preprocessor/src/ModFile.cc

/*
 * Copyright (C) 2006-2018 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/>.
 */

#include <cstdlib>
#include <iostream>
#include <fstream>
#include <typeinfo>
#include <cassert>

#include <boost/filesystem.hpp>

#include "ModFile.hh"
#include "ConfigFile.hh"
#include "ComputingTasks.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},
    non_linear_equations_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},
    diff_static_model{symbol_table, num_constants, external_functions_table},
    warnings{warnings_arg}
{
}

void
ModFile::evalAllExpressions(bool warn_uninit, const bool nopreprocessoroutput)
{
  if (!nopreprocessoroutput)
    cout << "Evaluating expressions...";

  // Loop over all statements, and fill global eval context if relevant
  for (auto &st : statements)
    {
      auto ips = dynamic_cast<InitParamStatement *>(st.get());
      if (ips)
        ips->fillEvalContext(global_eval_context);

      auto ies = dynamic_cast<InitOrEndValStatement *>(st.get());
      if (ies)
        ies->fillEvalContext(global_eval_context);

      auto lpass = dynamic_cast<LoadParamsAndSteadyStateStatement *>(st.get());
      if (lpass)
        lpass->fillEvalContext(global_eval_context);
    }

  // Evaluate model local variables
  dynamic_model.fillEvalContext(global_eval_context);

  if (!nopreprocessoroutput)
    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++)
    {
      SymbolType type = symbol_table.getType(id);
      if ((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(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
    || 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 && byte_code)
    {
      cerr << "ERROR: 'k_order_solver' (which is implicit if order >= 3), is not yet compatible with 'bytecode'." << endl;
      exit(EXIT_FAILURE);
    }

  if (use_dll && (block || byte_code || linear_decomposition))
    {
      cerr << "ERROR: In 'model' block, 'use_dll' option is not compatible with 'block', 'bytecode' or 'linear_decomposition'" << endl;
      exit(EXIT_FAILURE);
    }
  if (block && linear_decomposition)
    {
      cerr << "ERROR: In 'model' block, 'block' option is not compatible with 'linear_decomposition'" << endl;
      exit(EXIT_FAILURE);
    }

  if (!byte_code && linear_decomposition)
    {
      cerr << "ERROR: For the moment in 'model' block, 'linear_decomposition' option is compatible only with 'bytecode' option" << endl;
      exit(EXIT_FAILURE);
    }

  if (block || byte_code)
    if (dynamic_model.isModelLocalVariableUsed())
      {
        cerr << "ERROR: In 'model' block, 'block' or 'bytecode' options are not yet compatible with pound expressions" << 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)
    if (!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 << "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.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 << "WARNING: you have declared your model 'linear' but you are using a function (max, min, abs, sign) or an operator (<, >, <=, >=, ==, !=) which potentially makes it non-linear." << endl;

  // 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);
        }
    }
}

void
ModFile::transformPass(bool nostrict, bool stochastic, bool compute_xrefs, const bool nopreprocessoroutput, const bool transform_unary_ops)
{
  // Save the original model (must be done before any model transformations by preprocessor)
  // - except adl and diff which we always want expanded
  dynamic_model.substituteAdl();
  dynamic_model.setLeadsLagsOrig();
  dynamic_model.cloneDynamic(original_model);

  if (nostrict)
    {
      set<int> unusedEndogs = dynamic_model.findUnusedEndogenous();
      for (int unusedEndog : unusedEndogs)
        {
          symbol_table.changeType(unusedEndog, SymbolType::unusedEndogenous);
          warnings << "WARNING: '" << symbol_table.getName(unusedEndog)
                   << "' not used in model block, removed by nostrict command-line option" << endl;
        }
    }

  // Get all equation tags associated with VARs and Pac Models
  set<string> eqtags;
  for (auto const & it : trend_component_model_table.getEqTags())
    for (auto & it1 : it.second)
      eqtags.insert(it1);

  for (auto const & it : var_model_table.getEqTags())
    for (auto & it1 : it.second)
      eqtags.insert(it1);

  if (transform_unary_ops)
    dynamic_model.substituteUnaryOps(diff_static_model);
  else
    // substitute only those unary ops that appear in auxiliary model equations
    dynamic_model.substituteUnaryOps(diff_static_model, eqtags);

