1478 lines
62 KiB
C++
1478 lines
62 KiB
C++
/*
|
|
* Copyright © 2006-2021 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 <https://www.gnu.org/licenses/>.
|
|
*/
|
|
|
|
#include <cstdlib>
|
|
#include <iostream>
|
|
#include <fstream>
|
|
#include <typeinfo>
|
|
#include <cassert>
|
|
#include <random>
|
|
|
|
#include <filesystem>
|
|
|
|
#include "ModFile.hh"
|
|
#include "ConfigFile.hh"
|
|
#include "ComputingTasks.hh"
|
|
#include "Shocks.hh"
|
|
|
|
ModFile::ModFile(WarningConsolidation &warnings_arg)
|
|
: var_model_table{symbol_table},
|
|
trend_component_model_table{symbol_table},
|
|
expressions_tree{symbol_table, num_constants, external_functions_table},
|
|
original_model{symbol_table, num_constants, external_functions_table,
|
|
trend_component_model_table, var_model_table},
|
|
dynamic_model{symbol_table, num_constants, external_functions_table,
|
|
trend_component_model_table, var_model_table},
|
|
trend_dynamic_model{symbol_table, num_constants, external_functions_table,
|
|
trend_component_model_table, var_model_table},
|
|
ramsey_FOC_equations_dynamic_model{symbol_table, num_constants, external_functions_table,
|
|
trend_component_model_table, var_model_table},
|
|
orig_ramsey_dynamic_model{symbol_table, num_constants, external_functions_table,
|
|
trend_component_model_table, var_model_table},
|
|
epilogue{symbol_table, num_constants, external_functions_table,
|
|
trend_component_model_table, var_model_table},
|
|
static_model{symbol_table, num_constants, external_functions_table},
|
|
steady_state_model{symbol_table, num_constants, external_functions_table, static_model},
|
|
warnings{warnings_arg}
|
|
{
|
|
}
|
|
|
|
void
|
|
ModFile::evalAllExpressions(bool warn_uninit)
|
|
{
|
|
cout << "Evaluating expressions...";
|
|
|
|
// Loop over all statements, and fill global eval context if relevant
|
|
for (auto &st : statements)
|
|
{
|
|
if (auto ips = dynamic_cast<InitParamStatement *>(st.get()); ips)
|
|
ips->fillEvalContext(global_eval_context);
|
|
|
|
if (auto ies = dynamic_cast<InitOrEndValStatement *>(st.get()); ies)
|
|
ies->fillEvalContext(global_eval_context);
|
|
|
|
if (auto lpass = dynamic_cast<LoadParamsAndSteadyStateStatement *>(st.get()); lpass)
|
|
lpass->fillEvalContext(global_eval_context);
|
|
}
|
|
|
|
// Evaluate model local variables
|
|
dynamic_model.fillEvalContext(global_eval_context);
|
|
|
|
cout << "done" << endl;
|
|
|
|
// Check if some symbols are not initialized, and give them a zero value then
|
|
for (int id = 0; id <= symbol_table.maxID(); id++)
|
|
if (auto type = symbol_table.getType(id);
|
|
(type == SymbolType::endogenous || type == SymbolType::exogenous || type == SymbolType::exogenousDet
|
|
|| type == SymbolType::parameter || type == SymbolType::modelLocalVariable)
|
|
&& global_eval_context.find(id) == global_eval_context.end())
|
|
{
|
|
if (warn_uninit)
|
|
warnings << "WARNING: Can't find a numeric initial value for "
|
|
<< symbol_table.getName(id) << ", using zero" << endl;
|
|
global_eval_context[id] = 0;
|
|
}
|
|
}
|
|
|
|
void
|
|
ModFile::addStatement(unique_ptr<Statement> st)
|
|
{
|
|
statements.push_back(move(st));
|
|
}
|
|
|
|
void
|
|
ModFile::addStatementAtFront(unique_ptr<Statement> st)
|
|
{
|
|
statements.insert(statements.begin(), move(st));
|
|
}
|
|
|
|
void
|
|
ModFile::checkPass(bool nostrict, bool stochastic)
|
|
{
|
|
for (auto &statement : statements)
|
|
statement->checkPass(mod_file_struct, warnings);
|
|
|
|
// Check the steady state block
|
|
steady_state_model.checkPass(mod_file_struct, warnings);
|
|
|
|
// Check epilogue block
|
|
epilogue.checkPass(mod_file_struct, warnings);
|
|
|
|
if (mod_file_struct.write_latex_steady_state_model_present
|
|
&& !mod_file_struct.steady_state_model_present)
|
|
{
|
|
cerr << "ERROR: You cannot have a write_latex_steady_state_model statement without a steady_state_model block." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
// If order option has not been set, default to 2
|
|
if (!mod_file_struct.order_option)
|
|
mod_file_struct.order_option = 2;
|
|
|
|
param_used_with_lead_lag = dynamic_model.ParamUsedWithLeadLag();
|
|
if (param_used_with_lead_lag)
|
|
warnings << "WARNING: A parameter was used with a lead or a lag in the model block" << endl;
|
|
|
|
bool stochastic_statement_present = mod_file_struct.stoch_simul_present
|
|
|| mod_file_struct.estimation_present
|
|
|| mod_file_struct.osr_present
|
|
|| mod_file_struct.ramsey_policy_present
|
|
|| mod_file_struct.discretionary_policy_present
|
|
|| mod_file_struct.calib_smoother_present
|
|
|| mod_file_struct.identification_present
|
|
|| mod_file_struct.mom_estimation_present
|
|
|| mod_file_struct.sensitivity_present
|
|
|| stochastic;
|
|
|
|
// Allow empty model only when doing a standalone BVAR estimation
|
|
if (dynamic_model.equation_number() == 0
|
|
&& (mod_file_struct.check_present
|
|
|| mod_file_struct.perfect_foresight_solver_present
|
|
|| stochastic_statement_present))
|
|
{
|
|
cerr << "ERROR: At least one model equation must be declared!" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if ((mod_file_struct.ramsey_model_present || mod_file_struct.ramsey_policy_present)
|
|
&& mod_file_struct.discretionary_policy_present)
|
|
{
|
|
cerr << "ERROR: You cannot use the discretionary_policy command when you use either ramsey_model or ramsey_policy and vice versa" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (((mod_file_struct.ramsey_model_present || mod_file_struct.discretionary_policy_present)
|
|
&& !mod_file_struct.planner_objective_present)
|
|
|| (!(mod_file_struct.ramsey_model_present || mod_file_struct.discretionary_policy_present)
|
|
&& mod_file_struct.planner_objective_present))
|
|
{
|
|
cerr << "ERROR: A planner_objective statement must be used with a ramsey_model, a ramsey_policy or a discretionary_policy statement and vice versa." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if ((mod_file_struct.osr_present && (!mod_file_struct.osr_params_present || !mod_file_struct.optim_weights_present))
|
|
|| ((!mod_file_struct.osr_present || !mod_file_struct.osr_params_present) && mod_file_struct.optim_weights_present)
|
|
|| ((!mod_file_struct.osr_present || !mod_file_struct.optim_weights_present) && mod_file_struct.osr_params_present))
|
|
{
|
|
cerr << "ERROR: The osr statement must be used with osr_params and optim_weights." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (mod_file_struct.perfect_foresight_solver_present && stochastic_statement_present)
|
|
{
|
|
cerr << "ERROR: A .mod file cannot contain both one of {perfect_foresight_solver,simul} and one of {stoch_simul, estimation, osr, ramsey_policy, discretionary_policy}. This is not possible: one cannot mix perfect foresight context with stochastic context in the same file." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (mod_file_struct.k_order_solver && bytecode)
|
|
{
|
|
cerr << "ERROR: 'k_order_solver' (which is implicit if order >= 3), is not yet compatible with 'bytecode'." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (use_dll && bytecode)
|
|
{
|
|
cerr << "ERROR: In 'model' block, 'use_dll' option is not compatible with 'bytecode'" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if ((stochastic_statement_present || mod_file_struct.check_present || mod_file_struct.steady_present) && no_static)
|
|
{
|
|
cerr << "ERROR: no_static option is incompatible with stoch_simul, estimation, osr, ramsey_policy, discretionary_policy, steady and check commands" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (mod_file_struct.dsge_var_estimated && !mod_file_struct.dsge_prior_weight_in_estimated_params)
|
|
{
|
|
cerr << "ERROR: When estimating a DSGE-VAR model and estimating the weight of the prior, dsge_prior_weight must "
|
|
