diff --git a/doc/manual/source/the-model-file.rst b/doc/manual/source/the-model-file.rst
index 07101fdb669a29dab9241a82d8b947a29b0b5bde..fb077a848a5c782c47f164f8d80a6a0084883a05 100644
--- a/doc/manual/source/the-model-file.rst
+++ b/doc/manual/source/the-model-file.rst
@@ -1769,7 +1769,7 @@ in this case ``initval`` is used to specify the terminal conditions.
in the last ``initval`` or ``endval`` block (or the steady state
file if you provided one, see :ref:`st-st`).
-.. command:: initval_file (filename = FILENAME);
+.. command:: initval_file (OPTIONS...);
|br| In a deterministic setup, this command is used to specify a
path for all endogenous and exogenous variables. The length of
@@ -1786,33 +1786,534 @@ in this case ``initval`` is used to specify the terminal conditions.
by the path for endogenous variables for the simulation
periods (excluding initial and terminal conditions)
- The command accepts three file formats:
+ In perfect foresight and stochastic contexts, ``steady`` uses the
+ first observation loaded by ``initval_file`` as guess value to
+ solve for the steady state of the model. This first observation is
+ determined by the ``first_obs`` option when it is used.
+
+ Don’t mix ``initval_file`` with ``initval`` statements. However,
+ after ``initval_file``, you can modify the historical initial
+ values with ``histval`` or ``histval_file`` statement.
+
+ There can be several ``initval_file`` statements in a model
+ file. Each statement resets ``oo_.initval_series``.
+
+ *Options*
+
+ .. option:: datafile = FILENAME
+ filename = FILENAME (deprecated)
+
+ The name of the file containing the data. It must be included in quotes if the filename
+ contains a path or an extension. The command accepts the following file formats:
* M-file (extension ``.m``): for each endogenous and exogenous
variable, the file must contain a row or column vector of
- the same name. Their length must be ``periods +
- M_.maximum_lag + M_.maximum_lead``
+ the same name.
* MAT-file (extension ``.mat``): same as for M-files.
* Excel file (extension ``.xls`` or ``.xlsx``): for each
- endogenous and exogenous, the file must contain a column of
- the same name. NB: Octave only supports the ``.xlsx`` file
- extension and must have the `io`_ package installed (easily
- done via octave by typing ‘``pkg install -forge io``’).
+ endogenous and exogenous variable, the file must contain a
+ column of the same name. NB: Octave only supports the
+ ``.xlsx`` file extension and must have the `io`_ package
+ installed (easily done via octave by typing ‘``pkg
+ install -forge io``’). The first column may contain the date
+ of each observation.
+ * CSV files (extension ``.csv``): for each endogenous and
+ exogenous variable, the file must contain a column of the
+ same name. The first column may contain the date of each
+ observation.
+
+ .. option:: first_obs = {INTEGER | DATE}
+
+ The observation number or the date (see
+ :ref:`dates-members`) of the first observation to be used in the file
+
+ .. option:: first_simulation_period = {INTEGER | DATE}
+
+ The observation number in the file or the date (see
+ :ref:`dates <dates-members>`) at which the simulation (or the forecast) is
+ starting. This option avoids to have to compute the maximum
+ number of lags in the model. The observation corresponding to
+ the first period of simulation doesn’t need to exist in the
+ file as the only dates necessary for initialization are before
+ that date.
+
+ .. option:: last_obs = {INTEGER | DATE}
+
+ The observaton number or the date (see
+ :ref:`dates-members`) of the last observation to be used in
+ the file.
+
+ .. option:: nobs = INTEGER
+
+ The number of observations to be used in the file (starting
+ with first of ``first_obs`` observation).
+
+ .. option:: series = DSERIES NAME
+
+ The name of a DSERIES containing the data (see :ref:`dseries-members`)
+
+ *Example 1*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ initval_file(datafile=mydata.csv);
+
+ perfect_foresight_setup(periods=200);
+ perfect_foresight_solver;
+
+ The initial and terminal values are taken from file
+ ``mydata.csv`` (nothing guarantees that these vales are the
+ steady state of the model). The guess value for the
+ trajectories are also taken from the file. The file must
+ contain at least 203 observations of variables ``c``, ``x``
+ and ``e``. If there are more than 203 observations available
+ in the file, the first 203 are used by
+ ``perfect_foresight_setup(periods=200)``.
+ Note that the values for the auxiliary variable corresponding
+ to ``x(-2)`` are automatically computed by ``initval_file``.
+
+ *Example 2*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ initval_file(datafile=mydata.csv,
+ first_obs=10);
+
+ perfect_foresight_setup(periods=200);
+ perfect_foresight_solver;
+
+ The initial and terminal values are taken from file
+ ``mydata.csv`` starting with the 10th observation in the
+ file. There must be at least 212 observations in the file.
+
+ *Example 3*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ ds = dseries(mydata.csv);
+ lds = log(ds);
+
+ initval_file(series=lds,
+ first_obs=2010Q1);
+
+ perfect_foresight_setup(periods=200);
+ perfect_foresight_solver;
- .. warning:: The extension must be omitted in the command
- argument. Dynare will automatically figure out the
- extension and select the appropriate file type. If
- there are several files with the same name but different
- extensions, then the order of precedence is as follows:
- first ``.m``, then ``.mat``, ``.xls`` and finally ``.xlsx``.
+ The initial and terminal values are taken from dseries
+ ``lds``. All observations are loaded starting with the 1st quarter of
+ 2010 until the end of the file. There must be data available
+ at least until 2050Q3.
+
+ *Example 4*
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
-.. command:: histval_file (filename = FILENAME);
+ initval_file(datafile=mydata.csv,
+ first_simulation_period=2010Q1);
+
+ perfect_foresight_setup(periods=200);
+ perfect_foresight_solver;
+
+ The initial and terminal values are taken from file
+ ``mydata.csv``. The observations in the file must have
+ dates. All observations are loaded from the 3rd quarter of
+ 2009 until the end of the file. There must be data available
+ in the file at least until 2050Q1.
+
+ *Example 5*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ initval_file(datafile=mydata.csv,
+ last_obs = 212);
+
+ perfect_foresight_setup(periods=200);
+ perfect_foresight_solver;
+
+ The initial and terminal values are taken from file
+ ``mydata.csv``. The first 212 observations are loaded and the
+ first 203 observations will be used by
+ ``perfect_foresight_setup(periods=200)``.
+
+ *Example 6*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ initval_file(datafile=mydata.csv,
+ first_obs = 10,
+ nobs = 203);
+
+ perfect_foresight_setup(periods=200);
+ perfect_foresight_solver;
+
+ The initial and terminal values are taken from file
+ ``mydata.csv``. Observations 10 to 212 are loaded.
+
+ *Example 7*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ initval_file(datafile=mydata.csv,
+ first_obs = 10);
+
+ steady;
+
+ The values of the 10th observation of ``mydata.csv`` are used
+ as guess value to compute the steady state. The exogenous
+ variables are set to values found in the file or zero if these
+ variables aren't present.
+
+.. command:: histval_file (OPTIONS...);
|br| This command is equivalent to ``histval``, except that it
reads its input from a file, and is typically used in conjunction
with ``smoother2histval``.
+ *Options*
+
+ .. option:: datafile = FILENAME
+ filename = FILENAME (deprecated)
+
+ The name of the file containing the data. The command accepts
+ the following file formats:
+
+ * M-file (extension ``.m``): for each endogenous and exogenous
+ variable, the file must contain a row or column vector of
+ the same name.
+ * MAT-file (extension ``.mat``): same as for M-files.
+ * Excel file (extension ``.xls`` or ``.xlsx``): for each
+ endogenous and exogenous variable, the file must contain a
+ column of the same name. NB: Octave only supports the
+ ``.xlsx`` file extension and must have the `io`_ package
+ installed (easily done via octave by typing ‘``pkg
+ install -forge io``’). The first column may contain the
+ date of each observation.
+ * CSV files (extension ``.csv``): for each endogenous and
+ exogenous variable, the file must contain a column of the
+ same name. The first column may contain the date of each
+ observation.
+
+ .. option:: first_obs = {INTEGER | DATE}
+
+ The observation number or the date (see :ref:`dates-members`) of
+ the first observation to be used in the file
+
+ .. option:: first_simulation_period = {INTEGER | DATE}
+
+ The observation number in the file or the date (see
+ :ref:`dates-members`) at which the simulation (or the forecast) is
+ starting. This option avoids to have to compute the maximum
+ number of lags in the model. The observation corresponding to
+ the first period of simulation doesn’t need to exist in the
+ file as the only dates necessary for initialization are before
+ that date.
+
+ .. option:: last_obs = {INTEGER | DATE}
+
+ The observation number or the date (see :ref:`dates-members`) of the
+ last observation to be used in the file.
+
+ .. option:: nobs = INTEGER
+
+ The number of observations to be used in the file (starting
+ with first of ``first_obs`` observation).
+
+ .. option:: series = DSERIES NAME
+
+ The name of a DSERIES containing the data (see :ref:`dseries-members`)
+
+ *Example 1*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ steady_state_model;
+ x = 0;
+ c = exp(c*x/(1 - d));
+ end;
+
+ histval_file(datafile=mydata.csv);
+
+ stoch_simul(order=1,periods=100);
+
+ The initial values for the stochastic simulation are taken
+ from the two first rows of file ``mydata.csv``.
+
+ *Example 2*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ histval_file(datafile=mydata.csv,
+ first_obs=10);
+
+ stoch_simul(order=1,periods=100);
+
+ The initial values for the stochastic simulation are taken
+ from rows 10 and 11 of file ``mydata.csv``.
+
+
+ *Example 3*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ histval_file(datafile=mydata.csv,
+ first_obs=2010Q1);
+
+ stoch_simul(order=1,periods=100);
+
+ The initial values for the stochastic simulation are taken
+ from observations 2010Q1 and 2010Q2 of file ``mydata.csv``.
+
+ *Example 4*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ histval_file(datafile=mydata.csv,
+ first_simulation_period=2010Q1)
+
+ stoch_simul(order=1,periods=100);
+
+ The initial values for the stochastic simulation are taken
+ from observations 2009Q3 and 2009Q4 of file ``mydata.csv``.
