lag + M_.maximum_lead + 1;
iyv=M_.lead_lag_incidence';
% Find the jacobian
z = repmat(zeros(M_.endo_nbr,1),1,klen);
z = z(nonzeros(iyv)) ;
z = repmat(ys,1,klen);
iyr0 = find(iyv(:)) ;
z = z(iyr0);
it_ = M_.maximum_lag + 1 ;
if M_.exo_nbr == 0
@ -82,10 +86,10 @@ if M_.exo_nbr == 0
end
[junk,jacobia_] = feval([M_.fname '.dynamic'],z, [zeros(size(oo_.exo_simul)) ...
oo_.exo_det_simul], M_.params, zeros(M_.endo_nbr,1), it_);
if any(junk~=0)
info = 65; %the model must be written in deviation form and not have constant terms
return;
oo_.exo_det_simul], M_.params, ys, it_);
if max(abs(junk))>options_.solve_tolf
info = 65; %the model must be written in deviation form and not have constant terms or have a steady state provided
return;
end
Indices={'lag','contemp','lead'};
@ -116,10 +120,12 @@ else
end
%write back solution to dr
dr.ys =zeros(M_.endo_nbr,1);
dr.ys =ys;
dr=set_state_space(dr,M_,options_);
T=H(dr.order_var,dr.order_var);
dr.ghu=G(dr.order_var,:);
Selection=M_.lead_lag_incidence(1,dr.order_var)>0;%select state variables
if M_.maximum_endo_lag
Selection=M_.lead_lag_incidence(1,dr.order_var)>0;%select state variables
end
dr.ghx=T(:,Selection);
oo_.dr = dr;

13
matlab/evaluate_planner_objective.m
View File

@ -37,11 +37,6 @@ dr = oo.dr;
exo_nbr = M.exo_nbr;
nstatic = M.nstatic;
nspred = M.nspred;
if nspred > 180
fprintf('\nevaluate_planner_objective: model too large, can''t evaluate planner objective\n')
planner_objective_value = NaN;
return
end
beta = get_optimal_policy_discount_factor(M.params, M.param_names);
Gy = dr.ghx(nstatic+(1:nspred),:);
@ -64,7 +59,13 @@ Uyygygu = A_times_B_kronecker_C(Uyy,gy,gu);
Wbar =U/(1-beta); %steady state welfare
Wy = Uy*gy/(eye(nspred)-beta*Gy);
Wu = Uy*gu+beta*Wy*Gu;
Wyy = Uyygygy/(eye(nspred*nspred)-beta*kron(Gy,Gy));
% Wyy = Uyygygy/(eye(nspred*nspred)-beta*kron(Gy,Gy)); %solve Wyy=Uyy*kron(gy,gy)+beta*Wyy*kron(Gy,Gy)
if isempty(options.qz_criterium)
options.qz_criterium = 1+1e-6;
end
%solve Lyapunuv equation Wyy=gy'*Uyy*gy+beta*Gy'Wyy*Gy
Wyy = reshape(lyapunov_symm(sqrt(beta)*Gy',reshape(Uyygygy,nspred,nspred),options.lyapunov_fixed_point_tol,options.qz_criterium,options.lyapunov_complex_threshold, 3, options.debug),1,nspred*nspred);
Wyygugu = A_times_B_kronecker_C(Wyy,Gu,Gu);
Wyygygu = A_times_B_kronecker_C(Wyy,Gy,Gu);
Wuu = Uyygugu+beta*Wyygugu;

2
matlab/get_error_message.m
View File

@ -122,7 +122,7 @@ switch info(1)
case 64
message = 'discretionary_policy: the derivatives of the objective function contain NaN.';
case 65
message = 'discretionary_policy: the model must be written in deviation form and not have constant terms.';
message = 'discretionary_policy: the model must be written in deviation form and not have constant terms or an analytical steady state meeds to be provided.';
case 66
message = 'discretionary_policy: the objective function must have zero first order derivatives.';
case 71

2
matlab/stoch_simul.m
View File

@ -79,7 +79,7 @@ oo_.dr=set_state_space(dr,M_,options_);
if PI_PCL_solver
[oo_.dr, info] = PCL_resol(oo_.steady_state,0);
elseif options_.discretionary_policy
if ~options_.linear
if ~options_.order==1
error('discretionary_policy: only linear-quadratic problems can be solved');
end
[~,info,M_,options_,oo_] = discretionary_policy_1(options_.instruments,M_,options_,oo_);