<< "be referenced in the estimated_params block." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (symbol_table.exists("dsge_prior_weight"))
|
|
{
|
|
if (symbol_table.getType("dsge_prior_weight") != SymbolType::parameter)
|
|
{
|
|
cerr << "ERROR: dsge_prior_weight may only be used as a parameter." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
else
|
|
warnings << "WARNING: When estimating a DSGE-Var, declaring dsge_prior_weight as a "
|
|
<< "parameter is deprecated. The preferred method is to do this via "
|
|
<< "the dsge_var option in the estimation statement." << endl;
|
|
|
|
if (mod_file_struct.dsge_var_estimated || !mod_file_struct.dsge_var_calibrated.empty())
|
|
{
|
|
cerr << "ERROR: dsge_prior_weight can either be declared as a parameter (deprecated) or via the dsge_var option "
|
|
<< "to the estimation statement (preferred), but not both." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (!mod_file_struct.dsge_prior_weight_initialized && !mod_file_struct.dsge_prior_weight_in_estimated_params)
|
|
{
|
|
cerr << "ERROR: If dsge_prior_weight is declared as a parameter, it must either be initialized or placed in the "
|
|
<< "estimated_params block." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (mod_file_struct.dsge_prior_weight_initialized && mod_file_struct.dsge_prior_weight_in_estimated_params)
|
|
{
|
|
cerr << "ERROR: dsge_prior_weight cannot be both initialized and estimated." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
|
|
if (mod_file_struct.dsge_prior_weight_in_estimated_params)
|
|
if (!mod_file_struct.dsge_var_estimated && !mod_file_struct.dsge_var_calibrated.empty())
|
|
{
|
|
cerr << "ERROR: If dsge_prior_weight is in the estimated_params block, the prior weight cannot be calibrated "
|
|
<< "via the dsge_var option in the estimation statement." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
else if (!mod_file_struct.dsge_var_estimated && !symbol_table.exists("dsge_prior_weight"))
|
|
{
|
|
cerr << "ERROR: If dsge_prior_weight is in the estimated_params block, it must either be declared as a parameter "
|
|
<< "(deprecated) or the dsge_var option must be passed to the estimation statement (preferred)." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (dynamic_model.staticOnlyEquationsNbr() != dynamic_model.dynamicOnlyEquationsNbr())
|
|
{
|
|
cerr << "ERROR: the number of equations marked [static] must be equal to the number of equations marked [dynamic]" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (dynamic_model.staticOnlyEquationsNbr() > 0
|
|
&& (mod_file_struct.ramsey_model_present || mod_file_struct.discretionary_policy_present))
|
|
{
|
|
cerr << "ERROR: marking equations as [static] or [dynamic] is not possible with ramsey_model, ramsey_policy or discretionary_policy" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (stochastic_statement_present
|
|
&& (dynamic_model.isUnaryOpUsed(UnaryOpcode::sign)
|
|
|| dynamic_model.isUnaryOpUsed(UnaryOpcode::abs)
|
|
|| dynamic_model.isBinaryOpUsed(BinaryOpcode::max)
|
|
|| dynamic_model.isBinaryOpUsed(BinaryOpcode::min)
|
|
|| dynamic_model.isBinaryOpUsed(BinaryOpcode::greater)
|
|
|| dynamic_model.isBinaryOpUsed(BinaryOpcode::less)
|
|
|| dynamic_model.isBinaryOpUsed(BinaryOpcode::greaterEqual)
|
|
|| dynamic_model.isBinaryOpUsed(BinaryOpcode::lessEqual)
|
|
|| dynamic_model.isBinaryOpUsed(BinaryOpcode::equalEqual)
|
|
|| dynamic_model.isBinaryOpUsed(BinaryOpcode::different)))
|
|
warnings << R"(WARNING: you are using a function (max, min, abs, sign) or an operator (<, >, <=, >=, ==, !=) which is unsuitable for a stochastic context; see the reference manual, section about "Expressions", for more details.)" << endl;
|
|
|
|
if (linear
|
|
&& (dynamic_model.isUnaryOpUsedOnType(SymbolType::endogenous, UnaryOpcode::sign)
|
|
|| dynamic_model.isUnaryOpUsedOnType(SymbolType::endogenous, UnaryOpcode::abs)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::endogenous, BinaryOpcode::max)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::endogenous, BinaryOpcode::min)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::endogenous, BinaryOpcode::greater)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::endogenous, BinaryOpcode::less)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::endogenous, BinaryOpcode::greaterEqual)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::endogenous, BinaryOpcode::lessEqual)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::endogenous, BinaryOpcode::equalEqual)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::endogenous, BinaryOpcode::different)))
|
|
{
|
|
cerr << "ERROR: you have declared your model 'linear' but you are using a function "
|
|
<< "(max, min, abs, sign) or an operator (<, >, <=, >=, ==, !=) on an "
|
|
<< "endogenous variable." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (linear
|
|
&& !mod_file_struct.perfect_foresight_solver_present
|
|
&& (dynamic_model.isUnaryOpUsedOnType(SymbolType::exogenous, UnaryOpcode::sign)
|
|
|| dynamic_model.isUnaryOpUsedOnType(SymbolType::exogenous, UnaryOpcode::abs)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::exogenous, BinaryOpcode::max)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::exogenous, BinaryOpcode::min)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::exogenous, BinaryOpcode::greater)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::exogenous, BinaryOpcode::less)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::exogenous, BinaryOpcode::greaterEqual)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::exogenous, BinaryOpcode::lessEqual)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::exogenous, BinaryOpcode::equalEqual)
|
|
|| dynamic_model.isBinaryOpUsedOnType(SymbolType::exogenous, BinaryOpcode::different)))
|
|
{
|
|
cerr << "ERROR: you have declared your model 'linear' but you are using a function "
|
|
<< "(max, min, abs, sign) or an operator (<, >, <=, >=, ==, !=) on an "
|
|
<< "exogenous variable in a non-perfect-foresight context." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
// Test if some estimated parameters are used within the values of shocks
|
|
// statements (see issue #469)
|
|
set<int> parameters_intersect;
|
|
set_intersection(mod_file_struct.parameters_within_shocks_values.begin(),
|
|
mod_file_struct.parameters_within_shocks_values.end(),
|
|
mod_file_struct.estimated_parameters.begin(),
|
|
mod_file_struct.estimated_parameters.end(),
|
|
inserter(parameters_intersect, parameters_intersect.begin()));
|
|
if (parameters_intersect.size() > 0)
|
|
{
|
|
cerr << "ERROR: some estimated parameters (";
|
|
for (auto it = parameters_intersect.begin();
|
|
it != parameters_intersect.end();)
|
|
{
|
|
cerr << symbol_table.getName(*it);
|
|
if (++it != parameters_intersect.end())
|
|
cerr << ", ";
|
|
}
|
|
cerr << ") also appear in the expressions defining the variance/covariance matrix of shocks; this is not allowed." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
// Check if some exogenous is not used in the model block, Issue #841
|
|
set<int> unusedExo0 = dynamic_model.findUnusedExogenous();
|
|
set<int> unusedExo;
|
|
set_difference(unusedExo0.begin(), unusedExo0.end(),
|
|
mod_file_struct.pac_params.begin(), mod_file_struct.pac_params.end(),
|
|
inserter(unusedExo, unusedExo.begin()));
|
|
if (unusedExo.size() > 0)
|
|
{
|
|
ostringstream unused_exos;
|
|
for (int it : unusedExo)
|
|
unused_exos << symbol_table.getName(it) << " ";
|
|
|
|
if (nostrict)
|
|
warnings << "WARNING: " << unused_exos.str()
|
|
<< "not used in model block, removed by nostrict command-line option" << endl;
|
|
else
|
|
{
|
|
cerr << "ERROR: " << unused_exos.str() << "not used in model block. To bypass this error, use the `nostrict` option. This may lead to crashes or unexpected behavior." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