+
+ *Example 5*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ histval_file(datafile=mydata.csv,
+ last_obs = 4);
+
+ stoch_simul(order=1,periods=100);
+
+ The initial values for the stochastic simulation are taken
+ from the two first rows of file ``mydata.csv``.
+
+ *Example 6*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ initval_file(datafile=mydata.csv,
+ first_obs = 10,
+ nobs = 4);
+
+ stoch_simul(order=1,periods=100);
+
+ The initial values for the stochastic simulation are taken
+ from rows 10 and 11 of file ``mydata.csv``.
+
+ *Example 7*
+
+ ::
+
+ var c x;
+ varexo e;
+ parameters a b c d;
+
+ a = 1.5;
+ b = -0,6;
+ c = 0.5;
+ d = 0.5;
+
+ model;
+ x = a*x(-1) + b*x(-2) + e;
+ log(c) = c*x + d*log(c(+1));
+ end;
+
+ initval_file(datafile=mydata.csv,
+ first_obs=10);
+
+ histval_file(datafile=myotherdata.csv);
+
+ perfect_foresight_setup(periods=200);
+ perfect_foresight_solver;
+
+ Historical initial values for the simulation are taken from
+ the two first rows of file ``myotherdata.csv``.
+
+ Terminal values and guess values for the simulation are taken
+ from file ``mydata.csv`` starting with the 12th observation in
+ the file. There must be at least 212 observations in the file.
.. _shocks-exo:
diff --git a/matlab/global_initialization.m b/matlab/global_initialization.m
index 1b35a37e5028aab81d7af7ce06f5ded17b839c9c..8f5f909d55def5590e0a9fdee32adbf980f478c7 100644
--- a/matlab/global_initialization.m
+++ b/matlab/global_initialization.m
@@ -92,6 +92,7 @@ oo_.dr = [];
oo_.exo_steady_state = [];
oo_.exo_det_steady_state = [];
oo_.exo_det_simul = [];
+oo_.initval_series = dseries();
oo_.gui.ran_estimation = false;
oo_.gui.ran_stoch_simul = false;
diff --git a/matlab/histvalf.m b/matlab/histvalf.m
index f1f9fb0983aa96ef544e00108be77c58beb921a8..f15e72511e4c2bd269c7075929c367f33669de40 100644
--- a/matlab/histvalf.m
+++ b/matlab/histvalf.m
@@ -1,5 +1,5 @@
-function histvalf(fname)
-%function histvalf(fname)
+function [endo_histval, exo_histval, exo_det_histval] = histvalf(M, options)
+%function [endo_histval, exo_histval, exo_det_histval] = histvalf(M, options)
% Sets initial values for simulation using values contained in `fname`, a
% file possibly created by a call to `smoother2histval`
%
@@ -13,7 +13,7 @@ function histvalf(fname)
% none
-% Copyright (C) 2014-2019 Dynare Team
+% Copyright (C) 2014-2020 Dynare Team
%
% This file is part of Dynare.
%
@@ -30,72 +30,41 @@ function histvalf(fname)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-global M_ oo_ ex0_
-
-if ~exist(fname, 'file')
- error(['Can''t find datafile: ' fname ]);
+if ~isfield(options, 'nobs') || isempty(options.nobs)
+ options.nobs = M.orig_maximum_lag;
end
-M_.endo_histval = repmat(oo_.steady_state, 1, M_.maximum_endo_lag);
-
-% Also fill in oo_.exo_simul: necessary if we are in deterministic context,
-% since aux vars for lagged exo are not created in this case
-if isempty(oo_.exo_simul)
- if isempty(ex0_)
- oo_.exo_simul = repmat(oo_.exo_steady_state',M_.maximum_lag,1);
+if ~isfield(options, 'first_obs') || isempty(options.first_obs)
+ if isfield(options, 'first_simulation_period')
+ options.first_obs = options.first_simulation_period ...
+ - options.nobs;
else
- oo_.exo_simul = repmat(ex0_',M_.maximum_lag,1);
+ options.first_obs = 1;
+ end
+elseif isfield(options, 'first_simulation_period')
+ nobs = options.first_simulation_period - opions_.first_obs;
+ if options.nobs ~= nobs
+ error(sprintf(['HISTVALF: first_obs = %d and', ...
+ ' first_simulation_period = %d', ...
+ ' don''t provide for the number of' ...
+ ' lags in the model.'], ...
+ options.first_obs, ...
+ options.first_simulation_period))
end
end
-S = load(fname);
-
-outvars = fieldnames(S);
+series = histvalf_initvalf('HISTVAL', M, options);
+% capture the difference between stochastic and
+% perfect foresight setup
+k = M.orig_maximum_lag - M.maximum_lag + 1;
+endo_histval = series{M.endo_names{:}}.data(k:end, :)';
-for i = 1:length(outvars)
- ov_ = outvars{i};
- if ov_(end) == '_'
- ov = ov_(1:end-1);
- j = strmatch(ov, M_.endo_names, 'exact');
- if isempty(j)
- warning(['smoother2histval: output variable ' ov ' does not exist.'])
- end
- else
- % Lagged endogenous or exogenous, search through aux vars
- undidx = find(ov_ == '_', 1, 'last'); % Index of last underscore in name
- ov = ov_(1:(undidx-1));
- lead_lag = ov_((undidx+1):end);
- lead_lag = regexprep(lead_lag,'l','-');
- lead_lag = str2num(lead_lag);
- j = [];
- for i = 1:length(M_.aux_vars)
- if M_.aux_vars(i).type ~= 1 && M_.aux_vars(i).type ~= 3
- continue
- end
- if M_.aux_vars(i).type == 1
- % Endogenous
- orig_var = M_.endo_names{M_.aux_vars(i).orig_index};
- else
- % Exogenous
- orig_var = M_.exo_names{M_.aux_vars(i).orig_index};
- end
- if strcmp(orig_var, ov) && M_.aux_vars(i).orig_lead_lag == lead_lag
- j = M_.aux_vars(i).endo_index;
- end
- end
- if isempty(j)
- % There is no aux var corresponding to (orig_var, lead_lag).
- % If this is an exogenous variable, then it means we should put
- % the value in oo_.exo_simul (we are probably in deterministic
- % context).
- k = strmatch(ov, M_.exo_names);
- if isempty(k)
- warning(['smoother2histval: output variable ' ov '(' lead_lag ') does not exist.'])
- else
- oo_.exo_simul((M_.maximum_lag-M_.maximum_endo_lag+1):M_.maximum_lag, k) = S.(ov_);
- end
- continue
- end
- end
- M_.endo_histval(j, :) = S.(ov_);
+exo_histval = [];
+if M.exo_nbr
+ exo_histval = series{M.exo_names{:}}.data(k:end, :)';
end
+exo_det_histval = [];
+if M.exo_det_nbr
+ exo_det_histval = series{M.exo_names{:}}.data(k:end, :)';
+end
+
diff --git a/matlab/histvalf_initvalf.m b/matlab/histvalf_initvalf.m
new file mode 100644
index 0000000000000000000000000000000000000000..e65779c493129a3d732c9ecd4e4afca72421f4c0
--- /dev/null
+++ b/matlab/histvalf_initvalf.m
@@ -0,0 +1,223 @@
+function series = histvalf_initvalf(caller, M, options)
+% function initvalf(M)
+%
+% handles options for histvalf_initvalf() and initvalf()
+%
+% INPUTS
+% caller: string, name of calling function
+% M: model structure
+% options: options specific to initivalf
+%
+% OUTPUTS
+% series: dseries containing selected data from a file or a dseries
+%
+
+% Copyright (C) 2003-2020 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/>.
+
+
+% dseries
+if isfield(options, 'series')
+ series = options.series;
+ dseries_ispresent = true;
+else
+ dseries_ispresent = false;
+end
+
+% file
+datafile = '';
+if isfield(options, 'filename')
+ warning([caller, '_FILE: option FILENAME is deprecated, please use', ...
+ ' option DATAFILE'])
+ if dseries_ispresent
+ error([caller, '_FILE: you can''t use option FILENAME and option SERIES', ...
+ ' at the same time'])
+ end
+ if isfield(options, 'datafile')
+ error([caller, '_FILE: you can''t use option DATAFILE and option FILENAME', ...
+ ' at the same time'])
+ end
+ datafile = options.filename;
+end
+
+if isfield(options, 'datafile')
+ if dseries_ispresent
+ error([caller, '_FILE: you can''t use option DATAFILE and option SERIES', ...
+ ' at the same time'])
+ end
+ datafile = options.datafile;
+end
+
+if datafile
+ [directory,basename,extension] = fileparts(datafile);
+ % Auto-detect extension if not provided
+ if isempty(extension)
+ if exist([basename '.m'],'file')
+ extension = '.m';
+ elseif exist([basename '.mat'],'file')
+ extension = '.mat';
+ elseif exist([basename '.xls'],'file')
+ extension = '.xls';
+ elseif exist([basename '.xlsx'],'file')
+ extension = '.xlsx';
+ else
+ error([caller, '_FILE: Can''t find datafile: ' basename '.{m,mat,xls,xlsx}']);
+ end
+ end
+
+ fullname = [basename extension];
+ series = dseries(fullname);
+end
+
+% checking that all variable are present
+error_flag = false;
+for i = 1:M.orig_endo_nbr
+ if ~series.exist(M.endo_names{i})
+ disp(sprintf('%s_FILE: endogenous variable %s is missing', ...
+ caller, M.endo_names{i}))
+ error_flag = true;
+ end
+end
+
+for i = 1:M.exo_nbr
+ if ~series.exist(M.exo_names{i})
+ disp(sprintf('%s_FILE: exogenous variable %s is missing', ...
+ caller, M.exo_names{i}))
+ error_flag = true;
+ end
+end
+
+for i = 1:M.exo_det_nbr
+ if ~series.exist(M.exo_det_names{i})
+ disp(sprintf('%s_FILE: exo_det variable %s is missing', ...
