diff --git a/matlab/+occbin/set_default_options.m b/matlab/+occbin/set_default_options.m
index 68d90928c792d8a40b942f3c855dde8a7ba5c615..4b3153e9318b77efd49ae7bc24e52219f352512c 100644
--- a/matlab/+occbin/set_default_options.m
+++ b/matlab/+occbin/set_default_options.m
@@ -67,7 +67,7 @@ end
if ismember(flag,{'likelihood','all'})
options_occbin_.likelihood.curb_retrench = false;
- options_occbin_.likelihood.first_period_occbin_update = true;
+ options_occbin_.likelihood.first_period_occbin_update = 1;
options_occbin_.likelihood.full_output = false;
options_occbin_.likelihood.IF_likelihood = false;
options_occbin_.likelihood.init_regime_history = [];
@@ -187,7 +187,7 @@ if ismember(flag,{'smoother','all'})
options_occbin_.smoother.curb_retrench = false;
options_occbin_.smoother.debug = false;
options_occbin_.smoother.fast = false;
- options_occbin_.smoother.first_period_occbin_update = true;
+ options_occbin_.smoother.first_period_occbin_update = 1;
options_occbin_.smoother.full_output = false;
% options.occbin.smoother.init_mode = 1; % 0 = standard; 1 = unconditional frcsts zero shocks+smoothed states in each period
options_occbin_.smoother.init_regime_history = [];
diff --git a/matlab/+occbin/solve_one_constraint.m b/matlab/+occbin/solve_one_constraint.m
index f5f0c1446c79ff6edf9b1c829e8b98c90f2216ca..2f7834df9d589ea14b7c7f497f30411d432eaad2 100644
--- a/matlab/+occbin/solve_one_constraint.m
+++ b/matlab/+occbin/solve_one_constraint.m
@@ -105,7 +105,7 @@ end
SS_out.T = NaN(DM.n_vars,DM.n_vars,n_shocks_periods);
SS_out.R = NaN(DM.n_vars,DM.n_exo,n_shocks_periods);
SS_out.C = nan(DM.n_vars,n_shocks_periods);
-if ~exist('regime_history_','var') || isempty(regime_history_guess)
+if isempty(regime_history_guess)
regime_history = struct();
guess_history = false;
else
@@ -152,9 +152,7 @@ for shock_period = 1:n_shocks_periods
if length(binding_indicator)<(nperiods_0 + 1)
binding_indicator=[binding_indicator; false(nperiods_0 + 1-length(binding_indicator),1)];
end
-
- binding_indicator_history{iter}=binding_indicator;
-
+
if iter==1 && guess_history_it
regime = regime_history_guess(shock_period).regime;
regime_start = regime_history_guess(shock_period).regimestart;
@@ -164,6 +162,7 @@ for shock_period = 1:n_shocks_periods
end
nperiods_0 = size(binding_indicator,1)-1; %if history is present, update may be required
end
+ binding_indicator_history{iter}=binding_indicator;
% analyze when each regime starts based on current guess
[regime, regime_start, error_code_period]=occbin.map_regime(binding_indicator,opts_simul_.debug);
regime_history(shock_period).regime = regime;
diff --git a/matlab/+occbin/solve_two_constraints.m b/matlab/+occbin/solve_two_constraints.m
index 80744ac50943fa24b2e3ee285cb7ad3d3c587152..eab9c269b6614321f7e9cbd40a36567957834c52 100644
--- a/matlab/+occbin/solve_two_constraints.m
+++ b/matlab/+occbin/solve_two_constraints.m
@@ -115,7 +115,7 @@ end
SS_out.T = NaN(DM.n_vars,DM.n_vars,n_shocks_periods);
SS_out.R = NaN(DM.n_vars,DM.n_exo,n_shocks_periods);
SS_out.C = NaN(DM.n_vars,n_shocks_periods);
-if ~exist('regime_history_','var') || isempty(regime_history_guess)
+if isempty(regime_history_guess)
regime_history = struct();
guess_history = false;
else
@@ -164,7 +164,6 @@ for shock_period = 1:n_shocks_periods
% unconstrained regime (nperiods_0)
binding_indicator=[binding_indicator; false(nperiods_0 + 1-size(binding_indicator,1),2)];
end
- binding_indicator_history{iter}=binding_indicator;
if iter==1 && guess_history_it
regime_1 = regime_history_guess(shock_period).regime1;
@@ -181,6 +180,8 @@ for shock_period = 1:n_shocks_periods
end
nperiods_0 = size(binding_indicator,1)-1; %if history is present, update may be required
end
+ binding_indicator_history{iter}=binding_indicator;
+
% analyse violvec and isolate contiguous periods in the other regime.