5
tests/Makefile.am
View File

@ -114,6 +114,8 @@ MODFILES = \
discretionary_policy/dennis_1.mod \
discretionary_policy/dennis_1_estim.mod \
discretionary_policy/Gali_discretion.mod \
discretionary_policy/Gali_2015_chapter_3.mod \
discretionary_policy/Gali_2015_chapter_3_nonlinear.mod \
histval_initval_file/ramst_initval_file.mod \
histval_initval_file/ramst_data.mod \
histval_initval_file/ramst_datafile.mod \
@ -646,7 +648,8 @@ lmmcp/sw_newton.o.trs: lmmcp/sw_lmmcp.o.trs
discretionary_policy/dennis_1_estim.m.trs: discretionary_policy/dennis_1.m.trs
discretionary_policy/dennis_1_estim.o.trs: discretionary_policy/dennis_1.o.trs
discretionary_policy/Gali_2015_chapter_3_nonlinear.m.trs: discretionary_policy/Gali_2015_chapter_3.m.trs
discretionary_policy/Gali_2015_chapter_3_nonlinear.o.trs: discretionary_policy/Gali_2015_chapter_3.o.trs
observation_trends_and_prefiltering/MCMC: m/observation_trends_and_prefiltering/MCMC o/observation_trends_and_prefiltering/MCMC
m/observation_trends_and_prefiltering/MCMC: $(patsubst %.mod, %.m.trs, $(filter observation_trends_and_prefiltering/MCMC/%.mod, $(MODFILES)))