+ caller, M.exo_det_names{i}))
+ error_flag = true;
+ end
+end
+
+if error_flag
+ error([caller, '_FILE: some variables are missing'])
+end
+
+if exist(sprintf('+%s/dynamic_set_auxiliary_series', M.fname), 'file')
+ series = feval(sprintf('%s.dynamic_set_auxiliary_series', M.fname), series, M.params);
+end
+
+% selecting observations
+if isfield(options, 'nobs')
+ nobs = options.nobs;
+else
+ nobs = 0;
+end
+
+periods = series.dates;
+nobs0 = series.nobs;
+
+first_obs_ispresent = false;
+last_obs_ispresent = false;
+if isfield(options, 'first_obs')
+ i = options.first_obs;
+ if i < 1
+ error([caller, '_FILE: the first requested period is before available', ...
+ ' data.'])
+ elseif i > nobs0
+ error([caller, '_FILE: the first requested period is after available', ...
+ ' data.'])
+ end
+ first_obs = periods(i);
+ if nobs > 0
+ last_obs = first_obs + nobs - 1;
+ last_obs_ispresent = true;
+ end
+ first_obs_ispresent = true;
+elseif isfield(options, 'firstobs')
+ first_obs = options.firstobs;
+ if nobs > 0
+ last_obs = first_obs + nobs - 1;
+ last_obs_ispresent = true;
+ end
+ first_obs_ispresent = true;
+end
+
+if last_obs_ispresent
+ if isfield(options, 'last_obs')
+ i = options.last_obs;
+ if i < 1
+ error([caller, '_FILE: the last requested period is before available', ...
+ ' data.'])
+ elseif i > nobs0
+ error([caller, '_FILE: the last requested period is after available', ...
+ ' data.'])
+ end
+ if last_obs ~= periods(i)
+ error([caller, '_FILE: FIST_OBS, LAST_OBS and NOBS contain', ...
+ ' inconsistent information. Use only two of these', ...
+ ' options.'])
+ end
+ elseif isfield(options, 'lastobs')
+ if last_obs ~= options.lastobs
+ error([caller, '_FILE: FIST_OBS, LAST_OBS and NOBS contain', ...
+ ' inconsistent information. Use only two of these', ...
+ ' options.'])
+ end
+ end
+elseif isfield(options, 'last_obs')
+ i = options.last_obs;
+ if i < 1
+ error([caller, '_FILE: the last requested period is before available', ...
+ ' data.'])
+ elseif i > nobs0
+ error([caller, '_FILE: the last requested period is after available', ...
+ ' data.'])
+ end
+ last_obs = periods(i);
+ if nobs > 0
+ first_obs = last_obs - nobs + 1;
+ first_obs_ispresent = true;
+ end
+ last_obs_ispresent = true;
+elseif isfield(options, 'lastobs')
+ last_obs = options.lastobs;
+ if nobs > 0
+ first_obs = last_obs - nobs + 1;
+ first_obs_ispresent = true;
+ end
+ last_obs_ispresent = true;
+end
+
+if ~first_obs_ispresent
+ first_obs = periods(1);
+end
+
+if ~last_obs_ispresent
+ if nobs > 0
+ last_obs = first_obs + nobs - 1;
+ else
+ last_obs = periods(end);
+ end
+end
+
+if first_obs < series.init
+ error([caller, '_FILE: the first requested period is before available', ...
+ ' data.'])
+elseif last_obs > series.last
+ error([caller, '_FILE: the last requested period is after available', ...
+ ' data.'])
+else
+ series = series(first_obs:last_obs);
+end
+
diff --git a/matlab/initvalf.m b/matlab/initvalf.m
index f301e045fd5a8f927a7adfa62519abecfc034d15..17a5ff54a44de80b902bd3e58afb63ed29e73d6e 100644
--- a/matlab/initvalf.m
+++ b/matlab/initvalf.m
@@ -1,19 +1,18 @@
-function initvalf(fname_)
-% function initvalf(fname_)
+function series = initvalf(M, options)
+% function initvalf(M)
%
-% Reads an initial path from the 'fname_' file for exogenous and endogenous variables
+% handles options for histvalf() and initvalf()
%
% INPUTS
-% fname_: name of the function or file containing the data
+% caller: string, name of calling function
+% M: model structure
+% options: options specific to initivalf
%
% OUTPUTS
-% none
+% series: dseries containing selected data from a file or a dseries
%
-% SPECIAL REQUIREMENTS
-% All variables local to this function have an underscore appended to
-% their name, to minimize clashes with model variables loaded by this function.
-% Copyright (C) 2003-2018 Dynare Team
+% Copyright (C) 2003-2020 Dynare Team
%
% This file is part of Dynare.
%
@@ -30,81 +29,6 @@ function initvalf(fname_)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-global M_ oo_ options_
+series = histvalf_initvalf('INITVALF', M, options);
-series_ = 1;
-[directory,basename,extension] = fileparts(fname_);
-
-% Auto-detect extension if not provided
-if isempty(extension)
- if exist([basename '.m'],'file')
- extension = '.m';
- elseif exist([basename '.mat'],'file')
- extension = '.mat';
- elseif exist([basename '.xls'],'file')
- extension = '.xls';
- elseif exist([basename '.xlsx'],'file')
- extension = '.xlsx';
- else
- error(['Can''t find datafile: ' basename '.{m,mat,xls,xlsx}']);
- end
-end
-
-fullname = [basename extension];
-
-if ~exist(fullname)
- error(['Can''t find datafile: ' fullname ]);
-end
-
-switch (extension)
- case '.m'
- eval(basename);
- case '.mat'
- load(basename);
- case { '.xls', '.xlsx' }
- [data_,names_v_]=xlsread(fullname); % Octave needs the extension explicitly
- series_=0;
- otherwise
- error(['Unsupported extension for datafile: ' extension])
-end
-
-options_.initval_file = true;
-oo_.endo_simul = [];
-oo_.exo_simul = [];
-
-for i_=1:length(M_.endo_names)
- if series_ == 1
- x_ = eval(M_.endo_names{i_});
- if size(x_,2)>size(x_,1) %oo_.endo_simul must be collection of row vectors
- oo_.endo_simul = [oo_.endo_simul; x_];
- else %transpose if column vector
- oo_.endo_simul = [oo_.endo_simul; x_'];
- end
- else
- k_ = strmatch(M_.endo_names{i_}, names_v_, 'exact');
- if isempty(k_)
- error(['INITVAL_FILE: ' M_.endo_names{i_} ' not found'])
- end
- x_ = data_(:,k_);
- oo_.endo_simul = [oo_.endo_simul; x_'];
- end
-end
-
-for i_=1:length(M_.exo_names)
- if series_ == 1
- x_ = eval(M_.exo_names{i_});
- if size(x_,2)>size(x_,1) %oo_.endo_simul must be collection of row vectors
- oo_.exo_simul = [oo_.exo_simul x_'];
- else %if column vector
- oo_.exo_simul = [oo_.exo_simul x_];
- end
- else
- k_ = strmatch(M_.exo_names{i_}, names_v_, 'exact');
- if isempty(k_)
- error(['INITVAL_FILE: ' M_.exo_names{i_} ' not found'])
- end
- x_ = data_(:,k_);
- oo_.exo_simul = [oo_.exo_simul x_];
- end
-end
diff --git a/matlab/perfect-foresight-models/make_ex_.m b/matlab/perfect-foresight-models/make_ex_.m
index 4f72590484e4ee29f34fb652998f8c04792476ca..909ba238db950667f249153934098782c9959071 100644
--- a/matlab/perfect-foresight-models/make_ex_.m
+++ b/matlab/perfect-foresight-models/make_ex_.m
@@ -41,17 +41,33 @@ if M_.exo_det_nbr > 1 && isempty(oo_.exo_det_steady_state)
end
% Initialize oo_.exo_simul
-if isempty(M_.exo_histval)
- if isempty(ex0_)
- oo_.exo_simul = repmat(oo_.exo_steady_state',M_.maximum_lag+options_.periods+M_.maximum_lead,1);
+if isempty(oo_.initval_series)
+ if isempty(M_.exo_histval)
+ if isempty(ex0_)
+ oo_.exo_simul = repmat(oo_.exo_steady_state',M_.maximum_lag+options_.periods+M_.maximum_lead,1);
+ else
+ oo_.exo_simul = [ repmat(ex0_',M_.maximum_lag,1) ; repmat(oo_.exo_steady_state',options_.periods+M_.maximum_lead,1) ];
+ end
else
- oo_.exo_simul = [ repmat(ex0_',M_.maximum_lag,1) ; repmat(oo_.exo_steady_state',options_.periods+M_.maximum_lead,1) ];
+ if isempty(ex0_)
+ oo_.exo_simul = [M_.exo_histval'; repmat(oo_.exo_steady_state',options_.periods+M_.maximum_lead,1)];
+ else
+ error('histval and endval cannot be used simultaneously')
+ end
end
-else
- if isempty(ex0_)
- oo_.exo_simul = [M_.exo_histval'; repmat(oo_.exo_steady_state',options_.periods+M_.maximum_lead,1)];
- else
- error('histval and endval cannot be used simultaneously')
+elseif M_.exo_nbr > 0
+ x = oo_.initval_series{M_.exo_names{:}}.data;
+ oo_.exo_simul = x(1:M_.maximum_lag + options_.periods + M_.maximum_lead,:);
+ if ~isempty(M_.exo_histval)
+ oo_.exo_simul(1:M_.maximum_lag, :) ...
+ = M_.exo_histval(:, 1:M_.maximum_lag)';
+ end
+elseif M_.exo_det_nbr > 0
+ x_det = oo_.initval_series{M_.exo_det_names{:}}.data;
+ oo_.exo_det_simul = x_det(1:M_.maximum_lag + options_.periods + M_.maximum_lead,:);
+ if ~isempty(M_.exo_det_histval)
+ oo_.exo_det_simul(1:M_.maximum_lag, :) ...