|
|
// See dynare#1726
|
|
if ((stochastic_statement_present || mod_file_struct.check_present) && dynamic_model.mfs > 0)
|
|
{
|
|
cerr << "ERROR: mfs > 0 is incompatible with check, stoch_simul, estimation, osr, ramsey_policy, discretionary_policy, calib_smoother, identification, methods_of_moments and sensitivity commands" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
|
|
void
|
|
ModFile::transformPass(bool nostrict, bool stochastic, bool compute_xrefs, bool transform_unary_ops,
|
|
const string &exclude_eqs, const string &include_eqs)
|
|
{
|
|
/* Save the original model (must be done before any model transformations by preprocessor)
|
|
— except substituting out variables which we know are constant (they
|
|
appear in an equation of the form: X = constant)
|
|
— except adl operators which we always want expanded
|
|
— except predetermined variables (which must be handled before the call to
|
|
setLeadsLagsOrig(), see preprocessor#47)
|
|
— except diff operators with a lead which have been expanded by
|
|
DataTree:AddDiff()
|
|
*/
|
|
dynamic_model.includeExcludeEquations(exclude_eqs, true);
|
|
dynamic_model.includeExcludeEquations(include_eqs, false);
|
|
dynamic_model.simplifyEquations();
|
|
dynamic_model.substituteAdl();
|
|
if (symbol_table.predeterminedNbr() > 0)
|
|
dynamic_model.transformPredeterminedVariables();
|
|
dynamic_model.setLeadsLagsOrig();
|
|
original_model = dynamic_model;
|
|
dynamic_model.expandEqTags();
|
|
|
|
// Replace all model-local variables by their expression
|
|
dynamic_model.substituteModelLocalVariables();
|
|
|
|
// Check that all declared endogenous are used in equations
|
|
set<int> unusedEndogs = dynamic_model.findUnusedEndogenous();
|
|
bool unusedEndogsIsErr = !nostrict && !mod_file_struct.bvar_present && unusedEndogs.size();
|
|
for (int unusedEndog : unusedEndogs)
|
|
if (nostrict)
|
|
{
|
|
symbol_table.changeType(unusedEndog, SymbolType::unusedEndogenous);
|
|
warnings << "WARNING: '" << symbol_table.getName(unusedEndog)
|
|
<< "' not used in model block, removed by nostrict command-line option" << endl;
|
|
}
|
|
else if (unusedEndogsIsErr)
|
|
cerr << "Error: " << symbol_table.getName(unusedEndog) << " not used in the model block"<< endl;
|
|
|
|
if (unusedEndogsIsErr)
|
|
exit(EXIT_FAILURE);
|
|
|
|
// Declare endogenous used for PAC model-consistent expectations
|
|
for (auto &statement : statements)
|
|
if (auto pms = dynamic_cast<PacModelStatement *>(statement.get());
|
|
pms)
|
|
{
|
|
if (pms->growth)
|
|
pac_growth.push_back(pms->growth);
|
|
if (pms->aux_model_name.empty())
|
|
dynamic_model.declarePacModelConsistentExpectationEndogs(pms->name);
|
|
}
|
|
|
|
// Get all equation tags associated with VARs and Trend Component Models
|
|
set<string> eqtags;
|
|
for (const auto &it : trend_component_model_table.getEqTags())
|
|
for (auto &it1 : it.second)
|
|
eqtags.insert(it1);
|
|
|
|
for (const auto &it : var_model_table.getEqTags())
|
|
for (auto &it1 : it.second)
|
|
eqtags.insert(it1);
|
|
|
|
// Create auxiliary variables and equations for unary ops
|
|
lag_equivalence_table_t unary_ops_nodes;
|
|
ExprNode::subst_table_t unary_ops_subst_table;
|
|
if (transform_unary_ops)
|
|
tie(unary_ops_nodes, unary_ops_subst_table) = dynamic_model.substituteUnaryOps();
|
|
else
|
|
// substitute only those unary ops that appear in auxiliary model equations
|
|
tie(unary_ops_nodes, unary_ops_subst_table) = dynamic_model.substituteUnaryOps(eqtags);
|
|
|
|
// Create auxiliary variable and equations for Diff operators
|
|
auto [diff_nodes, diff_subst_table] = dynamic_model.substituteDiff(pac_growth);
|
|
|
|
// Fill Trend Component Model Table
|
|
dynamic_model.fillTrendComponentModelTable();
|
|
original_model.fillTrendComponentModelTableFromOrigModel();
|
|
dynamic_model.fillTrendComponentmodelTableAREC(diff_subst_table);
|
|
dynamic_model.fillVarModelTable();
|
|
original_model.fillVarModelTableFromOrigModel();
|
|
|
|
// Pac Model
|
|
int i = 0;
|
|
for (auto &statement : statements)
|
|
if (auto pms = dynamic_cast<PacModelStatement *>(statement.get()); pms)
|
|
{
|
|
if (pms->growth)
|
|
pms->overwriteGrowth(pac_growth.at(i++));
|
|
|
|
int max_lag;
|
|
vector<int> lhs;
|
|
vector<bool> nonstationary;
|
|
string aux_model_type;
|
|
if (trend_component_model_table.isExistingTrendComponentModelName(pms->aux_model_name))
|
|
{
|
|
aux_model_type = "trend_component";
|
|
max_lag = trend_component_model_table.getMaxLag(pms->aux_model_name) + 1;
|
|
lhs = dynamic_model.getUndiffLHSForPac(pms->aux_model_name, diff_subst_table);
|
|
// All lhs variables in a trend component model are nonstationary
|
|
nonstationary.insert(nonstationary.end(), trend_component_model_table.getDiff(pms->aux_model_name).size(), true);
|
|
}
|
|
else if (var_model_table.isExistingVarModelName(pms->aux_model_name))
|
|
{
|
|
aux_model_type = "var";
|
|
max_lag = var_model_table.getMaxLag(pms->aux_model_name);
|
|
lhs = var_model_table.getLhs(pms->aux_model_name);
|
|
// nonstationary variables in a VAR are those that are in diff
|
|
nonstationary = var_model_table.getDiff(pms->aux_model_name);
|
|
}
|
|
else if (pms->aux_model_name.empty())
|
|
max_lag = 0;
|
|
else
|
|
{
|
|
cerr << "Error: aux_model_name not recognized as VAR model or Trend Component model" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
auto eqtag_and_lag = dynamic_model.walkPacParameters(pms->name);
|
|
if (pms->aux_model_name.empty())
|
|
dynamic_model.addPacModelConsistentExpectationEquation(pms->name, symbol_table.getID(pms->discount),
|
|
eqtag_and_lag, diff_subst_table);
|
|
else
|
|
dynamic_model.fillPacModelInfo(pms->name, lhs, max_lag, aux_model_type,
|
|
eqtag_and_lag, nonstationary, pms->growth);
|
|
dynamic_model.substitutePacExpectation(pms->name);
|
|
}
|
|
dynamic_model.checkNoRemainingPacExpectation();
|
|
|
|
dynamic_model.addEquationsForVar();
|
|
|
|
// Create auxiliary vars for Expectation operator
|
|
dynamic_model.substituteExpectation(mod_file_struct.partial_information);
|
|
|
|
if (nonstationary_variables)
|
|
{
|
|
dynamic_model.detrendEquations();
|
|
trend_dynamic_model = dynamic_model;
|
|
dynamic_model.removeTrendVariableFromEquations();
|
|
const auto &trend_symbols = dynamic_model.getTrendSymbolsMap();
|
|
const auto &nonstationary_symbols = dynamic_model.getNonstationarySymbolsMap();
|
|
epilogue.detrend(trend_symbols, nonstationary_symbols);
|
|
}
|
|
|
|
epilogue.toStatic();
|
|
|
|
mod_file_struct.orig_eq_nbr = dynamic_model.equation_number();
|
|
if (mod_file_struct.ramsey_model_present)
|
|
{
|
|
PlannerObjectiveStatement *pos = nullptr;
|
|
for (auto &statement : statements)
|
|
if (auto pos2 = dynamic_cast<PlannerObjectiveStatement *>(statement.get()); pos2)
|
|
if (pos)
|
|
{
|
|
cerr << "ERROR: there can only be one planner_objective statement" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
else
|
|
pos = pos2;
|
|
assert(pos);
|
|
const StaticModel &planner_objective = pos->getPlannerObjective();
|
|
|
|
/*
|
|
clone the model then clone the new equations back to the original because
|
|
we have to call computeDerivIDs (in computeRamseyPolicyFOCs and computingPass)
|
|
*/
|
|
if (linear)
|
|
orig_ramsey_dynamic_model = dynamic_model;
|
|
ramsey_FOC_equations_dynamic_model = dynamic_model;
|
|
ramsey_FOC_equations_dynamic_model.computeRamseyPolicyFOCs(planner_objective);
|
|
ramsey_FOC_equations_dynamic_model.replaceMyEquations(dynamic_model);
|
|
mod_file_struct.ramsey_eq_nbr = dynamic_model.equation_number() - mod_file_struct.orig_eq_nbr;
|
|
}
|
|
|
|
/* Handle var_expectation_model statements: collect information about them,
|
|
create the new corresponding parameters, and the expressions to replace
|
|
the var_expectation statements.