  // Create auxiliary variable and equations for Diff operators that appear in VAR equations
  ExprNode::subst_table_t diff_subst_table;
  dynamic_model.substituteDiff(diff_static_model, diff_subst_table);

  // Fill Trend Component Model Table
  dynamic_model.fillTrendComponentModelTable();
  original_model.fillTrendComponentModelTableFromOrigModel(diff_static_model);
  dynamic_model.fillTrendComponentmodelTableAREC(diff_subst_table);
  dynamic_model.fillVarModelTable();
  original_model.fillVarModelTableFromOrigModel(diff_static_model);

  // Pac Model
  for (auto & statement : statements)
    {
      auto pms = dynamic_cast<PacModelStatement *>(statement.get());
      if (pms != nullptr)
         {
           vector<int> lhs;
           vector<bool> nonstationary;
           int growth_symb_id, max_lag;
           string aux_model_name, pac_model_name;
           tie ( pac_model_name, aux_model_name, growth_symb_id ) =
             pms->getPacModelInfoForPacExpectation();
           if (trend_component_model_table.isExistingTrendComponentModelName(aux_model_name))
             {
               max_lag = trend_component_model_table.getMaxLag(aux_model_name) + 1;
               lhs = dynamic_model.getUndiffLHSForPac(aux_model_name, diff_subst_table);
               nonstationary = trend_component_model_table.getNonstationary(aux_model_name);
             }
           else if (var_model_table.isExistingVarModelName(aux_model_name))
             {
               max_lag = var_model_table.getMaxLag(aux_model_name);
               lhs = var_model_table.getLhs(aux_model_name);
               nonstationary = var_model_table.getNonstationary(aux_model_name);
             }
           else
             {
               cerr << "Error: aux_model_name not recognized as VAR model or Trend Component model"
                    << endl;
               exit(EXIT_FAILURE);
             }
           pms->fillUndiffedLHS(lhs);
           dynamic_model.walkPacParameters();
           int pac_max_lag = original_model.getPacMaxLag(pac_model_name);
           dynamic_model.fillPacExpectationVarInfo(pac_model_name, lhs, max_lag,
                                                   pac_max_lag, nonstationary, growth_symb_id);
           dynamic_model.substitutePacExpectation();
         }
     }

  dynamic_model.addEquationsForVar();

  if (symbol_table.predeterminedNbr() > 0)
    dynamic_model.transformPredeterminedVariables();

  // Create auxiliary vars for Expectation operator
  dynamic_model.substituteExpectation(mod_file_struct.partial_information);

  if (nonstationary_variables)
    {
      dynamic_model.detrendEquations();
      dynamic_model.cloneDynamic(trend_dynamic_model);
      dynamic_model.removeTrendVariableFromEquations();
    }

  mod_file_struct.orig_eq_nbr = dynamic_model.equation_number();
  if (mod_file_struct.ramsey_model_present)
    {
      PlannerObjectiveStatement *pos = nullptr;
      for (auto & statement : statements)
        {
          auto pos2 = dynamic_cast<PlannerObjectiveStatement *>(statement.get());
          if (pos2 != nullptr)
            if (pos != nullptr)
              {
                cerr << "ERROR: there can only be one planner_objective statement" << endl;
                exit(EXIT_FAILURE);
              }
            else
              pos = pos2;
        }
      assert(pos != nullptr);
      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)
        dynamic_model.cloneDynamic(orig_ramsey_dynamic_model);
      dynamic_model.cloneDynamic(ramsey_FOC_equations_dynamic_model);
      ramsey_FOC_equations_dynamic_model.computeRamseyPolicyFOCs(planner_objective, nopreprocessoroutput);
      ramsey_FOC_equations_dynamic_model.replaceMyEquations(dynamic_model);
      mod_file_struct.ramsey_eq_nbr = dynamic_model.equation_number() - mod_file_struct.orig_eq_nbr;
    }