+ = M_.exo_det_histval(:, 1:M_.maximum_lag)';
end
end
diff --git a/matlab/perfect-foresight-models/make_y_.m b/matlab/perfect-foresight-models/make_y_.m
index abd48a84f3df6a2fbd81d629bb429ef54d0a5609..d36dd746ca5f8a8423364acd5cdd438a47929bdd 100644
--- a/matlab/perfect-foresight-models/make_y_.m
+++ b/matlab/perfect-foresight-models/make_y_.m
@@ -45,18 +45,31 @@ if isempty(oo_.steady_state)
oo_.steady_state = zeros(M_.endo_nbr,1);
end
-if isempty(M_.endo_histval)
- if isempty(ys0_)
- oo_.endo_simul = repmat(oo_.steady_state, 1, M_.maximum_lag+options_.periods+M_.maximum_lead);
+if isempty(oo_.initval_series)
+ if isempty(M_.endo_histval)
+ if isempty(ys0_)
+ oo_.endo_simul = repmat(oo_.steady_state, 1, M_.maximum_lag+options_.periods+M_.maximum_lead);
+ else
+ oo_.endo_simul = [repmat(ys0_, 1, M_.maximum_lag) repmat(oo_.steady_state, 1,options_.periods+M_.maximum_lead)];
+ end
else
- oo_.endo_simul = [repmat(ys0_, 1, M_.maximum_lag) repmat(oo_.steady_state, 1,options_.periods+M_.maximum_lead)];
+ if ~isempty(ys0_)
+ error('histval and endval cannot be used simultaneously')
+ end
+ % the first NaNs take care of the case where there are lags > 1 on
+ % exogenous variables
+ oo_.endo_simul = [M_.endo_histval ...
+ repmat(oo_.steady_state, 1, options_.periods+M_.maximum_lead)];
end
else
- if ~isempty(ys0_)
- error('histval and endval cannot be used simultaneously')
+ y = oo_.initval_series{M_.endo_names{:}}.data;
+ oo_.endo_simul = y(1:M_.maximum_lag + options_.periods + ...
+ M_.maximum_lead, :)';
+ if ~isempty(M_.endo_histval)
+ if ~isempty(ys0_)
+ error('histval and endval cannot be used simultaneously')
+ end
+ oo_.endo_simul(:,1:M_.maximum_lag) ...
+ = M_.endo_histval(:, 1:M_.maximum_lag);
end
- % the first NaNs take care of the case where there are lags > 1 on
- % exogenous variables
- oo_.endo_simul = [M_.endo_histval ...
- repmat(oo_.steady_state, 1, options_.periods+M_.maximum_lead)];
-end
+end
\ No newline at end of file
diff --git a/matlab/perfect-foresight-models/perfect_foresight_setup.m b/matlab/perfect-foresight-models/perfect_foresight_setup.m
index 45f6f2789dbfa3ac032f57e09ad56e9b8a76eb32..98d8e12fc22f1f66b4cf9de8566865f9eb624466 100644
--- a/matlab/perfect-foresight-models/perfect_foresight_setup.m
+++ b/matlab/perfect-foresight-models/perfect_foresight_setup.m
@@ -64,7 +64,6 @@ if ~isempty(M_.det_shocks) && options_.periods<max([M_.det_shocks.periods])
error('PERFECT_FORESIGHT_SETUP: Please check the declaration of the shocks or increase the value of the periods option.')
end
-if ~options_.initval_file
- oo_ = make_ex_(M_,options_,oo_);
- oo_ = make_y_(M_,options_,oo_);
-end
+oo_ = make_ex_(M_,options_,oo_);
+oo_ = make_y_(M_,options_,oo_);
+
diff --git a/matlab/perfect-foresight-models/sim1.m b/matlab/perfect-foresight-models/sim1.m
index 3bd956c91401d00bb59194e0c3122c56bf897ee2..d37afbf7e272cfc09644cba7cb033fbe09764f8d 100644
--- a/matlab/perfect-foresight-models/sim1.m
+++ b/matlab/perfect-foresight-models/sim1.m
@@ -119,7 +119,9 @@ if options.endogenous_terminal_period
end
if stop
- if any(any(isnan(endogenousvariables))) || any(any(isinf(endogenousvariables)))
+ % initial or terminal observations may contain
+ % harmless NaN or Inf. We test only values computed above
+ if any(any(isnan(y))) || any(any(isinf(y)))
info.status = false;% NaN or Inf occurred
info.error = err;
info.iterations = iter;
diff --git a/matlab/smoother2histval.m b/matlab/smoother2histval.m
index 6e1eb2c437ace4805c80bf2843f18ca7f342d89a..3ef7e438ea76cfa13285a63c267009f45ae04e5a 100644
--- a/matlab/smoother2histval.m
+++ b/matlab/smoother2histval.m
@@ -163,13 +163,15 @@ end
% Initialize outputs
if ~isfield(opts, 'outfile')
% Output to M_.endo_histval
- M_.endo_histval = repmat(oo_.steady_state, 1, M_.maximum_endo_lag);
+ M_.endo_histval = repmat(oo_.steady_state, 1, M_.maximum_lag);
else
% Output to a file
- o = struct();
+ o = dseries();
end
% Handle all endogenous variables to be copied
+data = zeros(M_.orig_maximum_endo_lag, length(invars));
+k = M_.orig_maximum_endo_lag - M_.maximum_endo_lag + 1: M_.orig_maximum_lag
for i = 1:length(invars)
if isempty(strmatch(invars{i}, M_.endo_names))
% Skip exogenous
@@ -177,61 +179,68 @@ for i = 1:length(invars)
end
s = smoothedvars.(invars{i});
j = strmatch(invars{i}, M_.endo_names, 'exact');
- v = s((period-M_.maximum_endo_lag+1):period);% + steady_state(j);
+ v = s((period-M_.orig_maximum_endo_lag+1):period);% + steady_state(j);
if ~isfield(opts, 'outfile')
j = strmatch(outvars{i}, M_.endo_names, 'exact');
if isempty(j)
error(['smoother2histval: output variable ' outvars{i} ' does not exist.'])
else
- M_.endo_histval(j, :) = v;
+ M_.endo_histval(j, :) = v(k);
end
else
- % When saving to a file, x(-1) is in the variable called "x_"
- o.([ outvars{i} '_' ]) = v;
+ data(:, i) = v';
end
end
-
-% Handle auxiliary variables for lags (both on endogenous and exogenous)
-for i = 1:length(M_.aux_vars)
- if ~ ismember(M_.endo_names{M_.aux_vars(i).endo_index},invars)
- if M_.aux_vars(i).type ~= 1 && M_.aux_vars(i).type ~= 3
- continue
- end
- if M_.aux_vars(i).type == 1
- % Endogenous
- orig_var = M_.endo_names{M_.aux_vars(i).orig_index};
- else
- % Exogenous
- orig_var = M_.exo_names{M_.aux_vars(i).orig_index};
- end
- [m, k] = ismember(orig_var, outvars);
- if m
- if ~isempty(strmatch(invars{k}, M_.endo_names))
- s = smoothedvars.(invars{k});
- else
- s = smoothedshocks.(invars{k});
- end
- l = M_.aux_vars(i).orig_lead_lag;
- if period-M_.maximum_endo_lag+1+l < 1
- error('The period that you indicated is too small to construct initial conditions')
- end
- j = M_.aux_vars(i).endo_index;
- v = s((period-M_.maximum_endo_lag+1+l):(period+l)); %+steady_state(j);
- if ~isfield(opts, 'outfile')
- M_.endo_histval(j, :) = v;
- else
- % When saving to a file, x(-2) is in the variable called "x_l2"
- lead_lag = num2str(l);
- lead_lag = regexprep(lead_lag, '-', 'l');
- o.([ orig_var '_' lead_lag ]) = v;
- end
- end
- end
+if isfield(opts, 'outfile')
+ o = dseries(data, '1Y', invars);
end
+% $$$ % Handle auxiliary variables for lags (both on endogenous and exogenous)
+% $$$ for i = 1:length(M_.aux_vars)
+% $$$ if ~ ismember(M_.endo_names{M_.aux_vars(i).endo_index},invars)
+% $$$ if M_.aux_vars(i).type ~= 1 && M_.aux_vars(i).type ~= 3
+% $$$ continue
+% $$$ end
+% $$$ if M_.aux_vars(i).type == 1
+% $$$ % Endogenous
+% $$$ orig_var = M_.endo_names{M_.aux_vars(i).orig_index};
+% $$$ else
+% $$$ % Exogenous
+% $$$ orig_var = M_.exo_names{M_.aux_vars(i).orig_index};
+% $$$ end
+% $$$ [m, k] = ismember(orig_var, outvars);
+% $$$ if m
+% $$$ if ~isempty(strmatch(invars{k}, M_.endo_names))
+% $$$ s = smoothedvars.(invars{k});
+% $$$ else
+% $$$ s = smoothedshocks.(invars{k});
+% $$$ end
+% $$$ l = M_.aux_vars(i).orig_lead_lag;
+% $$$ if period-M_.maximum_endo_lag+1+l < 1
+% $$$ error('The period that you indicated is too small to construct initial conditions')
+% $$$ end
+% $$$ j = M_.aux_vars(i).endo_index;
+% $$$ v = s((period-M_.maximum_endo_lag+1+l):(period+l)); %+steady_state(j);
+% $$$ if ~isfield(opts, 'outfile')
+% $$$ M_.endo_histval(j, :) = v;
+% $$$ else
+% $$$ % When saving to a file, x(-2) is in the variable called "x_l2"
+% $$$ lead_lag = num2str(l);
+% $$$ lead_lag = regexprep(lead_lag, '-', 'l');
+% $$$ o.([ orig_var '_' lead_lag ]) = v;
+% $$$ end
+% $$$ end
+% $$$ end
+% $$$ end
+
% Finalize output
if isfield(opts, 'outfile')
- save(opts.outfile, '-struct', 'o')
+ [dir, fname, ext] = fileparts(opts.outfile);
+ if ~strcmp(ext,'.mat') && ~isempty(ext)
+ error(['smoother2hisvtval: if outfile has an extension, it must ' ...