|
|
TODO: move information collection to checkPass(), within a new
|
|
VarModelTable class */
|
|
map<string, expr_t> var_expectation_subst_table;
|
|
for (auto &statement : statements)
|
|
{
|
|
auto vems = dynamic_cast<VarExpectationModelStatement *>(statement.get());
|
|
if (!vems)
|
|
continue;
|
|
|
|
int max_lag;
|
|
vector<int> lhs;
|
|
auto &model_name = vems->model_name;
|
|
if (var_model_table.isExistingVarModelName(vems->aux_model_name))
|
|
{
|
|
max_lag = var_model_table.getMaxLag(vems->aux_model_name);
|
|
lhs = var_model_table.getLhs(vems->aux_model_name);
|
|
}
|
|
else if (trend_component_model_table.isExistingTrendComponentModelName(vems->aux_model_name))
|
|
{
|
|
max_lag = trend_component_model_table.getMaxLag(vems->aux_model_name) + 1;
|
|
lhs = dynamic_model.getUndiffLHSForPac(vems->aux_model_name, diff_subst_table);
|
|
}
|
|
else
|
|
{
|
|
cerr << "ERROR: var_expectation_model " << model_name
|
|
<< " refers to nonexistent auxiliary model " << vems->aux_model_name << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
/* Substitute unary and diff operators in the 'expression' option, then
|
|
match the linear combination in the expression option */
|
|
vems->substituteUnaryOpNodes(unary_ops_nodes, unary_ops_subst_table);
|
|
vems->substituteDiff(diff_nodes, diff_subst_table);
|
|
vems->matchExpression();
|
|
|
|
/* Create auxiliary parameters and the expression to be substituted into
|
|
the var_expectations statement */
|
|
auto subst_expr = dynamic_model.Zero;
|
|
for (int lag = 0; lag < max_lag; lag++)
|
|
for (auto variable : lhs)
|
|
{
|
|
string param_name = "var_expectation_model_" + model_name + '_' + symbol_table.getName(variable) + '_' + to_string(lag);
|
|
int new_param_id = symbol_table.addSymbol(param_name, SymbolType::parameter);
|
|
vems->aux_params_ids.push_back(new_param_id);
|
|
|
|
subst_expr = dynamic_model.AddPlus(subst_expr,
|
|
dynamic_model.AddTimes(dynamic_model.AddVariable(new_param_id),
|
|
dynamic_model.AddVariable(variable, -lag)));
|
|
}
|
|
|
|
if (var_expectation_subst_table.find(model_name) != var_expectation_subst_table.end())
|
|
{
|
|
cerr << "ERROR: model name '" << model_name << "' is used by several var_expectation_model statements" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
var_expectation_subst_table[model_name] = subst_expr;
|
|
}
|
|
// And finally perform the substitutions
|
|
dynamic_model.substituteVarExpectation(var_expectation_subst_table);
|
|
dynamic_model.createVariableMapping(mod_file_struct.orig_eq_nbr +
|
|
(mod_file_struct.ramsey_model_present ?
|
|
mod_file_struct.ramsey_eq_nbr : 0));
|
|
|
|
/* Create auxiliary vars for leads and lags greater than 2, on both endos and
|
|
exos. The transformation is not exactly the same on stochastic and
|
|
deterministic models, because there is no need to take into account the
|
|
Jensen inequality on the latter. */
|
|
bool deterministic_model = !(mod_file_struct.stoch_simul_present
|
|
|| mod_file_struct.estimation_present
|
|
|| mod_file_struct.osr_present
|
|
|| mod_file_struct.ramsey_policy_present
|
|
|| mod_file_struct.discretionary_policy_present
|
|
|| mod_file_struct.calib_smoother_present
|
|
|| mod_file_struct.identification_present
|
|
|| mod_file_struct.mom_estimation_present
|
|
|| mod_file_struct.sensitivity_present
|
|
|| stochastic);
|
|
dynamic_model.substituteEndoLeadGreaterThanTwo(deterministic_model);
|
|
dynamic_model.substituteExoLead(deterministic_model);
|
|
dynamic_model.substituteEndoLagGreaterThanTwo(deterministic_model);
|
|
dynamic_model.substituteExoLag(deterministic_model);
|
|
|
|
dynamic_model.updateVarAndTrendModel();
|
|
|
|
if (differentiate_forward_vars)
|
|
dynamic_model.differentiateForwardVars(differentiate_forward_vars_subset);
|
|
|
|
if (mod_file_struct.dsge_var_estimated || !mod_file_struct.dsge_var_calibrated.empty())
|
|
try
|
|
{
|
|
int sid = symbol_table.addSymbol("dsge_prior_weight", SymbolType::parameter);
|
|
if (!mod_file_struct.dsge_var_calibrated.empty())
|
|
addStatementAtFront(make_unique<InitParamStatement>(sid,
|
|
expressions_tree.AddNonNegativeConstant(mod_file_struct.dsge_var_calibrated),
|
|
symbol_table));
|
|
}
|
|
catch (SymbolTable::AlreadyDeclaredException &e)
|
|
{
|
|
cerr << "ERROR: dsge_prior_weight should not be declared as a model variable / parameter "
|
|
<< "when the dsge_var option is passed to the estimation statement." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
dynamic_model.reorderAuxiliaryEquations();
|
|
|
|
// Freeze the symbol table
|
|
symbol_table.freeze();
|
|
|
|
if (compute_xrefs)
|
|
dynamic_model.computeXrefs();
|
|
|
|
/*
|
|
Enforce the same number of equations and endogenous, except in three cases:
|
|
- ramsey_model, ramsey_policy or discretionary_policy is used
|
|
- a BVAR command is used and there is no equation (standalone BVAR estimation)
|
|
- nostrict option is passed and there are more endogs than equations (dealt with before freeze)
|
|
*/
|
|
if (!(mod_file_struct.ramsey_model_present || mod_file_struct.discretionary_policy_present)
|
|
&& !(mod_file_struct.bvar_present && dynamic_model.equation_number() == 0)
|
|
&& (dynamic_model.equation_number() != symbol_table.endo_nbr()))
|
|
{
|
|
cerr << "ERROR: There are " << dynamic_model.equation_number() << " equations but " << symbol_table.endo_nbr() << " endogenous variables!" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (symbol_table.exo_det_nbr() > 0 && mod_file_struct.perfect_foresight_solver_present)
|
|
{
|
|
cerr << "ERROR: A .mod file cannot contain both one of {perfect_foresight_solver, simul} and varexo_det declaration (all exogenous variables are deterministic in this case)" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (mod_file_struct.ramsey_policy_present && symbol_table.exo_det_nbr() > 0)
|
|
{
|
|
cerr << "ERROR: ramsey_policy is incompatible with deterministic exogenous variables" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (mod_file_struct.identification_present && symbol_table.exo_det_nbr() > 0)
|
|
{
|
|
cerr << "ERROR: identification is incompatible with deterministic exogenous variables" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (occbin && !dynamic_model.hasOccbinTags())
|
|
{
|
|
cerr << "ERROR: the 'occbin' option is present, but there is no equation with the associated tags (bind/relax/pswitch/pcrit)" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (occbin
|
|
&& (mod_file_struct.osr_present || mod_file_struct.mom_estimation_present
|
|
|| mod_file_struct.ramsey_model_present || mod_file_struct.ramsey_policy_present
|
|
|| mod_file_struct.discretionary_policy_present || mod_file_struct.extended_path_present
|
|
|| mod_file_struct.identification_present || mod_file_struct.sensitivity_present))
|
|
{
|
|
cerr << "ERROR: the 'occbin' option is not compatible with commands other than 'estimation', 'stoch_simul', and 'calib_smoother'." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (!mod_file_struct.ramsey_model_present)
|
|
cout << "Found " << dynamic_model.equation_number() << " equation(s)." << endl;
|
|
else
|
|
{
|
|
cout << "Found " << mod_file_struct.orig_eq_nbr << " equation(s)." << endl;
|
|