163
tests/discretionary_policy/Gali_2015_chapter_3.mod Normal file
View File

@ -0,0 +1,163 @@
/*
* This file implements the baseline New Keynesian model of Jordi Galí (2015): Monetary Policy, Inflation,
* and the Business Cycle, Princeton University Press, Second Edition, Chapter 3
*
* THIS MOD-FILE REQUIRES DYNARE 4.5 OR HIGHER
*
* Notes:
* - all model variables are expressed in deviations from steady state, i.e. in contrast to
* to the chapter, both the nominal interest rate and natural output are not in log-levels, but rather mean 0
*
* This implementation was written by Johannes Pfeifer. In case you spot mistakes,
* email me at jpfeifer@gmx.de
*
* Please note that the following copyright notice only applies to this Dynare
* implementation of the model.
*/
/*
* Copyright (C) 2016-20 Johannes Pfeifer
* Copyright (C) 2020 Dynare Team
*
* This is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* It is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* For a copy of the GNU General Public License,
* see <http://www.gnu.org/licenses/>.
*/
var pi ${\pi}$ (long_name='inflation')
y_gap ${\tilde y}$ (long_name='output gap')
y_nat ${y^{nat}}$ (long_name='natural output') //(in contrast to the textbook defined in deviation from steady state)
y ${y}$ (long_name='output')
yhat ${\hat y}$ (long_name='output deviation from steady state')
r_nat ${r^{nat}}$ (long_name='natural interest rate')
r_real ${r^r}$ (long_name='real interest rate')
i ${i}$ (long_name='nominal interrst rate')
n ${n}$ (long_name='hours worked')
m_real ${m-p}$ (long_name='real money stock')
m_growth_ann ${\Delta m}$ (long_name='money growth annualized')
m_nominal ${m}$ (long_name='nominal money stock')
a ${a}$ (long_name='AR(1) technology shock process')
r_real_ann ${r^{r,ann}}$ (long_name='annualized real interest rate')
i_ann ${i^{ann}}$ (long_name='annualized nominal interest rate')
r_nat_ann ${r^{nat,ann}}$ (long_name='annualized natural interest rate')
pi_ann ${\pi^{ann}}$ (long_name='annualized inflation rate')
z ${z}$ (long_name='AR(1) preference shock process')
p ${p}$ (long_name='price level')
w ${w}$ (long_name='nominal wage')
c ${c}$ (long_name='consumption')
w_real ${\frac{w}{p}}$ (long_name='real wage')
mu ${\mu}$ (long_name='markup')
mu_hat ${\hat \mu}$ (long_name='markup gap')
;
varexo eps_a ${\varepsilon_a}$ (long_name='technology shock')
eps_z ${\varepsilon_z}$ (long_name='preference shock innovation')
;
parameters alppha ${\alpha}$ (long_name='capital share')
betta ${\beta}$ (long_name='discount factor')
rho_a ${\rho_a}$ (long_name='autocorrelation technology shock')
rho_z ${\rho_{z}}$ (long_name='autocorrelation monetary demand shock')
siggma ${\sigma}$ (long_name='inverse EIS')
varphi ${\varphi}$ (long_name='inverse Frisch elasticity')
phi_pi ${\phi_{\pi}}$ (long_name='inflation feedback Taylor Rule')
phi_y ${\phi_{y}}$ (long_name='output feedback Taylor Rule')
eta ${\eta}$ (long_name='semi-elasticity of money demand')
epsilon ${\epsilon}$ (long_name='demand elasticity')
theta ${\theta}$ (long_name='Calvo parameter')
;
%----------------------------------------------------------------
% Parametrization, p. 67 and p. 113-115
%----------------------------------------------------------------
siggma = 1;
varphi=5;
phi_pi = 1.5;
phi_y = 0.125;
theta=3/4;
rho_z = 0.5;
rho_a = 0.9;
betta = 0.99;
eta =3.77; %footnote 11, p. 115
alppha=1/4;
epsilon=9;
%----------------------------------------------------------------
% First Order Conditions
%----------------------------------------------------------------
model(linear);
//Composite parameters
#Omega=(1-alppha)/(1-alppha+alppha*epsilon); %defined on page 60
#psi_n_ya=(1+varphi)/(siggma*(1-alppha)+varphi+alppha); %defined on page 62
#lambda=(1-theta)*(1-betta*theta)/theta*Omega; %defined on page 61
#kappa=lambda*(siggma+(varphi+alppha)/(1-alppha)); %defined on page 63
[name='New Keynesian Phillips Curve eq. (22)']
pi=betta*pi(+1)+kappa*y_gap;
[name='Dynamic IS Curve eq. (23)']
y_gap=-1/siggma*(i-pi(+1)-r_nat)+y_gap(+1);
[name='Definition natural rate of interest eq. (24)']
r_nat=-siggma*psi_n_ya*(1-rho_a)*a+(1-rho_z)*z;
[name='Definition real interest rate']
r_real=i-pi(+1);
[name='Definition natural output, eq. (20)']
y_nat=psi_n_ya*a;
[name='Definition output gap']
y_gap=y-y_nat;
[name='TFP shock']
a=rho_a*a(-1)+eps_a;
[name='Production function (eq. 14)']
y=a+(1-alppha)*n;
[name='Preference shock, p. 54']
z = rho_z*z(-1) - eps_z;
[name='Money growth (derived from eq. (4))']
m_growth_ann=4*(y-y(-1)-eta*(i-i(-1))+pi);
[name='Real money demand (eq. 4)']
m_real=y-eta*i;
[name='Annualized nominal interest rate']
i_ann=4*i;
[name='Annualized real interest rate']
r_real_ann=4*r_real;
[name='Annualized natural interest rate']
r_nat_ann=4*r_nat;
[name='Annualized inflation']
pi_ann=4*pi;
[name='Output deviation from steady state']
yhat=y-steady_state(y);
[name='Definition price level']
pi=p-p(-1);
[name='resource constraint, eq. (12)']
y=c;
[name='FOC labor, eq. (2)']
w-p=siggma*c+varphi*n;
[name='definition real wage']
w_real=w-p;
[name='definition nominal money stock']
m_nominal=m_real+p;
[name='average price markup, eq. (18)']
mu=-(siggma+(varphi+alppha)/(1-alppha))*y+(1+varphi)/(1-alppha)*a;
[name='average price markup, eq. (20)']
mu_hat=-(siggma+(varphi+alppha)/(1-alppha))*y_gap;
end;
%----------------------------------------------------------------
% define shock variances
%---------------------------------------------------------------
shocks;
var eps_a = 0.5^2; //unit shock to preferences
end;
planner_objective 0.5*((siggma+(varphi+alppha)/(1-alppha))*yhat^2+epsilon/0.0215*pi^2)/100;
discretionary_policy(instruments=(i),irf=20,planner_discount=betta, periods=0) y_gap pi_ann y n w_real p yhat;

229
tests/discretionary_policy/Gali_2015_chapter_3_nonlinear.mod Normal file
View File