+ 'be .mat'])
+ end
+ o.save([dir fname]);
end
end
diff --git a/preprocessor b/preprocessor
index a2bea00fee97dd4cdc2db32690e0d492fda2edfb..d05ffde63ece3fa94882be784e0fdf9aa4ec8982 160000
--- a/preprocessor
+++ b/preprocessor
@@ -1 +1 @@
-Subproject commit a2bea00fee97dd4cdc2db32690e0d492fda2edfb
+Subproject commit d05ffde63ece3fa94882be784e0fdf9aa4ec8982
diff --git a/tests/.gitignore b/tests/.gitignore
index 35ff3c844a6594c2531570147ec596d81e02945a..501fbc71d03f0f5e8098101e43bfa26287473633 100644
--- a/tests/.gitignore
+++ b/tests/.gitignore
@@ -25,6 +25,9 @@ wsOct
/run_test_matlab_output.txt
/block_bytecode/ls2003_tmp.mod
+/histval_initval_file/data.csv
+/histval_initval_file/data.xls
+/histval_initval_file/data.xlsx
/partial_information/PItest3aHc0PCLsimModPiYrVarobsAll_PCL*
/partial_information/PItest3aHc0PCLsimModPiYrVarobsCNR_PCL*
@@ -67,10 +70,11 @@ wsOct
!/gsa/ls2003scr_mode.mat
!/gsa/ls2003scr_results.mat
!/gsa/morris/nk_est_data.m
+!/histval_initval_file/histval_initval_file_unit_tests.m
+!/histval_initval_file/ramst_initval_file_data.m
!/identification/as2007/as2007_steadystate.m
!/identification/as2007/G_QT.mat
!/identification/kim/kim2_steadystate.m
-!/initval_file/ramst_initval_file_data.m
!/internals/tests.m
!/k_order_perturbation/run_fs2000kplusplus.m
!/kalman/likelihood/compare_kalman_routines.m
diff --git a/tests/Makefile.am b/tests/Makefile.am
index 39caeb54d2af1545101f00bfcbaca7d2983881a2..6cda69122202b99398c1e12a5f2826d855607be0 100644
--- a/tests/Makefile.am
+++ b/tests/Makefile.am
@@ -104,9 +104,12 @@ MODFILES = \
discretionary_policy/dennis_1.mod \
discretionary_policy/dennis_1_estim.mod \
discretionary_policy/Gali_discretion.mod \
- initval_file/ramst_initval_file.mod \
- initval_file/ramst_datafile.mod \
- ramst_normcdf_and_friends.mod \
+ histval_initval_file/ramst_initval_file.mod \
+ histval_initval_file/ramst_data.mod \
+ histval_initval_file/ramst_datafile.mod \
+ histval_initval_file/sim_exo_lead_lag.mod \
+ histval_initval_file/sim_exo_lead_lag_initvalf.mod \
+ ramst_normcdf_and_friends.mod \
ramst_vec.mod \
example1_varexo_det.mod \
predetermined_variables.mod \
@@ -405,7 +408,8 @@ XFAIL_MODFILES = ramst_xfail.mod \
estimation/tune_mh_jscale/fs2000_1_xfail.mod \
estimation/tune_mh_jscale/fs2000_2_xfail.mod
-MFILES = initval_file/ramst_initval_file_data.m
+MFILES = histval_initval_file/ramst_initval_file_data.m \
+ histval_initval_file_unit_tests.m
# Dependencies
example1_use_dll.m.trs: example1.m.trs
@@ -503,10 +507,15 @@ deterministic_simulations/rbc_det_stack_solve_algo_7_exo_lead.o.trs: determinist
deterministic_simulations/rbc_det_stack_solve_algo_7_exo_lag.m.trs: deterministic_simulations/rbc_det.m.trs
deterministic_simulations/rbc_det_stack_solve_algo_7_exo_lag.o.trs: deterministic_simulations/rbc_det.o.trs
-initval_file/ramst_initval_file.m.trs: initval_file/ramst_initval_file_data.m.tls
-initval_file/ramst_initval_file.o.trs: initval_file/ramst_initval_file_data.o.tls
-initval_file/ramst_datafile.m.trs: initval_file/ramst_initval_file_data.m.tls
-initval_file/ramst_datafile.o.trs: initval_file/ramst_initval_file_data.o.tls
+histval_initval_file/ramst_initval_file.m.trs: histval_initval_file/ramst_initval_file_data.m.tls histval_initval_file/ramst_data.m.trs
+histval_initval_file/ramst_initval_file.o.trs: histval_initval_file/ramst_initval_file_data.o.tls histval_initval_file/ramst_data.o.trs
+histval_initval_file/ramst_datafile.m.trs: histval_initval_file/ramst_initval_file_data.m.tls
+histval_initval_file/ramst_datafile.o.trs: histval_initval_file/ramst_initval_file_data.o.tls
+histval_initval_file/sim_exo_lead_lag_initvalf.m.trs: histval_initval_file/sim_exo_lead_lag.m.trs
+histval_initval_file/sim_exo_lead_lag_initvalf.o.trs: histval_initval_file/sim_exo_lead_lag.o.trs
+histval_initval_file_unit_tests.m.trs: histval_initval_file/ramst_data.m.trs
+histval_initval_file_unit_tests.o.trs: histval_initval_file/ramst_data.o.trs
+
identification/rbc_ident/rbc_ident_varexo_only.m.trs: identification/rbc_ident/rbc_ident_std_as_structural_par.m.trs
identification/rbc_ident/rbc_ident_varexo_only.o.trs: identification/rbc_ident/rbc_ident_std_as_structural_par.o.trs
@@ -782,12 +791,20 @@ o/particle: $(patsubst %.mod, %.o.trs, $(PARTICLEFILES))
# Matlab TRS Files
M_TRS_FILES = $(patsubst %.mod, %.m.trs, $(MODFILES))
-M_TRS_FILES += run_block_byte_tests_matlab.m.trs run_reporting_test_matlab.m.trs run_all_unitary_tests.m.trs
+M_TRS_FILES += run_block_byte_tests_matlab.m.trs \
+ run_reporting_test_matlab.m.trs \
+ run_all_unitary_tests.m.trs \
+ histval_initval_file_unit_tests.m.trs
+
M_XFAIL_TRS_FILES = $(patsubst %.mod, %.m.trs, $(XFAIL_MODFILES))
# Octave TRS Files
O_TRS_FILES = $(patsubst %.mod, %.o.trs, $(MODFILES))
-O_TRS_FILES += run_block_byte_tests_octave.o.trs run_reporting_test_octave.o.trs run_all_unitary_tests.o.trs
+O_TRS_FILES += run_block_byte_tests_octave.o.trs \
+ run_reporting_test_octave.o.trs \
+ run_all_unitary_tests.o.trs \
+ histval_initval_file_unit_tests.o.trs
+
O_XFAIL_TRS_FILES = $(patsubst %.mod, %.o.trs, $(XFAIL_MODFILES))
# Matlab TLS Files
@@ -920,8 +937,12 @@ EXTRA_DIST = \
k_order_perturbation/fs2000k++.mod \
lmmcp/sw-common-header.inc \
lmmcp/sw-common-footer.inc \
- estimation/tune_mh_jscale/fs2000.inc
-
+ estimation/tune_mh_jscale/fs2000.inc \
+ histval_initval_file_unit_tests.m \
+ histval_initval_file/my_assert.m \
+ histval_initval_file/ramst_data.xls \
+ histval_initval_file/ramst_data.xlsx \
+ histval_initval_file/ramst_initval_file_data.m
if ENABLE_MATLAB
check-local: check-matlab
@@ -1073,7 +1094,7 @@ clean-local:
rm -f estimation/test_matrix.mat
- rm -f initval_file/ramst_initval_file_data_col_vec_mat.mat initval_file/ramst_initval_file_data_row_vec_mat.mat initval_file/ramst_initval_file_excel.xls
+ rm -f histval_initval_file/ramst_initval_file_data_col_vec_mat.mat histval_initval_file/ramst_initval_file_data_row_vec_mat.mat histval_initval_file/ramst_initval_file_excel.xls
rm -f loglinear/results_exp_histval.mat loglinear/results_exp.mat
diff --git a/tests/histval_initval_file/my_assert.m b/tests/histval_initval_file/my_assert.m
new file mode 100644
index 0000000000000000000000000000000000000000..2ac132e12d72b0c349f2a35cfd8666bf6f3a11a9
--- /dev/null
+++ b/tests/histval_initval_file/my_assert.m
@@ -0,0 +1,4 @@
+function failed_tests = my_assert(failed_tests, success, test_name)
+if ~success
+ failed_tests = cat(1, test_failed, test_name);
+end
\ No newline at end of file
diff --git a/tests/histval_initval_file/ramst_data.mod b/tests/histval_initval_file/ramst_data.mod
new file mode 100644
index 0000000000000000000000000000000000000000..c65b9fc816cb27a8444cec66fadbdb8f128d6568
--- /dev/null
+++ b/tests/histval_initval_file/ramst_data.mod
@@ -0,0 +1,68 @@
+/* Verify that the “datafile†option of “perfect_foresight_setup†behaves as
+ “initval_file†(see #1663) */
+
+var c k;
+varexo x;
+
+parameters alph gam delt bet aa;
+alph=0.5;
+gam=0.5;
+delt=0.02;
+bet=0.05;
+aa=0.5;
+
+
+model;
+c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
+c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
+end;
+
+initval;
+x = 1;
+k = ((delt+bet)/(1.0*aa*alph))^(1/(alph-1));
+c = aa*k^alph-delt*k;
+end;
+
+steady;
+
+shocks;
+ var x;
+ periods 2;
+ values 1.1;
+end;
+
+perfect_foresight_setup(periods=200);
+perfect_foresight_solver;
+
+fh = fopen('ramst_data.m', 'w');
+fprintf(fh, 'INIT__ = ''1Y'';\n');
+fprintf(fh, 'NAMES__ = {''c'', ''k'', ''x''};\n');
+fprintf(fh, 'TEX__ = {''c'', ''k'', ''x''};\n');
+fprintf(fh, 'c = [');
+fprintf(fh, '%f ', oo_.endo_simul(1,:));
+fprintf(fh, '];\n');
+fprintf(fh, 'k = [');
+fprintf(fh, '%f ', oo_.endo_simul(2,:));
+fprintf(fh, '];\n');
+fprintf(fh, 'x = [');
+fprintf(fh, '%f ', oo_.exo_simul);
+fprintf(fh, '];\n');
+fclose(fh);
+
+INIT__ = '1Y';
+NAMES__ = {'c', 'k', 'x'};
+TEX__ = {'c', 'k', 'x'};
+eval('c = oo_.endo_simul(1,:);');
+eval('k = oo_.endo_simul(2,:);');
+eval('x = oo_.exo_simul'';');
+save('ramst_data.mat', 'INIT__', 'NAMES__', ...