cout << "Found " << dynamic_model.equation_number() << " FOC equation(s) for Ramsey Problem." << endl;
|
|
}
|
|
|
|
if (symbol_table.exists("dsge_prior_weight"))
|
|
if (mod_file_struct.bayesian_irf_present)
|
|
{
|
|
if (symbol_table.exo_nbr() != symbol_table.observedVariablesNbr())
|
|
{
|
|
cerr << "ERROR: When estimating a DSGE-Var and the bayesian_irf option is passed to the estimation "
|
|
<< "statement, the number of shocks must equal the number of observed variables." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
else
|
|
if (symbol_table.exo_nbr() < symbol_table.observedVariablesNbr())
|
|
{
|
|
cerr << "ERROR: When estimating a DSGE-Var, the number of shocks must be "
|
|
<< "greater than or equal to the number of observed variables." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
|
|
void
|
|
ModFile::computingPass(bool no_tmp_terms, OutputType output, int params_derivs_order)
|
|
{
|
|
// Mod file may have no equation (for example in a standalone BVAR estimation)
|
|
if (dynamic_model.equation_number() > 0)
|
|
{
|
|
if (nonstationary_variables)
|
|
trend_dynamic_model.runTrendTest(global_eval_context);
|
|
|
|
// Compute static model and its derivatives
|
|
static_model = static_cast<StaticModel>(dynamic_model);
|
|
if (!no_static)
|
|
{
|
|
if (mod_file_struct.stoch_simul_present
|
|
|| mod_file_struct.estimation_present || mod_file_struct.osr_present
|
|
|| mod_file_struct.ramsey_model_present || mod_file_struct.identification_present
|
|
|| mod_file_struct.calib_smoother_present || mod_file_struct.mom_estimation_present)
|
|
static_model.set_cutoff_to_zero();
|
|
|
|
int derivsOrder = 1;
|
|
int paramsDerivsOrder = 0;
|
|
if (mod_file_struct.identification_present || mod_file_struct.estimation_analytic_derivation)
|
|
derivsOrder = 2;
|
|
|
|
if (mod_file_struct.identification_present
|
|
|| mod_file_struct.estimation_analytic_derivation
|
|
|| (mod_file_struct.GMM_present && (mod_file_struct.analytic_standard_errors_present || mod_file_struct.analytic_jacobian_present)))
|
|
paramsDerivsOrder = params_derivs_order;
|
|
|
|
static_model.computingPass(derivsOrder, paramsDerivsOrder, global_eval_context, no_tmp_terms, block, bytecode);
|
|
}
|
|
// Set things to compute for dynamic model
|
|
if (mod_file_struct.perfect_foresight_solver_present || mod_file_struct.check_present
|
|
|| mod_file_struct.stoch_simul_present
|
|
|| mod_file_struct.estimation_present || mod_file_struct.osr_present
|
|
|| mod_file_struct.ramsey_model_present || mod_file_struct.identification_present
|
|
|| mod_file_struct.calib_smoother_present || mod_file_struct.mom_estimation_present)
|
|
{
|
|
if (mod_file_struct.perfect_foresight_solver_present)
|
|
{
|
|
int derivsOrder = 1;
|
|
if (output == OutputType::second)
|
|
derivsOrder = 2;
|
|
else if (output == OutputType::third)
|
|
derivsOrder = 3;
|
|
dynamic_model.computingPass(true, derivsOrder, 0, global_eval_context, no_tmp_terms, block, use_dll, bytecode);
|
|
}
|
|
else
|
|
{
|
|
if (mod_file_struct.stoch_simul_present
|
|
|| mod_file_struct.estimation_present || mod_file_struct.osr_present
|
|
|| mod_file_struct.ramsey_model_present || mod_file_struct.identification_present
|
|
|| mod_file_struct.calib_smoother_present || mod_file_struct.mom_estimation_present)
|
|
dynamic_model.set_cutoff_to_zero();
|
|
if (mod_file_struct.order_option < 1)
|
|
{
|
|
cerr << "ERROR: Incorrect order option..." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
int derivsOrder = max(mod_file_struct.order_option,mod_file_struct.identification_order + 1); // See preprocessor#40
|
|
if (mod_file_struct.GMM_present
|
|
&& (mod_file_struct.analytic_standard_errors_present || mod_file_struct.analytic_jacobian_present)) //analytic_standard_errors or analytic_jacobian require one order more
|
|
derivsOrder = max(mod_file_struct.order_option,
|
|
max(mod_file_struct.identification_order,mod_file_struct.mom_order) + 1); // See preprocessor#40
|
|
|
|
if (mod_file_struct.sensitivity_present || linear || output == OutputType::second)
|
|
derivsOrder = max(derivsOrder, 2);
|
|
if (mod_file_struct.estimation_analytic_derivation || output == OutputType::third)
|
|
derivsOrder = max(derivsOrder, 3);
|
|
int paramsDerivsOrder = 0;
|
|
if (mod_file_struct.identification_present
|
|
|| mod_file_struct.estimation_analytic_derivation
|
|
|| (mod_file_struct.GMM_present && (mod_file_struct.analytic_standard_errors_present || mod_file_struct.analytic_jacobian_present)))
|
|
paramsDerivsOrder = params_derivs_order;
|
|
dynamic_model.computingPass(true, derivsOrder, paramsDerivsOrder, global_eval_context, no_tmp_terms, block, use_dll, bytecode);
|
|
if (linear && mod_file_struct.ramsey_model_present)
|
|
orig_ramsey_dynamic_model.computingPass(true, 2, paramsDerivsOrder, global_eval_context, no_tmp_terms, block, use_dll, bytecode);
|
|
}
|
|
}
|
|
else // No computing task requested, compute derivatives up to 2nd order by default
|
|
dynamic_model.computingPass(true, 2, 0, global_eval_context, no_tmp_terms, block, use_dll, bytecode);
|
|
|
|
/* Check that the model is linear.
|
|
FIXME: this check always passes if derivsOrder = 1, i.e. for a perfect
|
|
foresight model, because the Hessian is not computed in that case. */
|
|
if (linear)
|
|
{
|
|
set<int> eqs;
|
|
if (mod_file_struct.ramsey_model_present)
|
|
eqs = orig_ramsey_dynamic_model.getNonZeroHessianEquations();
|
|
else
|
|
eqs = dynamic_model.getNonZeroHessianEquations();
|
|
|
|
if (!eqs.empty())
|
|
{
|
|
cerr << "ERROR: If the model is declared linear the second derivatives must be equal to zero." << endl
|
|
<< " The following equations have non-zero second derivatives:" << endl;
|
|
for (const auto &it : eqs)
|
|
{
|
|
cerr << " * Eq # " << it+1;
|
|
auto tags = dynamic_model.getEquationTags(it);
|
|
if (auto it2 = tags.find("name"); it2 != tags.end())
|
|
cerr << " [" << it2->second << "]";
|
|
cerr << endl;
|
|
}
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
}
|
|
|
|
for (auto &statement : statements)
|
|
statement->computingPass(mod_file_struct);
|
|
|
|
// Compute epilogue derivatives (but silence standard output)
|
|
streambuf *oldcout = cout.rdbuf();
|
|
cout.rdbuf(nullptr);
|
|
epilogue.computingPass(true, 2, 0, global_eval_context, true, false, false, false);
|
|
cout.rdbuf(oldcout);
|
|
}
|
|
|
|
void
|
|
ModFile::writeMOutput(const string &basename, bool clear_all, bool clear_global, bool no_warn,
|
|
bool console, bool nograph, bool nointeractive, const ConfigFile &config_file,
|
|
bool check_model_changes, bool minimal_workspace, bool compute_xrefs,
|
|
const string &mexext,
|
|
const filesystem::path &matlabroot,
|
|
const filesystem::path &dynareroot, bool onlymodel, bool gui, bool notime) const
|
|
{
|
|
bool hasModelChanged = !dynamic_model.isChecksumMatching(basename, block) || !check_model_changes;
|
|
if (hasModelChanged)
|
|
{
|
|
// Erase possible remnants of previous runs
|
|
/* Under MATLAB+Windows (but not under Octave nor under GNU/Linux or
|
|
macOS), if we directly remove the "+" subdirectory, then the
|
|
preprocessor is not able to recreate it afterwards (presumably because
|
|
MATLAB maintains some sort of lock on it). The workaround is to rename
|
|
it before deleting it (the renaming must occur in the same directory,