  // Workaround for #1193
  if (!mod_file_struct.hist_vals_wrong_lag.empty())
    {
      bool err = false;
      for (map<int, int>::const_iterator it = mod_file_struct.hist_vals_wrong_lag.begin();
           it != mod_file_struct.hist_vals_wrong_lag.end(); it++)
          if (dynamic_model.minLagForSymbol(it->first) > it->second - 1)
            {
              cerr << "ERROR: histval: variable " << symbol_table.getName(it->first)
                   << " does not appear in the model with the lag " << it->second - 1
                   << " (see the reference manual for the timing convention in 'histval')" << endl;
              err = true;
            }
      if (err)
        exit(EXIT_FAILURE);
    }

  /* 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 = trend_component_model_table.getLhs(vems->aux_model_name);
        }
      else
        {
          cerr << "ERROR: var_expectation_model " << model_name
               << " refers to nonexistent auxiliary model " << vems->aux_model_name << endl;
          exit(EXIT_FAILURE);
        }

      /* 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);

  if (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
      || stochastic )
    {
      // In stochastic models, create auxiliary vars for leads and lags greater than 2, on both endos and exos
      dynamic_model.substituteEndoLeadGreaterThanTwo(false);
      dynamic_model.substituteExoLead(false);
      dynamic_model.substituteEndoLagGreaterThanTwo(false);
      dynamic_model.substituteExoLag(false);
    }
  else
    {
      // In deterministic models, create auxiliary vars for leads and lags endogenous greater than 2, only on endos (useless on exos)
      dynamic_model.substituteEndoLeadGreaterThanTwo(true);
      dynamic_model.substituteEndoLagGreaterThanTwo(true);
    }

  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);
      }

  // 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)
      && !(mod_file_struct.occbin_option)
      && (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.ramsey_policy_present)
    for (auto & statement : statements)
      {
        auto *rps = dynamic_cast<RamseyPolicyStatement *>(statement.get());
        if (rps != nullptr)
          rps->checkRamseyPolicyList();
      }

  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 (!nopreprocessoroutput)
    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, FileOutputType output, int params_derivs_order, const bool nopreprocessoroutput)
{
  // 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
      dynamic_model.toStatic(static_model);
	  if (linear_decomposition)
        {
          dynamic_model.cloneDynamic(non_linear_equations_dynamic_model);
          non_linear_equations_dynamic_model.set_cutoff_to_zero();
          non_linear_equations_dynamic_model.computingPass(true, false, false, 0, global_eval_context, no_tmp_terms, block, use_dll, byte_code, nopreprocessoroutput, linear_decomposition);
        }
      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)
            static_model.set_cutoff_to_zero();

          const bool static_hessian = mod_file_struct.identification_present
            || mod_file_struct.estimation_analytic_derivation;
          int paramsDerivsOrder = 0;
          if (mod_file_struct.identification_present || mod_file_struct.estimation_analytic_derivation)
            paramsDerivsOrder = params_derivs_order;
          static_model.computingPass(global_eval_context, no_tmp_terms, static_hessian,
                                     false, paramsDerivsOrder, block, byte_code, nopreprocessoroutput);
        }
      // 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)
        {
          if (mod_file_struct.perfect_foresight_solver_present)
            dynamic_model.computingPass(true, false, false, 0, global_eval_context, no_tmp_terms, block, use_dll, byte_code, nopreprocessoroutput, linear_decomposition);
          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)
                dynamic_model.set_cutoff_to_zero();
              if (mod_file_struct.order_option < 1 || mod_file_struct.order_option > 3)
                {
                  cerr << "ERROR: Incorrect order option..." << endl;
                  exit(EXIT_FAILURE);
                }
              bool hessian = mod_file_struct.order_option >= 2
                || mod_file_struct.identification_present
                || mod_file_struct.estimation_analytic_derivation
                || linear
                || output == FileOutputType::second
                || output == FileOutputType::third;
              bool thirdDerivatives = mod_file_struct.order_option == 3
                || mod_file_struct.estimation_analytic_derivation
                || output == FileOutputType::third;
              int paramsDerivsOrder = 0;
              if (mod_file_struct.identification_present || mod_file_struct.estimation_analytic_derivation)
                paramsDerivsOrder = params_derivs_order;
              dynamic_model.computingPass(true, hessian, thirdDerivatives, paramsDerivsOrder, global_eval_context, no_tmp_terms, block, use_dll, byte_code, nopreprocessoroutput, linear_decomposition);
              if (linear && mod_file_struct.ramsey_model_present)
                orig_ramsey_dynamic_model.computingPass(true, true, false, paramsDerivsOrder, global_eval_context, no_tmp_terms, block, use_dll, byte_code, nopreprocessoroutput, linear_decomposition);
            }
        }
      else // No computing task requested, compute derivatives up to 2nd order by default
        dynamic_model.computingPass(true, true, false, 0, global_eval_context, no_tmp_terms, block, use_dll, byte_code, nopreprocessoroutput, linear_decomposition);