+ 'TEX__', 'c', 'k', 'x');
+
+fh = fopen('ramst_data.csv', 'w');
+fprintf(fh, 'c,k,x\n');
+for i = 1:size(oo_.endo_simul, 2);
+ fprintf(fh, '%f, ', oo_.endo_simul(:, i));
+ fprintf(fh, '%f\n', oo_.exo_simul(i));
+end;
+fclose(fh);
+
diff --git a/tests/histval_initval_file/ramst_data.xls b/tests/histval_initval_file/ramst_data.xls
new file mode 100644
index 0000000000000000000000000000000000000000..050e2166c0db666245d60a99028e4452c68a394d
Binary files /dev/null and b/tests/histval_initval_file/ramst_data.xls differ
diff --git a/tests/histval_initval_file/ramst_data.xlsx b/tests/histval_initval_file/ramst_data.xlsx
new file mode 100644
index 0000000000000000000000000000000000000000..849953eacbb225829a8e34b0440042e1e9f7d238
Binary files /dev/null and b/tests/histval_initval_file/ramst_data.xlsx differ
diff --git a/tests/initval_file/ramst_datafile.mod b/tests/histval_initval_file/ramst_datafile.mod
similarity index 100%
rename from tests/initval_file/ramst_datafile.mod
rename to tests/histval_initval_file/ramst_datafile.mod
diff --git a/tests/histval_initval_file/ramst_histval_file.mod b/tests/histval_initval_file/ramst_histval_file.mod
new file mode 100644
index 0000000000000000000000000000000000000000..8971ba04e0d46fe794aca9ec61c07b4a7b51e4b8
--- /dev/null
+++ b/tests/histval_initval_file/ramst_histval_file.mod
@@ -0,0 +1,96 @@
+/* Test for the histval_file() command. This file needs ramst_histval_data.m. */
+
+var c k;
+varexo x;
+
+parameters alph gam delt bet aa;
+alph=0.5;
+gam=0.5;
+delt=0.02;
+bet=0.05;
+aa=0.5;
+
+
+model;
+c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
+c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
+end;
+
+initval;
+x = 1;
+k = ((delt+bet)/(1.0*aa*alph))^(1/(alph-1));
+c = aa*k^alph-delt*k;
+end;
+
+steady;
+
+histval_file(datafile = 'ramst_histval_data.m');
+perfect_foresight_setup(periods = 200);
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+initval_file(filename = ramst_initval_file_data_row_vec_mat);
+perfect_foresight_setup(periods=200);
+if oo_.exo_simul(2) ~= 1.2
+ error('initval_file problem with exogenous variable');
+end
+if oo_.endo_simul(2, 2) ~= 13
+ error('initval_file option problem with endogenous variable');
+end
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+
+initval_file(datafile = 'ramst_data.m');
+perfect_foresight_setup(periods = 200);
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+initval_file(datafile = 'ramst_data.mat');
+perfect_foresight_setup(periods = 200);
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+initval_file(datafile = 'ramst_data.csv');
+perfect_foresight_setup(periods = 200);
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+initval_file(datafile = 'ramst_data.xlsx');
+perfect_foresight_setup(periods = 200);
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+if ispc;
+ initval_file(datafile = 'ramst_data.cls');
+ perfect_foresight_setup(periods = 200);
+ perfect_foresight_solver;
+ oo_.exo_simul = [];
+ oo_.endo_simul = [];
+
+ if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+ end;
+end;
+
diff --git a/tests/histval_initval_file/ramst_initval_file.mod b/tests/histval_initval_file/ramst_initval_file.mod
new file mode 100644
index 0000000000000000000000000000000000000000..8e72fe7504468eb7ca84ade8584a801c74891de6
--- /dev/null
+++ b/tests/histval_initval_file/ramst_initval_file.mod
@@ -0,0 +1,113 @@
+/* Test for the initval_file() command. This file needs ramst_initval_file_data.m. It should give results similar to those of ramst.mod */
+
+var c k;
+varexo x;
+
+parameters alph gam delt bet aa;
+alph=0.5;
+gam=0.5;
+delt=0.02;
+bet=0.05;
+aa=0.5;
+
+
+model;
+c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
+c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
+end;
+
+initval;
+x = 1;
+k = ((delt+bet)/(1.0*aa*alph))^(1/(alph-1));
+c = aa*k^alph-delt*k;
+end;
+
+steady;
+
+initval_file(filename = ramst_initval_file_data_row_vec_mat);
+perfect_foresight_setup(periods=200);
+if oo_.exo_simul(2) ~= 1.2
+ error('initval_file problem with exogenous variable');
+end
+if oo_.endo_simul(2, 2) ~= 13
+ error('initval_file option problem with endogenous variable');
+end
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+initval_file(filename = ramst_initval_file_data_col_vec_mat);
+
+perfect_foresight_setup(periods=200);
+if oo_.exo_simul(2) ~= 1.2
+ error('initval_file problem with exogenous variable');
+end
+if oo_.endo_simul(2, 2) ~= 13
+ error('initval_file problem with endogenous variable');
+end
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+
+if ispc()
+ initval_file(filename = ramst_initval_file_excel);
+ perfect_foresight_setup(periods=200);
+ perfect_foresight_solver;
+ if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed');
+ end;
+end
+
+initval_file(datafile = 'ramst_data.m');
+perfect_foresight_setup(periods = 200);
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+initval_file(datafile = 'ramst_data.mat');
+perfect_foresight_setup(periods = 200);
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+initval_file(datafile = 'ramst_data.csv');
+perfect_foresight_setup(periods = 200);
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+initval_file(datafile = 'ramst_data.xlsx');
+perfect_foresight_setup(periods = 200);
+perfect_foresight_solver;
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+oo_.exo_simul = [];
+oo_.endo_simul = [];
+
+if ispc;
+ initval_file(datafile = 'ramst_data.cls');
+ perfect_foresight_setup(periods = 200);
+ perfect_foresight_solver;
+ oo_.exo_simul = [];
+ oo_.endo_simul = [];
+
+ if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+ end;
+end;
+
diff --git a/tests/histval_initval_file/ramst_initval_file_data.m b/tests/histval_initval_file/ramst_initval_file_data.m
new file mode 100644
index 0000000000000000000000000000000000000000..cc1914ca12367299d7db18040458f34389e1bb54
--- /dev/null
+++ b/tests/histval_initval_file/ramst_initval_file_data.m
@@ -0,0 +1,14 @@
+x = vertcat([ 1; 1.2 ], repmat(1, 200, 1));
+k = repmat(13, 202, 1);
+c = repmat(1.5, 202, 1);
+save('ramst_initval_file_data_col_vec_mat.mat','c','k','x');
+
+if ispc()
+ xlswrite('ramst_initval_file_excel',[x k c],1,'A2');
+ xlswrite('ramst_initval_file_excel',{'x' 'k' 'c'},1,'A1');
+end
+
+c=c';
+k=k';
+x=x';
+save('ramst_initval_file_data_row_vec_mat.mat','c','k','x');
diff --git a/tests/histval_initval_file/sim_exo_lead_lag.mod b/tests/histval_initval_file/sim_exo_lead_lag.mod
new file mode 100644
index 0000000000000000000000000000000000000000..5a06c1c5cb9b40f8c5419a0e99ccafeeac345890
--- /dev/null
+++ b/tests/histval_initval_file/sim_exo_lead_lag.mod
@@ -0,0 +1,43 @@
+// Uses autonomous system from sim_base.mod, but adds separate system where exogenous variables have several leads and lags
+// Lags and leads on exogenous variables are substituted out by auxiliary variables
+
+var c cmav k z_backward z_forward;
+varexo x;
+
+parameters alph gam delt bet aa;
+alph=0.5;
+gam=0.5;
+delt=0.02;
+bet=0.05;
+aa=0.5;
+
+model;
+ c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
+ c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
+ z_backward=0.1*1+0.9*z_backward(-1) + (x(-4) - 1);
+ z_forward=0.2*1+0.8*z_forward(+1) + (x(+4) - 1);
+ cmav = 0.2*(c(-2) + c(-1) + c + c(+1) + c(+2));
+end;
+
+initval;
+ c = 1.2;
+ cmav = 1.2;
+ k = 12;
+ x = 1; //set x(0), x(-1), x(-2), x(-3)
+ z_backward = 1;
+ z_forward = 1;
+end;
+
+shocks;
+var x; //sets x(+2)
+periods 2;
+values 0.9;
+end;
+
+simul(periods=200);
+
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+
+
diff --git a/tests/histval_initval_file/sim_exo_lead_lag_histvalf.mod b/tests/histval_initval_file/sim_exo_lead_lag_histvalf.mod
new file mode 100644
index 0000000000000000000000000000000000000000..3d9ae12bbc5dcc63b1efdc97a77f66af69404053
--- /dev/null
+++ b/tests/histval_initval_file/sim_exo_lead_lag_histvalf.mod
@@ -0,0 +1,76 @@
+// Uses autonomous system from sim_base.mod, but adds separate system where exogenous variables have several leads and lags
+// Lags and leads on exogenous variables are substituted out by auxiliary variables
+
+var c cmav k z_backward z_forward;