|
|
otherwise it may file if the destination is not on the same
|
|
filesystem). */
|
|
if (filesystem::path plusfolder{"+" + basename}; filesystem::exists(plusfolder))
|
|
{
|
|
if (filesystem::exists(plusfolder / "+objective"))
|
|
{
|
|
// Do it recursively for the +objective folder, created by ramsey_policy
|
|
auto tmp2 = unique_path();
|
|
filesystem::rename(plusfolder / "+objective", tmp2);
|
|
filesystem::remove_all(tmp2);
|
|
}
|
|
|
|
auto tmp = unique_path();
|
|
filesystem::rename(plusfolder, tmp);
|
|
filesystem::remove_all(tmp);
|
|
}
|
|
filesystem::remove_all(basename + "/model/src");
|
|
filesystem::remove_all(basename + "/model/bytecode");
|
|
}
|
|
|
|
ofstream mOutputFile;
|
|
|
|
if (basename.size())
|
|
{
|
|
filesystem::create_directory("+" + basename);
|
|
string fname = "+" + basename + "/driver.m";
|
|
mOutputFile.open(fname, ios::out | ios::binary);
|
|
if (!mOutputFile.is_open())
|
|
{
|
|
cerr << "ERROR: Can't open file " << fname << " for writing" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
cerr << "ERROR: Missing file name" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
mOutputFile << "%" << endl
|
|
<< "% Status : main Dynare file" << endl
|
|
<< "%" << endl
|
|
<< "% Warning : this file is generated automatically by Dynare" << endl
|
|
<< "% from model file (.mod)" << endl << endl;
|
|
|
|
if (no_warn)
|
|
mOutputFile << "warning off" << endl; // This will be executed *after* function warning_config()
|
|
|
|
if (clear_all)
|
|
mOutputFile << "if isoctave || matlab_ver_less_than('8.6')" << endl
|
|
<< " clear all" << endl
|
|
<< "else" << endl
|
|
<< " clearvars -global" << endl
|
|
<< " clear_persistent_variables(fileparts(which('dynare')), false)" << endl
|
|
<< "end" << endl;
|
|
else if (clear_global)
|
|
mOutputFile << "clear M_ options_ oo_ estim_params_ bayestopt_ dataset_ dataset_info estimation_info ys0_ ex0_;" << endl;
|
|
|
|
if (!notime)
|
|
mOutputFile << "tic0 = tic;" << endl;
|
|
|
|
mOutputFile << "% Define global variables." << endl
|
|
<< "global M_ options_ oo_ estim_params_ bayestopt_ dataset_ dataset_info estimation_info ys0_ ex0_" << endl
|
|
<< "options_ = [];" << endl
|
|
<< "M_.fname = '" << basename << "';" << endl
|
|
<< "M_.dynare_version = '" << PACKAGE_VERSION << "';" << endl
|
|
<< "oo_.dynare_version = '" << PACKAGE_VERSION << "';" << endl
|
|
<< "options_.dynare_version = '" << PACKAGE_VERSION << "';" << endl
|
|
<< "%" << endl
|
|
<< "% Some global variables initialization" << endl
|
|
<< "%" << endl;
|
|
if (!onlymodel)
|
|
config_file.writeHooks(mOutputFile);
|
|
mOutputFile << "global_initialization;" << endl;
|
|
|
|
if (minimal_workspace)
|
|
mOutputFile << "options_.minimal_workspace = true;" << endl;
|
|
|
|
if (console)
|
|
mOutputFile << "options_.console_mode = true;" << endl
|
|
<< "options_.nodisplay = true;" << endl;
|
|
if (nograph)
|
|
mOutputFile << "options_.nograph = true;" << endl;
|
|
|
|
if (nointeractive)
|
|
mOutputFile << "options_.nointeractive = true;" << endl;
|
|
|
|
if (param_used_with_lead_lag)
|
|
mOutputFile << "M_.parameter_used_with_lead_lag = true;" << endl;
|
|
|
|
cout << "Processing outputs ..." << endl;
|
|
|
|
symbol_table.writeOutput(mOutputFile);
|
|
|
|
// Fill the fields related to solve_algo={12,14} if possible.
|
|
mOutputFile << "M_ = setup_solvers(M_);" << endl;
|
|
|
|
var_model_table.writeOutput(basename, mOutputFile);
|
|
trend_component_model_table.writeOutput(basename, mOutputFile);
|
|
|
|
// Initialize M_.Sigma_e, M_.Correlation_matrix, M_.H, and M_.Correlation_matrix_ME
|
|
mOutputFile << "M_.Sigma_e = zeros(" << symbol_table.exo_nbr() << ", "
|
|
<< symbol_table.exo_nbr() << ");" << endl
|
|
<< "M_.Correlation_matrix = eye(" << symbol_table.exo_nbr() << ", "
|
|
<< symbol_table.exo_nbr() << ");" << endl;
|
|
|
|
if (mod_file_struct.calibrated_measurement_errors)
|
|
mOutputFile << "M_.H = zeros(" << symbol_table.observedVariablesNbr() << ", "
|
|
<< symbol_table.observedVariablesNbr() << ");" << endl
|
|
<< "M_.Correlation_matrix_ME = eye(" << symbol_table.observedVariablesNbr() << ", "
|
|
<< symbol_table.observedVariablesNbr() << ");" << endl;
|
|
else
|
|
mOutputFile << "M_.H = 0;" << endl
|
|
<< "M_.Correlation_matrix_ME = 1;" << endl;
|
|
|
|
// May be later modified by a shocks block
|
|
mOutputFile << "M_.sigma_e_is_diagonal = true;" << endl;
|
|
|
|
// Initialize M_.det_shocks
|
|
mOutputFile << "M_.det_shocks = [];" << endl;
|
|
|
|
auto to_matlab_logical = [](bool m) { return m ? "true" : "false"; };
|
|
|
|
mOutputFile << "options_.linear = " << to_matlab_logical(linear) << ";" << endl
|
|
<< "options_.block = " << to_matlab_logical(block) << ";" << endl
|
|
<< "options_.bytecode = " << to_matlab_logical(bytecode) << ";" << endl
|
|
<< "options_.use_dll = " << to_matlab_logical(use_dll) << ";" << endl;
|
|
|
|
if (parallel_local_files.size() > 0)
|
|
{
|
|
mOutputFile << "options_.parallel_info.local_files = {" << endl;
|
|
for (const auto ¶llel_local_file : parallel_local_files)
|
|
{
|
|
size_t j = parallel_local_file.find_last_of(R"(/\)");
|
|
if (j == string::npos)
|
|
mOutputFile << "'', '" << parallel_local_file << "';" << endl;
|
|
else
|
|
mOutputFile << "'" << parallel_local_file.substr(0, j+1) << "', '"
|
|
<< parallel_local_file.substr(j+1, string::npos) << "';" << endl;
|
|
}
|
|
mOutputFile << "};" << endl;
|
|
}
|
|
|
|
if (dynamic_model.isHessianComputed())
|
|
{
|
|
mOutputFile << "M_.nonzero_hessian_eqs = ";
|
|
dynamic_model.printNonZeroHessianEquations(mOutputFile);
|
|
mOutputFile << ";" << endl
|
|
<< "M_.hessian_eq_zero = isempty(M_.nonzero_hessian_eqs);" << endl;
|
|
}
|
|
|
|
if (!onlymodel)
|
|
config_file.writeCluster(mOutputFile);
|
|
|
|
if (bytecode)
|
|
mOutputFile << "if exist('bytecode') ~= 3" << endl
|
|
<< " error('DYNARE: Can''t find bytecode DLL. Please compile it or remove the ''bytecode'' option.')" << endl
|
|
<< "end" << endl;
|
|
|
|
mOutputFile << "M_.orig_eq_nbr = " << mod_file_struct.orig_eq_nbr << ";" << endl
|
|
<< "M_.eq_nbr = " << dynamic_model.equation_number() << ";" << endl
|
|
<< "M_.ramsey_eq_nbr = " << mod_file_struct.ramsey_eq_nbr << ";" << endl
|
|
<< "M_.set_auxiliary_variables = exist(['./+' M_.fname '/set_auxiliary_variables.m'], 'file') == 2;" << endl;
|
|
|
|
epilogue.writeOutput(mOutputFile);
|
|
|
|
if (dynamic_model.equation_number() > 0)
|
|
{
|
|
dynamic_model.writeDriverOutput(mOutputFile, basename, block, use_dll, occbin, mod_file_struct.estimation_present, compute_xrefs);
|
|
if (!no_static)
|
|
static_model.writeDriverOutput(mOutputFile, block);
|
|
}
|
|
|
|
if (occbin)
|
|
mOutputFile << "options_ = occbin.set_default_options(options_, M_);" << endl
|
|
<< "M_ = occbin.get_info(M_);" << endl;
|
|
|
|
if (onlymodel || gui)
|
|
for (const auto &statement : statements)
|
|
{
|
|
/* Special treatment for initval block: insert initial values for the
|
|
auxiliary variables and initialize exo det */
|
|
if (auto ivs = dynamic_cast<InitValStatement *>(statement.get()); ivs)
|
|
{
|
|
ivs->writeOutput(mOutputFile, basename, minimal_workspace);
|
|
static_model.writeAuxVarInitval(mOutputFile, ExprNodeOutputType::matlabOutsideModel);
|
|