      map<int, string> eqs;
      if (mod_file_struct.ramsey_model_present)
        orig_ramsey_dynamic_model.setNonZeroHessianEquations(eqs);
      else
        dynamic_model.setNonZeroHessianEquations(eqs);

      if (linear && !eqs.empty())
        {
          cerr << "ERROR: If the model is declared linear the second derivatives must be equal to zero." << endl
               << "       The following equations had non-zero second derivatives:" << endl;
          for (map<int, string >::const_iterator it = eqs.begin(); it != eqs.end(); it++)
            {
              cerr << "       * Eq # " << it->first+1;
              if (!it->second.empty())
                cerr << " [" << it->second << "]";
              cerr << endl;
            }
          exit(EXIT_FAILURE);
        }
    }

  for (auto & statement : statements)
    statement->computingPass();

  epilogue.computingPass(true, true, false, 0, global_eval_context, true, false, false, false, true, false);
}

void
ModFile::writeOutputFiles(const string &basename, bool clear_all, bool clear_global, bool no_log, bool no_warn,
                          bool console, bool nograph, bool nointeractive, const ConfigFile &config_file,
                          bool check_model_changes, bool minimal_workspace, bool compute_xrefs
#if defined(_WIN32) || defined(__CYGWIN32__)
                          , bool cygwin, bool msvc, bool mingw
#endif
                          , const bool nopreprocessoroutput
                          ) const
{
  bool hasModelChanged = !dynamic_model.isChecksumMatching(basename, block);
  if (!check_model_changes)
    hasModelChanged = true;

  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. */
      if (boost::filesystem::exists("+" + basename))
	{
	  auto tmp = boost::filesystem::unique_path();
	  boost::filesystem::rename("+" + basename, tmp);
	  boost::filesystem::remove_all(tmp);
	}
      boost::filesystem::remove_all(basename + "/model/src");
      boost::filesystem::remove_all(basename + "/model/bytecode");
    }

  ofstream mOutputFile;

  if (basename.size())
    {
      boost::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;

  mOutputFile << "tic0 = tic;" << endl
              << "% 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;
  config_file.writeHooks(mOutputFile);
  mOutputFile << "global_initialization;" << endl
              << "diary off;" << endl;
  if (!no_log)
    mOutputFile << "diary('" << basename << ".log');" << endl;

  if (minimal_workspace)
    mOutputFile << "options_.minimal_workspace = 1;" << endl;

  if (console)
    mOutputFile << "options_.console_mode = 1;" << endl
                << "options_.nodisplay = 1;" << endl;
  if (nograph)
    mOutputFile << "options_.nograph = 1;" << endl;

  if (nointeractive)
    mOutputFile << "options_.nointeractive = 1;" << endl;

  if (param_used_with_lead_lag)
    mOutputFile << "M_.parameter_used_with_lead_lag = true;" << endl;

  if (!nopreprocessoroutput)
    cout << "Processing outputs ..." << endl;

  symbol_table.writeOutput(mOutputFile);

  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 = 1;" << endl;

  // Initialize M_.det_shocks
  mOutputFile << "M_.det_shocks = [];" << endl;

  if (linear == 1)
    mOutputFile << "options_.linear = 1;" << endl;

  mOutputFile << "options_.block=" << block << ";" << endl
              << "options_.bytecode=" << byte_code << ";" << endl
              << "options_.use_dll=" << use_dll << ";" << endl
              << "options_.linear_decomposition=" << linear_decomposition << ";" << endl;

  if (parallel_local_files.size() > 0)
    {
      mOutputFile << "options_.parallel_info.local_files = {" << endl;
      for (const auto & parallel_local_file : parallel_local_files)
        {
          size_t j = parallel_local_file.find_last_of("/\\");
          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;
    }