+varexo x;
+
+parameters alph gam delt bet aa;
+alph=0.5;
+gam=0.5;
+delt=0.02;
+bet=0.05;
+aa=0.5;
+
+model;
+ c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
+ c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
+ z_backward=0.1*1+0.9*z_backward(-1) + (x(-4) - 1);
+ z_forward=0.2*1+0.8*z_forward(+1) + (x(+4) - 1);
+ cmav = 0.2*(c(-2) + c(-1) + c + c(+1) + c(+2));
+end;
+
+initval;
+ x = 1;
+end;
+
+steady_state_model;
+ k = ((bet + delt)/(aa*alph*x))^(1/(alph - 1));
+ c = aa*x*k^alph - delt*k;
+ z_backward = x;
+ z_forward = x;
+ cmav = c;
+end;
+
+steady;
+
+shocks;
+ var x;
+ periods 2;
+ values 0.9;
+end;
+
+perfect_foresight_setup(periods=200);
+perfect_foresight_solver;
+
+reference = oo_.endo_simul;
+
+data1 = repmat([oo_.steady_state' 1], 4, 1);
+ds = dseries(data1, '1Y', [M_.endo_names; M_.exo_names]);
+
+histval_file(series = ds);
+perfect_foresight_setup(periods=200);
+perfect_foresight_solver;
+
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed');
+end
+
+if max(max(abs(reference(1:5,5:end) - oo_.endo_simul(1:5,5:end)))) > 1e-8
+ error('Simulation with leads and lags doesn''t match the one with auxiliary variables')
+end
+
+data1 = repmat([oo_.steady_state' 1], 6, 1);
+ds1 = dseries(data1, '1Y', [M_.endo_names; M_.exo_names]);
+
+histval_file(series = ds1, first_obs = 3, last_obs = 6, nobs = 4);
+
+perfect_foresight_setup(periods=200);
+perfect_foresight_solver;
+
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed');
+end
+
+if max(max(abs(reference(1:5,:) - oo_.endo_simul(1:5,:)))) > 1e-8
+ error('Simulation with leads and lags doesn''t match the one with auxiliary variables')
+end
diff --git a/tests/histval_initval_file/sim_exo_lead_lag_initvalf.mod b/tests/histval_initval_file/sim_exo_lead_lag_initvalf.mod
new file mode 100644
index 0000000000000000000000000000000000000000..e74b6c9b27a3721bd0a0ab10330f292b9be7ddaa
--- /dev/null
+++ b/tests/histval_initval_file/sim_exo_lead_lag_initvalf.mod
@@ -0,0 +1,56 @@
+// Uses autonomous system from sim_base.mod, but adds separate system where exogenous variables have several leads and lags
+// Lags and leads on exogenous variables are substituted out by auxiliary variables
+
+data1 = repmat([1.2, 1.2, 12, 1, 1, 1], 208, 1);
+data1(6, 6) = 0.9; //shock to x in period 2
+ds = dseries(data1, '1Y', {'c', 'cmav', 'k', 'z_backward', 'z_forward', 'x'});
+
+var c cmav k z_backward z_forward;
+varexo x;
+
+parameters alph gam delt bet aa;
+alph=0.5;
+gam=0.5;
+delt=0.02;
+bet=0.05;
+aa=0.5;
+
+model;
+ c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
+ c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
+ z_backward=0.1*1+0.9*z_backward(-1) + (x(-4) - 1);
+ z_forward=0.2*1+0.8*z_forward(+1) + (x(+4) - 1);
+ cmav = 0.2*(c(-2) + c(-1) + c + c(+1) + c(+2));
+end;
+
+initval_file(series = ds);
+
+perfect_foresight_setup(periods=200);
+perfect_foresight_solver(maxit=100);
+
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed');
+end
+
+base_results=load('sim_exo_lead_lag_results.mat');
+if max(max(abs(base_results.oo_.endo_simul(1:5,:) - oo_.endo_simul(1:5,:)))) > 1e-8
+ error('Simulation with leads and lags doesn''t match the one with auxiliary variables')
+end
+
+data1 = repmat([1.2, 1.2, 12, 1, 1, 1], 212, 1);
+data1(8, 6) = 0.9; //shock to x in period 2
+ds1 = dseries(data1, '1Y', {'c', 'cmav', 'k', 'z_backward', 'z_forward', 'x'});
+
+initval_file(series = ds1, first_obs = 3, last_obs = 210, nobs = 208);
+
+perfect_foresight_setup(periods=200);
+perfect_foresight_solver(maxit=100);
+
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed');
+end
+
+base_results=load('sim_exo_lead_lag_results.mat');
+if max(max(abs(base_results.oo_.endo_simul(1:5,:) - oo_.endo_simul(1:5,:)))) > 1e-8
+ error('Simulation with leads and lags doesn''t match the one with auxiliary variables')
+end
diff --git a/tests/histval_initval_file/sim_histvalf_stoch_simul.mod b/tests/histval_initval_file/sim_histvalf_stoch_simul.mod
new file mode 100644
index 0000000000000000000000000000000000000000..924a5f0029a907b94f6522f2c925efc4ba5a9150
--- /dev/null
+++ b/tests/histval_initval_file/sim_histvalf_stoch_simul.mod
@@ -0,0 +1,86 @@
+// Uses autonomous system from sim_base.mod, but adds separate system where exogenous variables have several leads and lags
+// Lags and leads on exogenous variables are substituted out by auxiliary variables
+
+var c cmav k z_backward z_forward;
+varexo x;
+
+parameters alph gam delt bet aa;
+alph=0.5;
+gam=0.5;
+delt=0.02;
+bet=0.05;
+aa=0.5;
+
+model;
+ c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
+ c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
+ z_backward=0.1*1+0.9*z_backward(-1) + (x(-4) - 1);
+ z_forward=0.2*1+0.8*z_forward(+1) + (x(+4) - 1);
+ cmav = 0.2*(c(-2) + c(-1) + c + c(+1) + c(+2));
+end;
+
+initval;
+ x = 1;
+end;
+
+steady_state_model;
+ k = ((bet + delt)/(aa*alph*x))^(1/(alph - 1));
+ c = aa*x*k^alph - delt*k;
+ z_backward = x;
+ z_forward = x;
+ cmav = c;
+end;
+
+steady;
+
+shocks;
+ var x;
+ stderr 0.01;
+end;
+
+s = rng;
+stoch_simul(periods=20, drop=0, irf=0);
+
+reference = oo_.endo_simul;
+
+data1 = repmat([oo_.steady_state' 1], 4, 1);
+ds = dseries(data1, '1Y', [M_.endo_names; M_.exo_names]);
+
+histval_file(series = ds);
+
+rng(s);
+stoch_simul(periods=20, drop=0, irf=0);
+
+if max(max(abs(reference(1:5,5:end) - oo_.endo_simul(1:5,5:end)))) > 1e-8
+ error('Simulation with leads and lags doesn''t match the reference')
+end
+
+data1 = repmat([oo_.steady_state' 1], 6, 1);
+ds1 = dseries(data1, '1Y', [M_.endo_names; M_.exo_names]);
+
+histval_file(series = ds1, first_obs = 6, last_obs = 6, nobs = 1);
+
+rng(s);
+stoch_simul(periods=20, drop=0, irf=0);
+
+if max(max(abs(reference(1:5,:) - oo_.endo_simul(1:5,:)))) > 1e-8
+ error('Simulation with leads and lags doesn''t match the reference')
+end
+
+histval_file(series = ds1, first_simulation_period = 7);
+
+rng(s);
+stoch_simul(periods=20, drop=0, irf=0);
+
+if max(max(abs(reference(1:5,:) - oo_.endo_simul(1:5,:)))) > 1e-8
+ error('Simulation with leads and lags doesn''t match the reference')
+end
+
+histval_file(series = ds1, first_simulation_period = 7Y);
+
+rng(s);
+stoch_simul(periods=20, drop=0, irf=0);
+
+if max(max(abs(reference(1:5,:) - oo_.endo_simul(1:5,:)))) > 1e-8
+ error('Simulation with leads and lags doesn''t match the reference')
+end
diff --git a/tests/histval_initval_file_unit_tests.m b/tests/histval_initval_file_unit_tests.m
new file mode 100644
index 0000000000000000000000000000000000000000..4b81f71de5588fd15d26a2a42b4cf78f6d1aaa52
--- /dev/null
+++ b/tests/histval_initval_file_unit_tests.m
@@ -0,0 +1,220 @@
+top_test_dir = getenv('TOP_TEST_DIR');
+addpath([top_test_dir filesep '..' filesep 'matlab/']);
+dynare_config;
+
+cd('histval_initval_file');
+num_tests = 0;
+failed_tests = {};
+
+ds = dseries(randn(10,4));
+
+M = struct();
+M.fname = '';
+M.endo_nbr = 3;
+M.orig_endo_nbr = 3;
+M.endo_names = {'Variable_1','Variable_2','Variable_3'};
+M.exo_nbr = 1;
+M.exo_names = {'Variable_4'};
+M.exo_det_nbr = 0;
+
+caller = 'INITVAL';
+
+options = struct();
+options.series = ds;
+ds1 = histvalf_initvalf(caller, M, options);
+
+failed_tests = my_assert(failed_tests, all(all(ds1 == ds)), 'basic test');
+num_tests = num_tests + 1;
+
+options = struct();
+options.series = ds;
+options.first_obs = 2;
+ds1 = histvalf_initvalf(caller, M, options);
+failed_tests = my_assert(failed_tests, ds1.init == dates('2Y'), ...
+ 'init test 1');
+num_tests = num_tests + 1;
+
+options = struct();
+options.series = ds;
+options.first_obs = 2;
+options.last_obs = 9;
+ds1 = histvalf_initvalf(caller, M, options);
+failed_tests = my_assert(failed_tests, ds1.init == dates('2Y'), ...
+ 'first_obs last_obs test 1');
+failed_tests = my_assert(failed_tests, ds1.last == dates('9Y'), ...
+ 'first_obs last_obs test 2');
+num_tests = num_tests + 2;
+
+options = struct();
+options.series = ds;
+options.last_obs = 9;
+ds1 = histvalf_initvalf(caller, M, options);
+failed_tests = my_assert(failed_tests, ds1.init == dates('1Y'), ...
+ 'last_obs test 1');
+failed_tests = my_assert(failed_tests, ds1.last == dates('9Y'), ...