ivs->writeOutputPostInit(mOutputFile);
|
|
}
|
|
|
|
// Special treatment for endval block: insert initial values for the auxiliary variables
|
|
if (auto evs = dynamic_cast<EndValStatement *>(statement.get()); evs)
|
|
{
|
|
evs->writeOutput(mOutputFile, basename, minimal_workspace);
|
|
static_model.writeAuxVarInitval(mOutputFile, ExprNodeOutputType::matlabOutsideModel);
|
|
}
|
|
|
|
if (auto ips = dynamic_cast<InitParamStatement *>(statement.get()); ips)
|
|
ips->writeOutput(mOutputFile, basename, minimal_workspace);
|
|
|
|
if (auto ss = dynamic_cast<ShocksStatement *>(statement.get()); ss)
|
|
ss->writeOutput(mOutputFile, basename, minimal_workspace);
|
|
|
|
if (auto eps = dynamic_cast<EstimatedParamsStatement *>(statement.get()); eps)
|
|
eps->writeOutput(mOutputFile, basename, minimal_workspace);
|
|
|
|
if (auto sgs = dynamic_cast<ShockGroupsStatement *>(statement.get()); sgs)
|
|
sgs->writeOutput(mOutputFile, basename, minimal_workspace);
|
|
|
|
if (gui)
|
|
if (auto it = dynamic_cast<NativeStatement *>(statement.get()); it)
|
|
it->writeOutput(mOutputFile, basename, minimal_workspace);
|
|
}
|
|
else
|
|
{
|
|
for (const auto &statement : statements)
|
|
{
|
|
statement->writeOutput(mOutputFile, basename, minimal_workspace);
|
|
|
|
/* Special treatment for initval block: insert initial values for the
|
|
auxiliary variables and initialize exo det */
|
|
if (auto ivs = dynamic_cast<InitValStatement *>(statement.get()); ivs)
|
|
{
|
|
static_model.writeAuxVarInitval(mOutputFile, ExprNodeOutputType::matlabOutsideModel);
|
|
ivs->writeOutputPostInit(mOutputFile);
|
|
}
|
|
|
|
// Special treatment for endval block: insert initial values for the auxiliary variables
|
|
if (auto evs = dynamic_cast<EndValStatement *>(statement.get()); evs)
|
|
static_model.writeAuxVarInitval(mOutputFile, ExprNodeOutputType::matlabOutsideModel);
|
|
|
|
// Special treatment for load params and steady state statement: insert initial values for the auxiliary variables
|
|
if (auto lpass = dynamic_cast<LoadParamsAndSteadyStateStatement *>(statement.get()); lpass && !no_static)
|
|
static_model.writeAuxVarInitval(mOutputFile, ExprNodeOutputType::matlabOutsideModel);
|
|
}
|
|
|
|
if (!notime)
|
|
mOutputFile << endl << endl
|
|
<< "oo_.time = toc(tic0);" << endl
|
|
<< "disp(['Total computing time : ' dynsec2hms(oo_.time) ]);" << endl;
|
|
|
|
mOutputFile << "save('" << basename << "_results.mat', 'oo_', 'M_', 'options_');" << endl
|
|
<< "if exist('estim_params_', 'var') == 1" << endl
|
|
<< " save('" << basename << "_results.mat', 'estim_params_', '-append');" << endl << "end" << endl
|
|
<< "if exist('bayestopt_', 'var') == 1" << endl
|
|
<< " save('" << basename << "_results.mat', 'bayestopt_', '-append');" << endl << "end" << endl
|
|
<< "if exist('dataset_', 'var') == 1" << endl
|
|
<< " save('" << basename << "_results.mat', 'dataset_', '-append');" << endl << "end" << endl
|
|
<< "if exist('estimation_info', 'var') == 1" << endl
|
|
<< " save('" << basename << "_results.mat', 'estimation_info', '-append');" << endl << "end" << endl
|
|
<< "if exist('dataset_info', 'var') == 1" << endl
|
|
<< " save('" << basename << "_results.mat', 'dataset_info', '-append');" << endl << "end" << endl
|
|
<< "if exist('oo_recursive_', 'var') == 1" << endl
|
|
<< " save('" << basename << "_results.mat', 'oo_recursive_', '-append');" << endl << "end" << endl;
|
|
|
|
config_file.writeEndParallel(mOutputFile);
|
|
|
|
if (!no_warn)
|
|
{
|
|
if (warnings.countWarnings() > 0)
|
|
mOutputFile << "disp('Note: " << warnings.countWarnings() << " warning(s) encountered in the preprocessor')" << endl;
|
|
|
|
mOutputFile << "if ~isempty(lastwarn)" << endl
|
|
<< " disp('Note: warning(s) encountered in MATLAB/Octave code')" << endl
|
|
<< "end" << endl;
|
|
}
|
|
}
|
|
|
|
mOutputFile.close();
|
|
|
|
if (hasModelChanged)
|
|
{
|
|
// Create static and dynamic files
|
|
if (dynamic_model.equation_number() > 0)
|
|
{
|
|
if (!no_static)
|
|
{
|
|
static_model.writeStaticFile(basename, block, bytecode, use_dll, mexext, matlabroot, dynareroot, false);
|
|
static_model.writeParamsDerivativesFile(basename, false);
|
|
}
|
|
|
|
dynamic_model.writeDynamicFile(basename, block, bytecode, use_dll, mexext, matlabroot, dynareroot, false);
|
|
|
|
dynamic_model.writeParamsDerivativesFile(basename, false);
|
|
|
|
dynamic_model.writeDynamicJacobianNonZeroElts(basename);
|
|
}
|
|
|
|
// Create steady state file
|
|
steady_state_model.writeSteadyStateFile(basename, mod_file_struct.ramsey_model_present, false);
|
|
|
|
// Create epilogue file
|
|
epilogue.writeEpilogueFile(basename);
|
|
}
|
|
|
|
cout << "done" << endl;
|
|
}
|
|
|
|
void
|
|
ModFile::writeJuliaOutput(const string &basename) const
|
|
{
|
|
if (dynamic_model.equation_number() > 0)
|
|
{
|
|
if (!no_static)
|
|
{
|
|
static_model.writeStaticFile(basename, false, false, false, "", {}, {}, true);
|
|
static_model.writeParamsDerivativesFile(basename, true);
|
|
}
|
|
dynamic_model.writeDynamicFile(basename, block, bytecode, use_dll, "", {}, {}, true);
|
|
dynamic_model.writeParamsDerivativesFile(basename, true);
|
|
}
|
|
steady_state_model.writeSteadyStateFile(basename, mod_file_struct.ramsey_model_present, true);
|
|
}
|
|
|
|
void
|
|
ModFile::writeJsonOutput(const string &basename, JsonOutputPointType json, JsonFileOutputType json_output_mode, bool onlyjson, bool jsonderivsimple)
|
|
{
|
|
if (json == JsonOutputPointType::nojson)
|
|
return;
|
|
|
|
if (json == JsonOutputPointType::parsing || json == JsonOutputPointType::checkpass)
|
|
symbol_table.freeze();
|
|
|
|
if (json_output_mode == JsonFileOutputType::standardout)
|
|
cout << "//-- BEGIN JSON --// " << endl
|
|
<< "{" << endl;
|
|
|
|
writeJsonOutputParsingCheck(basename, json_output_mode, json == JsonOutputPointType::transformpass, json == JsonOutputPointType::computingpass);
|
|
|
|
if (json == JsonOutputPointType::parsing || json == JsonOutputPointType::checkpass)
|
|
symbol_table.unfreeze();
|
|
|
|
if (json == JsonOutputPointType::computingpass)
|
|
writeJsonComputingPassOutput(basename, json_output_mode, jsonderivsimple);
|
|
|
|
if (json_output_mode == JsonFileOutputType::standardout)
|
|
cout << "}" << endl
|
|
<< "//-- END JSON --// " << endl;
|
|
|
|
switch (json)
|
|
{
|
|
case JsonOutputPointType::parsing:
|
|
cout << "JSON written after Parsing step." << endl;
|
|
break;
|
|
case JsonOutputPointType::checkpass:
|
|
cout << "JSON written after Check step." << endl;
|
|
break;
|
|
case JsonOutputPointType::transformpass:
|
|
cout << "JSON written after Transform step." << endl;
|
|
break;
|
|
case JsonOutputPointType::computingpass:
|
|
cout << "JSON written after Computing step." << endl;
|
|
break;
|
|
case JsonOutputPointType::nojson:
|
|
cerr << "ModFile::writeJsonOutput: should not arrive here." << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
if (onlyjson)
|
|
exit(EXIT_SUCCESS);
|
|
}
|
|
|
|
void
|
|
ModFile::writeJsonOutputParsingCheck(const string &basename, JsonFileOutputType json_output_mode, bool transformpass, bool computingpass) const
|
|
{
|
|
ostringstream output;
|
|
output << "{" << endl;
|
|
|
|
symbol_table.writeJsonOutput(output);
|
|
output << ", ";
|
|