  mOutputFile << "M_.nonzero_hessian_eqs = ";
  if (mod_file_struct.ramsey_model_present)
    orig_ramsey_dynamic_model.printNonZeroHessianEquations(mOutputFile);
  else
    dynamic_model.printNonZeroHessianEquations(mOutputFile);
  mOutputFile << ";" << endl
              << "M_.hessian_eq_zero = isempty(M_.nonzero_hessian_eqs);" << endl;

  config_file.writeCluster(mOutputFile);

  if (byte_code)
    mOutputFile << "if exist('bytecode') ~= 3" << endl
                << "  error('DYNARE: Can''t find bytecode DLL. Please compile it or remove the ''bytecode'' option.')" << endl
                << "end" << endl;

  // Compile the dynamic MEX file for use_dll option
  // When check_model_changes is true, don't force compile if MEX is fresher than source
  if (use_dll)
    {
#if defined(_WIN32) || defined(__CYGWIN32__)
      if (msvc)
        // MATLAB/Windows + Microsoft Visual C++
        mOutputFile << "dyn_mex('msvc', '" << basename << "', " << !check_model_changes << ")" <<  endl;
      else if (cygwin)
        // MATLAB/Windows + Cygwin g++
        mOutputFile << "dyn_mex('cygwin', '" << basename << "', " << !check_model_changes << ")" << endl;
      else if (mingw)
        // MATLAB/Windows + MinGW g++
        mOutputFile << "dyn_mex('mingw', '" << basename << "', " << !check_model_changes << ")" << endl;
      else
        mOutputFile << "if isoctave" << endl
                    << "    dyn_mex('', '" << basename << "', " << !check_model_changes << ")" << endl
                    << "else" << endl
                    << "    error('When using the USE_DLL option on Matlab, you must give the ''cygwin'', ''msvc'', or ''mingw'' option to the ''dynare'' command')" << endl
                    << "end" << endl;
#else
      // other configurations
      mOutputFile << "dyn_mex('', '" << basename << "', " << !check_model_changes << ")" << endl;
#endif
    }

  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;

  if (dynamic_model.equation_number() > 0)
    {
      if (linear_decomposition)
        non_linear_equations_dynamic_model.writeOutput(mOutputFile, basename, block, true, byte_code, use_dll, mod_file_struct.order_option, mod_file_struct.estimation_present, compute_xrefs, false);
      dynamic_model.writeOutput(mOutputFile, basename, block, false, byte_code, use_dll, mod_file_struct.order_option, mod_file_struct.estimation_present, compute_xrefs, false);
      if (!no_static)
        static_model.writeOutput(mOutputFile, block);
    }

  for (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 */
      auto ivs = dynamic_cast<InitValStatement *>(statement.get());
      if (ivs != nullptr)
        {
          static_model.writeAuxVarInitval(mOutputFile, ExprNodeOutputType::matlabOutsideModel);
          ivs->writeOutputPostInit(mOutputFile);
        }

      // Special treatment for endval block: insert initial values for the auxiliary variables
      auto evs = dynamic_cast<EndValStatement *>(statement.get());
      if (evs != nullptr)
        static_model.writeAuxVarInitval(mOutputFile, ExprNodeOutputType::matlabOutsideModel);

      // Special treatment for load params and steady state statement: insert initial values for the auxiliary variables
      auto lpass = dynamic_cast<LoadParamsAndSteadyStateStatement *>(statement.get());
      if (lpass && !no_static)
        static_model.writeAuxVarInitval(mOutputFile, ExprNodeOutputType::matlabOutsideModel);
    }

  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);

  mOutputFile << endl << endl
              << "disp(['Total computing time : ' dynsec2hms(toc(tic0)) ]);" << endl;