@ -0,0 +1,229 @@
/*
* This file implements the baseline New Keynesian model of Jordi Galí (2015): Monetary Policy, Inflation,
* and the Business Cycle, Princeton University Press, Second Edition, Chapter 3
*
* Note that this mod-file implements the non-linear first order conditions and that the IRFs show the log-deviations
* from steady state.
*
* THIS MOD-FILE REQUIRES DYNARE 4.5 OR HIGHER
*
* Notes:
* - in the LOM for the discount rate shock z the shock enters with a minus sign in this mod-file to generate the
* IRF to a -0.5% shock
*
* This implementation was written by Johannes Pfeifer. In case you spot mistakes,
* email me at jpfeifer@gmx.de
*
* Please note that the following copyright notice only applies to this Dynare
* implementation of the model.
*/
/*
* Copyright (C) 2016-20 Johannes Pfeifer
* Copyright (C) 2020 Dynare Team
*
* This is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* It is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* For a copy of the GNU General Public License,
* see <http://www.gnu.org/licenses/>.
*/
var C ${C}$ (long_name='Consumption')
W_real ${\frac{W}{P}}$ (long_name='Real Wage')
Pi ${\Pi}$ (long_name='inflation')
A ${A}$ (long_name='AR(1) technology process')
N ${N}$ (long_name='Hours worked')
R ${R^n}$ (long_name='Nominal Interest Rate')
realinterest ${R^{r}}$ (long_name='Real Interest Rate')
Y ${Y}$ (long_name='Output')
Q ${Q}$ (long_name='Bond price')
Z ${Z}$ (long_name='AR(1) preference shock process')
S ${S}$ (long_name='Price dispersion')
Pi_star ${\Pi^*}$ (long_name='Optimal reset price')
x_aux_1 ${x_1}$ (long_name='aux. var. 1 recursive price setting')
x_aux_2 ${x_2}$ (long_name='aux. var. 2 recursive price setting')
MC ${mc}$ (long_name='real marginal costs')
M_real ${M/P}$ (long_name='real money stock')
i_ann ${i^{ann}}$ (long_name='annualized nominal interest rate')
pi_ann ${\pi^{ann}}$ (long_name='annualized inflation rate')
r_real_ann ${r^{r,ann}}$ (long_name='annualized real interest rate')
P ${P}$ (long_name='price level')
log_m_nominal ${log(M)}$ (long_name='log nominal money stock')
log_y ${log(Y)}$ (long_name='log output')
log_W_real ${log(W/P)}$ (long_name='log real wage')
log_N ${log(N)}$ (long_name='log hours')
log_P ${log(P)}$ (long_name='log price level')
log_A ${log(A)}$ (long_name='log technology level')
log_Z ${log(Z)}$ (long_name='log preference shock')
y_hat
pi
;
varexo eps_a ${\varepsilon_a}$ (long_name='technology shock')
eps_z ${\varepsilon_z}$ (long_name='preference shock')
;
parameters alppha ${\alpha}$ (long_name='capital share')
betta ${\beta}$ (long_name='discount factor')
rho_a ${\rho_a}$ (long_name='autocorrelation technology shock')
rho_z ${\rho_{z}}$ (long_name='autocorrelation monetary demand shock')
siggma ${\sigma}$ (long_name='inverse EIS')
varphi ${\varphi}$ (long_name='inverse Frisch elasticity')
phi_pi ${\phi_{\pi}}$ (long_name='inflation feedback Taylor Rule')
phi_y ${\phi_{y}}$ (long_name='output feedback Taylor Rule')
eta ${\eta}$ (long_name='semi-elasticity of money demand')
epsilon ${\epsilon}$ (long_name='demand elasticity')
theta ${\theta}$ (long_name='Calvo parameter')
tau ${\tau}$ (long_name='labor subsidy')
;
%----------------------------------------------------------------
% Parametrization, p. 67 and p. 113-115
%----------------------------------------------------------------
siggma = 1;
varphi=5;
phi_pi = 1.5;
phi_y = 0.125;
theta=3/4;
rho_z = 0.5;
rho_a = 0.9;
betta = 0.99;
eta =3.77; %footnote 11, p. 115
alppha=1/4;
epsilon=9;
tau=0; //1/epsilon;
%----------------------------------------------------------------
% First Order Conditions
%----------------------------------------------------------------