+ 'last_obs test 2');
+num_tests = num_tests + 2;
+
+options = struct();
+options.series = ds;
+options.first_obs = 2;
+options.last_obs = 9;
+options.nobs = 8;
+ds1 = histvalf_initvalf(caller, M, options);
+failed_tests = my_assert(failed_tests, ds1.init == dates('2Y'), ...
+ 'first_obs, last_obs, nobs test 1');
+failed_tests = my_assert(failed_tests, ds1.last == dates('9Y'), ...
+ 'first_obs, last_obs, nobs test 2');
+num_tests = num_tests + 2;
+
+options = struct();
+options.series = ds;
+options.last_obs = 9;
+options.nobs = 8;
+ds1 = histvalf_initvalf(caller, M, options);
+failed_tests = my_assert(failed_tests, ds1.init == dates('2Y'), ...
+ 'last_obs, nobs test 1');
+failed_tests = my_assert(failed_tests, ds1.last == dates('9Y'), ...
+ 'last_obs, nobs test 2');
+num_tests = num_tests + 2;
+
+options = struct();
+options.series = ds;
+options.first_obs = 2;
+options.last_obs = 9;
+options.nobs = 7;
+
+try
+ ds1 = histvalf_initvalf(caller, M, options);
+ error('This test didn''t catch the error')
+catch me
+ if strcmp(me.message, ['INITVAL_FILE: FIST_OBS, LAST_OBS and NOBS contain', ...
+ ' inconsistent information. Use only two of these', ...
+ ' options.']) == false
+ failed_tests = cat(1, failed_tests, 'Wrong nobs error message' );
+ end
+end
+num_tests = num_tests + 1;
+
+options = struct();
+options.series = ds;
+options.first_obs = -1;
+
+try
+ ds1 = histvalf_initvalf(caller, M, options);
+ error('This test didn''t catch the error')
+catch me
+ if strcmp(me.message, [caller, '_FILE: the first requested period is', ...
+ ' before available data.']) == false
+ failed_tests = cat(1, failed_tests, ...
+ 'Wrong first period error message');
+ end
+end
+num_tests = num_tests + 1;
+
+options = struct();
+options.series = ds;
+options.last_obs = 11;
+
+try
+ ds1 = histvalf_initvalf(caller, M, options);
+ error('This test didn''t catch the error')
+catch me
+ if strcmp(me.message, [caller, '_FILE: the last requested period is', ...
+ ' after available data.']) == false
+ failed_tests = cat(1, failed_tests, ...
+ 'Wrong last period error message');
+ end
+end
+num_tests = num_tests + 1;
+
+fh = fopen('data.m', 'w');
+init__ = 'INIT__ = ''1Y'';';
+fprintf(fh, [init__ '\n']);
+eval(init__);
+names__ = 'NAMES__ = {''x'', ''y''};';
+fprintf(fh, [names__ '\n']);
+eval(names__);
+tex__ = 'TEX__ = {''x'', ''y''};';
+fprintf(fh, [tex__ '\n']);
+eval(tex__);
+x = randn(10, 1);
+fprintf(fh, 'x = [');
+fprintf(fh, '%f ', x);
+fprintf(fh, '];\n');
+y = randn(10, 1);
+fprintf(fh, 'y = [');
+fprintf(fh, '%f ', y);
+fprintf(fh, '];\n');
+fclose(fh);
+
+M.endo_nbr = 1;
+M.orig_endo_nbr = 1;
+M.endo_names = {'y'};
+M.exo_nbr = 1;
+M.exo_names = {'x'};
+M.exo_det_nbr = 0;
+
+options = struct();
+options.datafile = 'data.m';
+series = histvalf_initvalf('INITVAL_FILE', M, options);
+failed_tests = my_assert(failed_tests, series.init == dates('1Y'), ...
+ '*.m file first_obs test');
+failed_tests = my_assert(failed_tests, series.nobs == 10, ...
+ '*.m file nobs test');
+
+save('data.mat', 'INIT__', 'NAMES__', 'TEX__', 'x', 'y');
+options = struct();
+options.datafile = 'data.mat';
+series = histvalf_initvalf('INITVAL_FILE', M, options);
+failed_tests = my_assert(failed_tests, series.init == dates('1Y'), ...
+ '*.mat file first_obs test');
+failed_tests = my_assert(failed_tests, series.nobs == 10, ...
+ '*.mat file nobs test');
+
+fh = fopen('data.csv', 'w');
+fprintf(fh, 'x,y\n');
+for i = 1:size(x,1)
+ fprintf(fh, '%f,%f\n', x(i), y(i));
+end
+fclose(fh);
+
+if ~verLessThan('matlab', '8.2')
+ writetable(table(x,y), 'data.xlsx')
+ options = struct();
+ options.datafile = 'data.xlsx';
+ series = histvalf_initvalf('INITVAL_FILE', M, options);
+ failed_tests = my_assert(failed_tests, series.init == dates('1Y'), ...
+ '*.xlsx file first_obs test');
+ failed_tests = my_assert(failed_tests, series.nobs == 10, ...
+ '*.xlsx file nobs test');
+ num_tests = num_tests + 2;
+
+ if ispc
+ writetable(table(x,y), 'data.xls')
+ options = struct();
+ options.datafile = 'data.xls';
+ series = histvalf_initvalf('INITVAL_FILE', M, options);
+ failed_tests = my_assert(failed_tests, series.init == dates('1Y'), ...
+ '*.xls file first_obs test');
+ failed_tests = my_assert(failed_tests, series.nobs == 10, ...
+ '*.xls file nobs test');
+ num_tests = num_tests + 2;
+ end
+end
+
+cd(getenv('TOP_TEST_DIR'));
+fid = fopen('histval_initval_file_unit_tests.m.trs', 'w+');
+num_failed_tests = length(failed_tests)
+if num_failed_tests > 0
+ fprintf(fid,':test-result: FAIL\n');
+ fprintf(fid,':number-tests: %d\n', num_tests);
+ fprintf(fid,':number-failed-tests: %d\n', num_failed_tests);
+ fprintf(fid,':list-of-failed-tests: %s\n', failed_tests{:});
+else
+ fprintf(fid,':test-result: PASS\n');
+ fprintf(fid,':number-tests: %d\n', num_tests);
+ fprintf(fid,':number-failed-tests: 0\n');
+end
+fclose(fid);
+exit;
diff --git a/tests/initval_file/ramst_initval_file.mod b/tests/initval_file/ramst_initval_file.mod
deleted file mode 100644
index 2cc8f91ed9f9cd5efaf80a762bf9c1ec03c080ee..0000000000000000000000000000000000000000
--- a/tests/initval_file/ramst_initval_file.mod
+++ /dev/null
@@ -1,55 +0,0 @@
-/* Test for the initval_file() command. This file needs ramst_initval_file_data.m. It should give results similar to those of ramst.mod */
-
-var c k;
-varexo x;
-
-parameters alph gam delt bet aa;
-alph=0.5;
-gam=0.5;
-delt=0.02;
-bet=0.05;
-aa=0.5;
-
-
-model;
-c + k - aa*x*k(-1)^alph - (1-delt)*k(-1);
-c^(-gam) - (1+bet)^(-1)*(aa*alph*x(+1)*k^(alph-1) + 1 - delt)*c(+1)^(-gam);
-end;
-
-initval;
-x = 1;
-k = ((delt+bet)/(1.0*aa*alph))^(1/(alph-1));
-c = aa*k^alph-delt*k;
-end;
-
-steady;
-
-initval_file(filename = ramst_initval_file_data_row_vec_mat);
-if oo_.exo_simul(2) ~= 1.2
- error('initval_file problem with exogenous variable');
-end
-if oo_.endo_simul(2, 2) ~= 13
- error('initval_file option problem with endogenous variable');
-end
-perfect_foresight_setup(periods=200);
-perfect_foresight_solver;
-
-oo_.exo_simul = [];
-oo_.endo_simul = [];
-
-initval_file(filename = ramst_initval_file_data_col_vec_mat);
-if oo_.exo_simul(2) ~= 1.2
- error('initval_file problem with exogenous variable');
-end
-if oo_.endo_simul(2, 2) ~= 13
- error('initval_file problem with endogenous variable');
-end
-
-perfect_foresight_setup(periods=200);
-perfect_foresight_solver;
-
-if ispc()
- initval_file(filename = ramst_initval_file_excel);
- perfect_foresight_setup(periods=200);
- perfect_foresight_solver;
-end
diff --git a/tests/smoother2histval/fs2000_simul.mod b/tests/smoother2histval/fs2000_simul.mod
index eb65974e1df9074f25372afdc4ce0f09cd88573a..a682c76c04bbcbb957740d652c13bf2b366a7eb4 100644
--- a/tests/smoother2histval/fs2000_simul.mod
+++ b/tests/smoother2histval/fs2000_simul.mod
@@ -66,6 +66,10 @@ results_estimation=load('fs2000_smooth_results');
M_.params=results_estimation.M_.params;
steady;
+OO = load('fs2000_smooth_results.mat');
+M_.params = OO.M_.params;
+
histval_file(filename = 'fs2000_histval.mat');
-simul(periods = 30);
+perfect_foresight_setup(periods = 100);
+perfect_foresight_solver;
diff --git a/tests/smoother2histval/fs2000_smooth.mod b/tests/smoother2histval/fs2000_smooth.mod
index 89447eb57142ae3933b3fc66d92631f63b381210..65bb15b68bcd07d5e6f96aafa18657958a09a13d 100644
--- a/tests/smoother2histval/fs2000_smooth.mod
+++ b/tests/smoother2histval/fs2000_smooth.mod
@@ -82,6 +82,6 @@ varobs gp_obs gy_obs;
options_.solve_tolf = 1e-12;
-estimation(order=1,datafile=fsdat_simul,nobs=192,mh_replic=1500,mh_nblocks=1,mh_jscale=0.8,smoother,consider_all_endogenous);
+estimation(order=1,datafile=fsdat_simul,mh_replic=1500,mh_nblocks=1,mh_jscale=0.8,smoother,consider_all_endogenous);
smoother2histval(period = 5, outfile = 'fs2000_histval.mat');