[regime_1, regime_start_1, error_code_period(1)]=occbin.map_regime(binding_indicator(:,1),opts_simul_.debug);
regime_history(shock_period).regime1 = regime_1;
diff --git a/matlab/+occbin/solver.m b/matlab/+occbin/solver.m
index 11ac70eafa860dc806753c2fa63a3e9bb7b2d1fc..e38293bcf01d637ce9b6e0829573cb6281b5ba6a 100644
--- a/matlab/+occbin/solver.m
+++ b/matlab/+occbin/solver.m
@@ -54,6 +54,9 @@ if solve_dr
if isempty(options_.qz_criterium)
options_.qz_criterium = 1+1e-6;
end
+ if options_.order>1
+ options_.order = 1;
+ end
[dr,error_flag,M_,oo_] = resol(0,M_,options_,oo_);
out.error_flag=error_flag;
diff --git a/matlab/evaluate_likelihood.m b/matlab/evaluate_likelihood.m
index f48385a843e286c0e2ed0c0cecf1710514ac50f1..692588145c71fe566499197d5f8729ee3bf21f30 100644
--- a/matlab/evaluate_likelihood.m
+++ b/matlab/evaluate_likelihood.m
@@ -47,24 +47,24 @@ end
if ischar(parameters)
switch parameters
- case 'posterior mode'
- parameters = get_posterior_parameters('mode',M_,estim_params_,oo_,options_);
- case 'posterior mean'
- parameters = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
- case 'posterior median'
- parameters = get_posterior_parameters('median',M_,estim_params_,oo_,options_);
- case 'prior mode'
- parameters = bayestopt_.p5(:);
- case 'prior mean'
- parameters = bayestopt_.p1;
- otherwise
- disp('eval_likelihood:: If the input argument is a string, then it has to be equal to:')
- disp(' ''posterior mode'', ')
- disp(' ''posterior mean'', ')
- disp(' ''posterior median'', ')
- disp(' ''prior mode'' or')
- disp(' ''prior mean''.')
- error
+ case 'posterior mode'
+ parameters = get_posterior_parameters('mode',M_,estim_params_,oo_,options_);
+ case 'posterior mean'
+ parameters = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
+ case 'posterior median'
+ parameters = get_posterior_parameters('median',M_,estim_params_,oo_,options_);
+ case 'prior mode'
+ parameters = bayestopt_.p5(:);
+ case 'prior mean'
+ parameters = bayestopt_.p1;
+ otherwise
+ disp('eval_likelihood:: If the input argument is a string, then it has to be equal to:')
+ disp(' ''posterior mode'', ')
+ disp(' ''posterior mean'', ')
+ disp(' ''posterior median'', ')
+ disp(' ''prior mode'' or')
+ disp(' ''prior mean''.')
+ error
end
end
@@ -73,10 +73,23 @@ if isempty(dataset)
end
options_=select_qz_criterium_value(options_);
+if ~isempty(bayestopt_) && any(bayestopt_.pshape > 0)
+ % Plot prior densities.
+ % Set prior bounds
+ bounds = prior_bounds(bayestopt_, options_.prior_trunc);
+else % estimated parameters but no declared priors
+ % No priors are declared so Dynare will estimate the model by
+ % maximum likelihood with inequality constraints for the parameters.
+ [~,~,~,lb,ub] = set_prior(estim_params_,M_,options_);
+ bounds.lb = lb;
+ bounds.ub = ub;
+end
+
+
if options_.occbin.likelihood.status && options_.occbin.likelihood.inversion_filter
- llik = -occbin.IVF_posterior(parameters,dataset,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
-else
- llik = -dsge_likelihood(parameters,dataset,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
+ llik = -occbin.IVF_posterior(parameters,dataset,dataset_info,options_,M_,estim_params_,bayestopt_,bounds,oo_);
+else
+ llik = -dsge_likelihood(parameters,dataset,dataset_info,options_,M_,estim_params_,bayestopt_,bounds,oo_);
end
ldens = evaluate_prior(parameters,M_,estim_params_,oo_,options_,bayestopt_);
llik = llik - ldens;
\ No newline at end of file