  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;
    }

  if (!no_log)
    mOutputFile << "diary off" << endl;

  mOutputFile.close();

  if (hasModelChanged)
    {
      // Create static and dynamic files
      if (dynamic_model.equation_number() > 0)
        {
          if (!no_static)
            {
              static_model.writeStaticFile(basename, block, byte_code, use_dll, false);
              static_model.writeParamsDerivativesFile(basename, false);
            }

          if (linear_decomposition)
            {
              non_linear_equations_dynamic_model.writeDynamicFile(basename, block, linear_decomposition, byte_code, use_dll, mod_file_struct.order_option, false);
              non_linear_equations_dynamic_model.writeParamsDerivativesFile(basename, false);
            }

          dynamic_model.writeDynamicFile(basename, block, false, byte_code, use_dll, mod_file_struct.order_option, false);

          dynamic_model.writeParamsDerivativesFile(basename, false);
        }

      // Create steady state file
      steady_state_model.writeSteadyStateFile(basename, mod_file_struct.ramsey_model_present, false);

      // Create epilogue file
      epilogue.writeEpilogueFile(basename);
    }

  if (!nopreprocessoroutput)
    cout << "done" << endl;
}

void
ModFile::writeExternalFiles(const string &basename, FileOutputType output, LanguageOutputType language, const bool nopreprocessoroutput) const
{
  switch (language)
    {
    case LanguageOutputType::julia:
      writeExternalFilesJulia(basename, output, nopreprocessoroutput);
      break;
    default:
      cerr << "This case shouldn't happen. Contact the authors of Dynare" << endl;
      exit(EXIT_FAILURE);
    }
}

void
ModFile::writeExternalFilesJulia(const string &basename, FileOutputType output, const bool nopreprocessoroutput) const
{
  ofstream jlOutputFile;
  if (basename.size())
    {
      string fname(basename);
      fname += ".jl";
      jlOutputFile.open(fname, ios::out | ios::binary);
      if (!jlOutputFile.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);
    }

  jlOutputFile << "module " << basename << endl
               << "#" << endl
               << "# NB: this file was automatically generated by Dynare" << endl
               << "#     from " << basename << ".mod" << endl
               << "#" << endl << endl
               << "using DynareModel" << endl
               << "using DynareOptions" << endl
               << "using DynareOutput" << endl << endl
               << "using Utils" << endl
               << "using SteadyState" << endl << endl
               << "using " << basename << "Static" << endl
               << "using " << basename << "Dynamic" << endl
               << "if isfile(\"" << basename << "SteadyState.jl"  "\")" << endl
               << "    using " << basename << "SteadyState" << endl
               << "end" << endl
               << "if isfile(\"" << basename << "SteadyState2.jl"  "\")" << endl
               << "    using " << basename << "SteadyState2" << endl
               << "end" << endl << endl
               << "export model_, options_, oo_" << endl;

  // Write Output
  jlOutputFile << endl
               << "oo_ = dynare_output()" << endl
               << "oo_.dynare_version = \"" << PACKAGE_VERSION << "\"" << endl;

  // Write Options
  jlOutputFile << endl
               << "options_ = dynare_options()" << endl
               << "options_.dynare_version = \"" << PACKAGE_VERSION << "\"" << endl;
  if (linear == 1)
    jlOutputFile << "options_.linear = true" << endl;

  // Write Model
  jlOutputFile << endl
               << "model_ = dynare_model()" << endl
               << "model_.fname = \"" << basename << "\"" << endl
               << "model_.dynare_version = \"" << PACKAGE_VERSION << "\"" << endl
               << "model_.sigma_e = zeros(Float64, " << symbol_table.exo_nbr() << ", "
               << symbol_table.exo_nbr() << ")" << endl
               << "model_.correlation_matrix = ones(Float64, " << symbol_table.exo_nbr() << ", "
               << symbol_table.exo_nbr() << ")" << endl
               << "model_.orig_eq_nbr = " << mod_file_struct.orig_eq_nbr << endl
               << "model_.eq_nbr = " << dynamic_model.equation_number() << endl
               << "model_.ramsey_eq_nbr = " << mod_file_struct.ramsey_eq_nbr << endl;

  if (mod_file_struct.calibrated_measurement_errors)
    jlOutputFile << "model_.h = zeros(Float64,"
                 << symbol_table.observedVariablesNbr() << ", "
                 << symbol_table.observedVariablesNbr() << ");" << endl
                 << "model_.correlation_matrix_me = ones(Float64, "
                 << symbol_table.observedVariablesNbr() << ", "
                 << symbol_table.observedVariablesNbr() << ");" << endl;
  else
    jlOutputFile << "model_.h = zeros(Float64, 1, 1)" << endl
                 << "model_.correlation_matrix_me = ones(Float64, 1, 1)" << endl;

