diff --git a/doc/manual/source/the-model-file.rst b/doc/manual/source/the-model-file.rst
index 064ba0c51f7c3b046a7af47ff476f5900d4b9347..63ba6916c020bb55d5c191b941ddff365b7e811b 100644
--- a/doc/manual/source/the-model-file.rst
+++ b/doc/manual/source/the-model-file.rst
@@ -7461,7 +7461,7 @@ observed variables.
Triggers the computation of the posterior distribution of
IRFs. The length of the IRFs are controlled by the ``irf``
option. Results are stored in ``oo_.PosteriorIRF.dsge`` (see
- below for a description of this variable).
+ below for a description of this variable). Not compatible with OccBin.
.. option:: relative_irf
@@ -7753,7 +7753,7 @@ observed variables.
stored in ``oo_.PosteriorTheoreticalMoments`` (see
:mvar:`oo_.PosteriorTheoreticalMoments`). The number of lags in
the autocorrelation function is controlled by the ``ar``
- option.
+ option. Not compatible with OccBin.
.. option:: contemporaneous_correlation
@@ -7838,7 +7838,7 @@ observed variables.
the posterior mode. If a Metropolis-Hastings is computed, the
distribution of forecasts is stored in variables
``oo_.PointForecast`` and ``oo_.MeanForecast``. See
- :ref:`fore`, for a description of these variables.
+ :ref:`fore`, for a description of these variables. Not compatible with OccBin.
.. option:: tex
diff --git a/matlab/estimation/dynare_estimation_1.m b/matlab/estimation/dynare_estimation_1.m
index 21ccfa542184e5a875280207ff8b43198b0634c9..2800c84b089a15eab551e0685ec3098e600fa517 100644
--- a/matlab/estimation/dynare_estimation_1.m
+++ b/matlab/estimation/dynare_estimation_1.m
@@ -514,7 +514,11 @@ if issmc(options_) || (any(bayestopt_.pshape>0) && options_.mh_replic) || (any(
if error_flag
error('%s: I cannot compute the posterior IRFs!',dispString)
end
- oo_=PosteriorIRF('posterior',options_,estim_params_,oo_,M_,bayestopt_,dataset_,dataset_info,dispString);
+ if options_.occbin.likelihood.status
+ fprintf('%s: the bayesian_irf option is not compatible with the use of OccBin.',dispString)
+ else
+ oo_=PosteriorIRF('posterior',options_,estim_params_,oo_,M_,bayestopt_,dataset_,dataset_info,dispString);
+ end
else
fprintf('%s: SMC does not yet support the bayesian_irf option. Skipping computation.\n',dispString);
end
@@ -543,7 +547,11 @@ if issmc(options_) || (any(bayestopt_.pshape>0) && options_.mh_replic) || (any(
end
end
end
- oo_ = compute_moments_varendo('posterior',options_,M_,oo_,estim_params_,var_list_);
+ if options_.occbin.likelihood.status
+ fprintf('%s: the moments_varendo option is not compatible with the use of OccBin.',dispString)
+ else
+ oo_ = compute_moments_varendo('posterior',options_,M_,oo_,estim_params_,var_list_);
+ end
else
fprintf('%s: SMC does not yet support the moments_varendo option. Skipping computation.\n',dispString);
end
diff --git a/matlab/estimation/initial_estimation_checks.m b/matlab/estimation/initial_estimation_checks.m
index 148a219d529b2257fb6165bbd8980e0217b6f15c..cea50c9f2f122922b2d3a71e0c029dc951b65747 100644
--- a/matlab/estimation/initial_estimation_checks.m
+++ b/matlab/estimation/initial_estimation_checks.m
@@ -86,6 +86,15 @@ if options_.occbin.likelihood.status || options_.occbin.smoother.status
if options_.fast_kalman_filter
error('initial_estimation_checks:: Occbin is incompatible with the fast Kalman filter.')
end
+ if options_.bayesian_irf
+ error('initial_estimation_checks:: Occbin is incompatible with the bayesian_irf option.')
+ end
+ if options_.moments_varendo
+ error('initial_estimation_checks:: Occbin is incompatible with the moments_varendo option.')
+ end
+ if options_.forecast
+ error('initial_estimation_checks:: Occbin is incompatible with the forecast option.')
+ end
end
if (options_.occbin.likelihood.status && options_.occbin.likelihood.inversion_filter) || (options_.occbin.smoother.status && options_.occbin.smoother.inversion_filter)
diff --git a/matlab/estimation/prior_posterior_statistics_core.m b/matlab/estimation/prior_posterior_statistics_core.m
index 65660dabb59324575ac2bbcee33e3d90c0aff31b..f10585aca1e784c369d8588d2b04dad6f541790d 100644
--- a/matlab/estimation/prior_posterior_statistics_core.m
+++ b/matlab/estimation/prior_posterior_statistics_core.m
@@ -76,7 +76,7 @@ naK=myinputs.naK;
horizon=myinputs.horizon;
iendo=myinputs.iendo;
IdObs=myinputs.IdObs; %index of observables
-if horizon
+if horizon && ~options_.occbin.smoother.status
i_last_obs=myinputs.i_last_obs;
MAX_nforc1=myinputs.MAX_nforc1;
MAX_nforc2=myinputs.MAX_nforc2;
@@ -167,7 +167,7 @@ if run_smoother
stock_smoothed_constant=NaN(endo_nbr,gend,MAX_n_smoothed_constant);
stock_smoothed_trend=NaN(endo_nbr,gend,MAX_n_smoothed_trend);
stock_trend_coeff = zeros(endo_nbr,MAX_n_trend_coeff);
- if horizon
+ if horizon && ~options_.occbin.smoother.status
stock_forcst_mean= NaN(endo_nbr,horizon,MAX_nforc1);
stock_forcst_point = NaN(endo_nbr,horizon,MAX_nforc2);
if ~isequal(M_.H,0)
@@ -310,7 +310,7 @@ for b=fpar:B
end
end
end
- if horizon
+ if horizon && ~options_.occbin.smoother.status
yyyy = alphahat(iendo,i_last_obs);
yf = simulate_posterior_forecasts(yyyy,dr,horizon,false,M_.Sigma_e,1);
if options_.prefilter
@@ -545,7 +545,7 @@ dyn_waitbar_close(h);
function yf=simulate_posterior_forecasts(y0,dr,horizon,stochastic_indicator,Sigma_e,n)
-% function yf=forcst2(y0,horizon,dr,n)
+% function yf=simulate_posterior_forecasts(y0,horizon,dr,n)
%
% computes forecasts based on first order model solution, given shocks
% drawn from the shock distribution, but not including measurement error