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Merge pull request #818 from JohannesPfeifer/smoother_only 

Various fixes when running only smoother on a model
time-shift
Stéphane Adjemian 2014-12-17 11:29:05 +01:00
parent c3855a949d ed8b47bbf4
commit 077654fda2
5 changed files with 144 additions and 7 deletions
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14
matlab/DsgeSmoother.m
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@ -17,18 +17,20 @@ function [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK,T,R,P,PK,de
% o trend_coeff [double] (n*1) vector, parameters specifying the slope of the trend associated to each observed variable.
% o aK [double] (K,n,T+K) array, k (k=1,...,K) steps ahead filtered (endogenous) variables.
% o T and R [double] Matrices defining the state equation (T is the (m*m) transition matrix).
% P: 3D array of one-step ahead forecast error variance
% matrices
% PK: 4D array of k-step ahead forecast error variance
% matrices (meaningless for periods 1:d)
%
% o P: 3D array of one-step ahead forecast error variance
% matrices
% o PK: 4D array of k-step ahead forecast error variance
% matrices (meaningless for periods 1:d)
% o decomp 4D array of shock decomposition of k-step ahead
% filtered variables
%
% ALGORITHM
% Diffuse Kalman filter (Durbin and Koopman)
%
% SPECIAL REQUIREMENTS
% None
% Copyright (C) 2006-2012 Dynare Team
% Copyright (C) 2006-2014 Dynare Team
%
% This file is part of Dynare.
%

2
matlab/dynare_estimation_1.m
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@ -201,7 +201,7 @@ end
if isequal(options_.mode_compute,0) && isempty(options_.mode_file) && options_.mh_posterior_mode_estimation==0
if options_.smoother == 1
[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp] = DsgeSmoother(xparam1,gend,data,data_index,missing_value);
[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp] = DsgeSmoother(xparam1,gend,transpose(data),data_index,missing_value);
oo_.Smoother.SteadyState = ys;
oo_.Smoother.TrendCoeffs = trend_coeff;
if options_.filter_covariance

2
matlab/dynare_estimation_init.m
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@ -321,6 +321,8 @@ if isempty(estim_params_)% If estim_params_ is empty (e.g. when running the smoo
estim_params_.ncx = 0;
estim_params_.ncn = 0;
estim_params_.np = 0;
bounds.lb = [];
bounds.ub = [];
end
% storing prior parameters in results

1
tests/Makefile.am
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@ -154,6 +154,7 @@ MODFILES = \
kalman_filter_smoother/fs2000_1.mod \
kalman_filter_smoother/fs2000_2.mod \
kalman_filter_smoother/fs2000a.mod \
kalman_filter_smoother/fs2000_smoother_only.mod \
kalman_filter_smoother/check_variable_dimensions/fs2000.mod \
kalman_filter_smoother/check_variable_dimensions/fs2000_ML.mod \
second_order/burnside_1.mod \

132
tests/kalman_filter_smoother/fs2000_smoother_only.mod Normal file
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@ -0,0 +1,132 @@
/*
* This file replicates the estimation of the cash in advance model described
* Frank Schorfheide (2000): "Loss function-based evaluation of DSGE models",
* Journal of Applied Econometrics, 15(6), 645-670.
*
* The data are in file "fsdat_simul.m", and have been artificially generated.
* They are therefore different from the original dataset used by Schorfheide.
*
* The equations are taken from J. Nason and T. Cogley (1994): "Testing the
* implications of long-run neutrality for monetary business cycle models",
* Journal of Applied Econometrics, 9, S37-S70.
* Note that there is an initial minus sign missing in equation (A1), p. S63.
*
* This implementation was written by Michel Juillard. Please note that the
* following copyright notice only applies to this Dynare implementation of the
* model.
*/
/*
* Copyright (C) 2004-2010 Dynare Team
*
* This file is part of Dynare.
*
* Dynare 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.
*
* Dynare 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.
*
* You should have received a copy of the GNU General Public License
* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
*/
var m P c e W R k d n l gy_obs gp_obs y dA;
varexo e_a e_m;
parameters alp bet gam mst rho psi del;
alp = 0.33;
bet = 0.99;
gam = 0.003;
mst = 1.011;
rho = 0.7;
psi = 0.787;
del = 0.02;
model;
dA = exp(gam+e_a);
log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
W = l/n;
-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
P*c = m;
m-1+d = l;
e = exp(e_a);
y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
gy_obs = dA*y/y(-1);
gp_obs = (P/P(-1))*m(-1)/dA;
end;
initval;
k = 6;
m = mst;
P = 2.25;
c = 0.45;
e = 1;
W = 4;
R = 1.02;
d = 0.85;
n = 0.19;
l = 0.86;
y = 0.6;
gy_obs = exp(gam);
gp_obs = exp(-gam);
dA = exp(gam);
end;
shocks;
var e_a; stderr 0.014;
var e_m; stderr 0.005;
end;
steady_state_model;
dA = exp(gam);
gst = 1/dA;
m = mst;
khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
nust = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
n = xist/(nust+xist);
P = xist + nust;
k = khst*n;
l = psi*mst*n/( (1-psi)*(1-n) );
c = mst/P;
d = l - mst + 1;
y = k^alp*n^(1-alp)*gst^alp;
R = mst/bet;
W = l/n;
ist = y-c;
q = 1 - d;
e = 1;
gp_obs = m/dA;
gy_obs = dA;
end;
steady;
check;
varobs gp_obs gy_obs;
estimation(order=1, datafile=fsdat_simul, mode_compute=0,nobs=192, loglinear, smoother) m P c e W R k d n l gy_obs gp_obs y dA;
/*
* The following lines were used to generate the data file. If you want to
* generate another random data file, comment the "estimation" line and uncomment
* the following lines.
*/
//stoch_simul(periods=200, order=1);
//datatomfile('fsdat_simul', char('gy_obs', 'gp_obs'));