dynamic_model.writeJsonOutput(output);
|
|
|
|
if (!statements.empty()
|
|
|| !var_model_table.empty()
|
|
|| !trend_component_model_table.empty())
|
|
{
|
|
output << R"(, "statements": [)";
|
|
if (!var_model_table.empty())
|
|
{
|
|
var_model_table.writeJsonOutput(output);
|
|
output << ", ";
|
|
}
|
|
|
|
if (!trend_component_model_table.empty())
|
|
{
|
|
trend_component_model_table.writeJsonOutput(output);
|
|
output << ", ";
|
|
}
|
|
|
|
for (auto it = statements.begin(); it != statements.end(); ++it)
|
|
{
|
|
if (it != statements.begin())
|
|
output << ", " << endl;
|
|
(*it)->writeJsonOutput(output);
|
|
}
|
|
output << "]" << endl;
|
|
}
|
|
|
|
if (computingpass)
|
|
{
|
|
output << ",";
|
|
dynamic_model.writeJsonDynamicModelInfo(output);
|
|
}
|
|
output << "}" << endl;
|
|
|
|
ostringstream original_model_output;
|
|
original_model_output << "";
|
|
if (transformpass || computingpass)
|
|
{
|
|
original_model_output << "{";
|
|
original_model.writeJsonOriginalModelOutput(original_model_output);
|
|
if (!statements.empty() || !var_model_table.empty() || !trend_component_model_table.empty())
|
|
{
|
|
original_model_output << endl << R"(, "statements": [)";
|
|
if (!var_model_table.empty())
|
|
{
|
|
var_model_table.writeJsonOutput(original_model_output);
|
|
original_model_output << ", ";
|
|
}
|
|
if (!trend_component_model_table.empty())
|
|
{
|
|
trend_component_model_table.writeJsonOutput(original_model_output);
|
|
original_model_output << ", ";
|
|
}
|
|
int i = 0;
|
|
for (const auto &it : statements)
|
|
{
|
|
original_model_output << (i++ > 0 ? "," : "") << endl;
|
|
it->writeJsonOutput(original_model_output);
|
|
}
|
|
original_model_output << "]" << endl;
|
|
}
|
|
original_model_output << "}" << endl;
|
|
}
|
|
|
|
ostringstream steady_state_model_output;
|
|
steady_state_model_output << "";
|
|
if (dynamic_model.equation_number() > 0)
|
|
steady_state_model.writeJsonSteadyStateFile(steady_state_model_output,
|
|
transformpass || computingpass);
|
|
|
|
if (json_output_mode == JsonFileOutputType::standardout)
|
|
{
|
|
if (transformpass || computingpass)
|
|
cout << R"("transformed_modfile": )";
|
|
else
|
|
cout << R"("modfile": )";
|
|
cout << output.str();
|
|
if (!original_model_output.str().empty())
|
|
cout << R"(, "original_model": )" << original_model_output.str();
|
|
if (!steady_state_model_output.str().empty())
|
|
cout << R"(, "steady_state_model": )" << steady_state_model_output.str();
|
|
}
|
|
else
|
|
{
|
|
ofstream jsonOutputFile;
|
|
|
|
if (basename.size())
|
|
{
|
|
filesystem::create_directories(basename + "/model/json");
|
|
string fname{basename + "/model/json/modfile.json"};
|
|
jsonOutputFile.open(fname, ios::out | ios::binary);
|
|
if (!jsonOutputFile.is_open())
|
|
{
|
|
cerr << "ERROR: Can't open file " << fname << " for writing" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
cerr << "ERROR: Missing file name" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
jsonOutputFile << output.str();
|
|
jsonOutputFile.close();
|
|
|
|
if (!original_model_output.str().empty())
|
|
{
|
|
if (basename.size())
|
|
{
|
|
string fname{basename + "/model/json/modfile-original.json"};
|
|
jsonOutputFile.open(fname, ios::out | ios::binary);
|
|
if (!jsonOutputFile.is_open())
|
|
{
|
|
cerr << "ERROR: Can't open file " << fname << " for writing" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
cerr << "ERROR: Missing file name" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
jsonOutputFile << original_model_output.str();
|
|
jsonOutputFile.close();
|
|
}
|
|
if (!steady_state_model_output.str().empty())
|
|
{
|
|
if (basename.size())
|
|
{
|
|
string fname{basename + "/model/json/steady_state_model.json"};
|
|
jsonOutputFile.open(fname, ios::out | ios::binary);
|
|
if (!jsonOutputFile.is_open())
|
|
{
|
|
cerr << "ERROR: Can't open file " << fname << " for writing" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
cerr << "ERROR: Missing file name" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
jsonOutputFile << steady_state_model_output.str();
|
|
jsonOutputFile.close();
|
|
}
|
|
}
|
|
}
|
|
|
|
void
|
|
ModFile::writeJsonComputingPassOutput(const string &basename, JsonFileOutputType json_output_mode, bool jsonderivsimple) const
|
|
{
|
|
if (basename.empty() && json_output_mode != JsonFileOutputType::standardout)
|
|
{
|
|
cerr << "ERROR: Missing file name" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
ostringstream tmp_out, static_output, dynamic_output, static_paramsd_output, dynamic_paramsd_output;
|
|
|
|
static_output << "{";
|
|
static_model.writeJsonComputingPassOutput(static_output, !jsonderivsimple);
|
|
static_output << "}";
|
|
|
|
dynamic_output << "{";
|
|
dynamic_model.writeJsonComputingPassOutput(dynamic_output, !jsonderivsimple);
|
|
dynamic_output << "}";
|
|
|
|
static_model.writeJsonParamsDerivativesFile(tmp_out, !jsonderivsimple);
|
|
if (!tmp_out.str().empty())
|
|
static_paramsd_output << "{" << tmp_out.str() << "}" << endl;
|
|
|
|
tmp_out.str("");
|
|
dynamic_model.writeJsonParamsDerivativesFile(tmp_out, !jsonderivsimple);
|
|
if (!tmp_out.str().empty())
|
|
dynamic_paramsd_output << "{" << tmp_out.str() << "}" << endl;
|
|
|
|
if (json_output_mode == JsonFileOutputType::standardout)
|
|
{
|
|
cout << R"(, "static_model": )" << static_output.str() << endl
|
|
<< R"(, "dynamic_model": )" << dynamic_output.str() << endl;
|
|
|
|
if (!static_paramsd_output.str().empty())
|
|
cout << R"(, "static_params_deriv": )" << static_paramsd_output.str() << endl;
|
|
|
|
if (!dynamic_paramsd_output.str().empty())
|
|
cout << R"(, "dynamic_params_deriv": )" << dynamic_paramsd_output.str() << endl;
|
|
}
|
|
else
|
|
{
|
|
filesystem::create_directories(basename + "/model/json");
|
|
|
|
writeJsonFileHelper(basename + "/model/json/static.json", static_output);
|
|
writeJsonFileHelper(basename + "/model/json/dynamic.json", dynamic_output);
|
|
|
|
if (!static_paramsd_output.str().empty())
|
|
writeJsonFileHelper(basename + "/model/json/static_params_derivs.json", static_paramsd_output);
|
|
|
|
if (!dynamic_paramsd_output.str().empty())
|
|
writeJsonFileHelper(basename + "/model/json/params_derivs.json", dynamic_paramsd_output);
|
|
}
|
|
}
|
|
|
|
void
|
|
ModFile::writeJsonFileHelper(const string &fname, ostringstream &output) const
|
|
{
|
|
ofstream jsonOutput;
|
|
jsonOutput.open(fname, ios::out | ios::binary);
|
|
if (!jsonOutput.is_open())
|
|
{
|
|
cerr << "ERROR: Can't open file " << fname << " for writing" << endl;
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
jsonOutput << output.str();
|
|
jsonOutput.close();
|
|
}
|
|
|
|
filesystem::path
|
|
ModFile::unique_path()
|
|
{
|
|
filesystem::path path;
|
|
string possible_characters = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz";
|
|
random_device rd;
|
|
mt19937 generator(rd());
|
|
uniform_int_distribution<int> distribution{0, static_cast<int>(possible_characters.size())-1};
|
|
do
|
|
{
|
|
constexpr int rand_length = 10;
|
|
string rand_str(rand_length, '\0');
|
|
for (auto &dis : rand_str)
|
|
dis = possible_characters[distribution(generator)];
|
|
path = rand_str;
|
|
}
|
|
while (filesystem::exists(path));
|
|
|
|
return path;
|
|
}
|