  if (!nopreprocessoroutput)
    cout << "Processing outputs ..." << endl;
  symbol_table.writeJuliaOutput(jlOutputFile);

  if (dynamic_model.equation_number() > 0)
    {
      dynamic_model.writeOutput(jlOutputFile, basename, false, false, false, false,
                                mod_file_struct.order_option,
                                mod_file_struct.estimation_present, false, true);
      if (!no_static)
        {
          static_model.writeStaticFile(basename, false, false, false, true);
          static_model.writeParamsDerivativesFile(basename, true);
        }
      dynamic_model.writeDynamicFile(basename, block, linear_decomposition, byte_code, use_dll,
                                     mod_file_struct.order_option, true);
      dynamic_model.writeParamsDerivativesFile(basename, true);
    }
  steady_state_model.writeSteadyStateFile(basename, mod_file_struct.ramsey_model_present, true);

  // Print statements (includes parameter values)
  for (auto &statement : statements)
    statement->writeJuliaOutput(jlOutputFile, basename);

  jlOutputFile << "model_.static = " << basename << "Static.static!" << endl
               << "model_.dynamic = " << basename << "Dynamic.dynamic!" << endl
               << "model_.temporaries.static = " << basename << "Static.tmp_nbr" << endl
               << "model_.temporaries.dynamic = " << basename << "Dynamic.tmp_nbr" << endl
               << "if isfile(\"" << basename << "SteadyState.jl"  "\")" << endl
               << "    model_.user_written_analytical_steady_state = true" << endl
               << "    model_.steady_state = " << basename << "SteadyState.steady_state!" << endl
               << "end" << endl
               << "if isfile(\"" << basename << "SteadyState2.jl"  "\")" << endl
               << "    model_.analytical_steady_state = true" << endl
               << "    model_.steady_state = " << basename << "SteadyState2.steady_state!" << endl
               << "end" << endl
               << "if isfile(\"" << basename << "StaticParamsDerivs.jl"  "\")" << endl
               << "    using " << basename << "StaticParamsDerivs" << endl
               << "    model_.static_params_derivs = " << basename << "StaticParamsDerivs.params_derivs" << endl
               << "end" << endl
               << "if isfile(\"" << basename << "DynamicParamsDerivs.jl"  "\")" << endl
               << "    using " << basename << "DynamicParamsDerivs" << endl
               << "    model_.dynamic_params_derivs = " << basename << "DynamicParamsDerivs.params_derivs" << endl
               << "end" << endl
               << "end" << endl;
  jlOutputFile.close();
  if (!nopreprocessoroutput)
    cout << "done" << endl;
}

void
ModFile::writeJsonOutput(const string &basename, JsonOutputPointType json, JsonFileOutputType json_output_mode, bool onlyjson, const bool nopreprocessoroutput, 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;

  if (!nopreprocessoroutput)
    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 << ", \"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);
      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 << "\"transformed_modfile\": ";
      else
        cout << "\"modfile\": ";
      cout << output.str();
      if (!original_model_output.str().empty())
        cout << ", \"original_model\": " << original_model_output.str();
      if (!steady_state_model_output.str().empty())
        cout << ", \"steady_state_model\": " << steady_state_model_output.str();
    }
  else
    {
      ofstream jsonOutputFile;

      if (basename.size())
        {
          boost::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 << "}";

  tmp_out << "";
  static_paramsd_output << "";
  static_model.writeJsonParamsDerivativesFile(tmp_out, !jsonderivsimple);
  if (!tmp_out.str().empty())
    static_paramsd_output << "{" << tmp_out.str() << "}" << endl;

  tmp_out.str("");
  dynamic_paramsd_output << "";
  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 << ", \"static_model\": " << static_output.str() << endl
           << ", \"dynamic_model\": " << dynamic_output.str() << endl;

      if (!static_paramsd_output.str().empty())
        cout << ", \"static_params_deriv\": " << static_paramsd_output.str() << endl;

      if (!dynamic_paramsd_output.str().empty())
        cout << ", \"dynamic_params_deriv\": " << dynamic_paramsd_output.str() << endl;
    }
  else
    {
      boost::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();
}