model;
[name='FOC Wages, eq. (2)']
W_real=C^siggma*N^varphi;
[name='Euler equation eq. (3)']
Q=betta*(C(+1)/C)^(-siggma)*(Z(+1)/Z)/Pi(+1);
[name='Definition nominal interest rate), p. 22 top']
R=1/Q;
[name='Aggregate output, above eq. (14)']
Y=A*(N/S)^(1-alppha);
[name='Definition Real interest rate']
R=realinterest*Pi(+1);
% @#if money_growth_rule==0
% [name='Monetary Policy Rule, p. 26 bottom/eq. (22)']
% R=1/betta*Pi^phi_pi*(Y/steady_state(Y))^phi_y;
% @#endif
[name='Market Clearing, eq. (15)']
C=Y;
[name='Technology Shock, eq. (6)']
log(A)=rho_a*log(A(-1))+eps_a;
[name='Preference Shock, p.54']
log(Z)=rho_z*log(Z(-1))-eps_z;
[name='Definition marginal cost']
MC=W_real/((1-alppha)*Y/N*S);
[name='LOM prices, eq. (7)']
1=theta*Pi^(epsilon-1)+(1-theta)*(Pi_star)^(1-epsilon);
[name='LOM price dispersion']
S=(1-theta)*Pi_star^(-epsilon/(1-alppha))+theta*Pi^(epsilon/(1-alppha))*S(-1);
[name='FOC price setting']
Pi_star^(1+epsilon*(alppha/(1-alppha)))=x_aux_1/x_aux_2*(1-tau)*epsilon/(epsilon-1);
[name='Auxiliary price setting recursion 1']
x_aux_1=Z*C^(-siggma)*Y*MC+betta*theta*Pi(+1)^(epsilon+alppha*epsilon/(1-alppha))*x_aux_1(+1);
[name='Auxiliary price setting recursion 2']
x_aux_2=Z*C^(-siggma)*Y+betta*theta*Pi(+1)^(epsilon-1)*x_aux_2(+1);
[name='Definition log output']
log_y = log(Y);
[name='Definition log real wage']
log_W_real=log(W_real);
[name='Definition log hours']
log_N=log(N);
[name='Annualized inflation']
pi_ann=4*log(Pi);
[name='Annualized nominal interest rate']
i_ann=4*log(R);
[name='Annualized real interest rate']
r_real_ann=4*log(realinterest);
[name='Real money demand, eq. (4)']
M_real=Y/R^eta;
[name='definition nominal money stock']
log_m_nominal=log(M_real*P);
[name='Definition price level']
Pi=P/P(-1);
[name='Definition log price level']
log_P=log(P);
[name='Definition log TFP']
log_A=log(A);
[name='Definition log preference']
log_Z=log(Z);
[mcp='a']
y_hat=log(Y)-STEADY_STATE(log(Y));
pi=log(Pi)-STEADY_STATE(log(Pi));
end;
%----------------------------------------------------------------
% Steady state values
%---------------------------------------------------------------
steady_state_model;
A=1;
Z=1;
S=1;
Pi_star=1;
P=1;
MC=(epsilon-1)/epsilon/(1-tau);
R=1/betta;
Pi=1;
Q=1/R;
realinterest=R;
N=((1-alppha)*MC)^(1/((1-siggma)*alppha+varphi+siggma));
C=A*N^(1-alppha);
W_real=C^siggma*N^varphi;
Y=C;
money_growth=0;
money_growth_ann=0;
nu=0;
x_aux_1=C^(-siggma)*Y*MC/(1-betta*theta*Pi^(epsilon/(1-alppha)));
x_aux_2=C^(-siggma)*Y/(1-betta*theta*Pi^(epsilon-1));
log_y = log(Y);
log_W_real=log(W_real);
log_N=log(N);
pi_ann=4*log(Pi);
i_ann=4*log(R);
r_real_ann=4*log(realinterest);
M_real=Y/R^eta;
log_m_nominal=log(M_real*P);
log_P=log(P);
log_A=0;
log_Z=0;
end;
%----------------------------------------------------------------
% define shock variances
%---------------------------------------------------------------
shocks;
var eps_a = 0.5^2; //unit shock to preferences
end;
% steady;
% check;
% stoch_simul;
planner_objective 0.5*((siggma+(varphi+alppha)/(1-alppha))*y_hat^2+epsilon/0.0215*pi^2)/100;
discretionary_policy(order=1,instruments=(R),irf=20,planner_discount=betta, periods=0) y_hat pi_ann log_y log_N log_W_real log_P;
temp=load('Gali_2015_chapter_3_results.mat');
if abs(oo_.planner_objective_value-temp.oo_.planner_objective_value)>1e-6
warning('Planner objective does not match linear model')
end
if max(max(abs([temp.oo_.irfs.y_eps_a; temp.oo_.irfs.w_real_eps_a; temp.oo_.irfs.n_eps_a; temp.oo_.irfs.pi_ann_eps_a]-...
[oo_.irfs.log_y_eps_a; oo_.irfs.log_W_real_eps_a; oo_.irfs.log_N_eps_a; oo_.irfs.pi_ann_eps_a])))>1e-6
error('Policy is different')
end