Removed trailing whitespaces.
Stéphane Adjemian (Charybdis)
parent
893d2ca2b2
commit
49b286957e
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doc/dynare.texi
334
doc/dynare.texi
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@ -91,123 +91,123 @@ This is Dynare Reference Manual, version @value{VERSION}.
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@end ifnottex
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@menu
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* Introduction::
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* Installation and configuration::
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* Dynare invocation::
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* The Model file::
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* The Configuration File::
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* Examples::
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* Bibliography::
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* Command and Function Index::
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* Variable Index::
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* Introduction::
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* Installation and configuration::
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* Dynare invocation::
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* The Model file::
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* The Configuration File::
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* Examples::
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* Bibliography::
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* Command and Function Index::
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* Variable Index::
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@detailmenu
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--- The Detailed Node Listing ---
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Introduction
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* What is Dynare ?::
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* Documentation sources::
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* Citing Dynare in your research::
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* What is Dynare ?::
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* Documentation sources::
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* Citing Dynare in your research::
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Installation and configuration
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* Software requirements::
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* Installation of Dynare::
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* Configuration::
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* Software requirements::
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* Installation of Dynare::
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* Configuration::
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Installation of Dynare
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* On Windows::
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* On Debian GNU/Linux and Ubuntu::
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* On Mac OS X::
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* For other systems::
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* On Windows::
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* On Debian GNU/Linux and Ubuntu::
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* On Mac OS X::
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* For other systems::
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Configuration
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* For MATLAB::
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* For GNU Octave::
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* Some words of warning::
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* For MATLAB::
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* For GNU Octave::
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* Some words of warning::
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The Model file
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* Conventions::
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* Variable declarations::
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* Expressions::
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* Parameter initialization::
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* Model declaration::
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* Auxiliary variables::
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* Initial and terminal conditions::
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* Shocks on exogenous variables::
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* Other general declarations::
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* Steady state::
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* Getting information about the model::
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* Deterministic simulation::
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* Stochastic solution and simulation::
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* Estimation::
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* Forecasting::
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* Optimal policy::
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* Sensitivity and identification analysis::
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* Displaying and saving results::
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* Macro-processing language::
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* Misc commands::
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* Conventions::
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* Variable declarations::
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* Expressions::
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* Parameter initialization::
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* Model declaration::
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* Auxiliary variables::
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* Initial and terminal conditions::
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* Shocks on exogenous variables::
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* Other general declarations::
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* Steady state::
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* Getting information about the model::
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* Deterministic simulation::
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* Stochastic solution and simulation::
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* Estimation::
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* Forecasting::
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* Optimal policy::
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* Sensitivity and identification analysis::
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* Displaying and saving results::
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* Macro-processing language::
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* Misc commands::
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Expressions
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* Parameters and variables::
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* Operators::
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* Functions::
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* Parameters and variables::
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* Operators::
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* Functions::
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Parameters and variables
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* Inside the model::
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* Outside the model::
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* Inside the model::
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* Outside the model::
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Functions
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* Built-in Functions::
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* External Functions::
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* Built-in Functions::
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* External Functions::
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Steady state
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* Finding the steady state with Dynare nonlinear solver::
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* Using a steady state file::
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* Finding the steady state with Dynare nonlinear solver::
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* Using a steady state file::
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Stochastic solution and simulation
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* Computing the stochastic solution::
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* Typology and ordering of variables::
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* First order approximation::
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* Second order approximation::
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* Third order approximation::
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* Computing the stochastic solution::
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* Typology and ordering of variables::
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* First order approximation::
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* Second order approximation::
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* Third order approximation::
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Sensitivity and identification analysis
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* Sampling::
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* Stability Mapping::
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* Reduced Form Mapping::
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* RMSE::
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* Screening Analysis::
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* Identification Analysis::
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* Performing Sensitivity and Identification Analysis::
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* Sampling::
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* Stability Mapping::
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* Reduced Form Mapping::
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* RMSE::
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* Screening Analysis::
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* Identification Analysis::
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* Performing Sensitivity and Identification Analysis::
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Macro-processing language
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* Macro expressions::
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* Macro directives::
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* Typical usages::
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* MATLAB/Octave loops versus macro-processor loops::
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* Macro expressions::
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* Macro directives::
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* Typical usages::
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* MATLAB/Octave loops versus macro-processor loops::
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Typical usages
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* Modularization::
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* Indexed sums or products::
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* Multi-country models::
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* Endogeneizing parameters::
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* Modularization::
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* Indexed sums or products::
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* Multi-country models::
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* Endogeneizing parameters::
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The Configuration File
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* Parallel Configuration::
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* Parallel Configuration::
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@end detailmenu
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@end menu
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@ -216,9 +216,9 @@ The Configuration File
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@chapter Introduction
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@menu
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* What is Dynare ?::
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* Documentation sources::
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* Citing Dynare in your research::
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* What is Dynare ?::
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* Documentation sources::
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* Citing Dynare in your research::
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@end menu
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@node What is Dynare ?
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@ -339,9 +339,9 @@ If you want to give a URL, use the address of the Dynare website:
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@chapter Installation and configuration
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@menu
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* Software requirements::
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* Installation of Dynare::
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* Configuration::
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* Software requirements::
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* Installation of Dynare::
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* Configuration::
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@end menu
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@node Software requirements
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@ -355,7 +355,7 @@ steps are necessary in that case.
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In order to run Dynare, you need at least one of the following:
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@itemize
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@itemize
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@item
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MATLAB version 7.0 (R14) or above; note that no toolbox is needed by
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@ -396,10 +396,10 @@ upgrade Dynare and discard the previous version without having to worry
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about your own files.
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@menu
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* On Windows::
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* On Debian GNU/Linux and Ubuntu::
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* On Mac OS X::
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* For other systems::
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* On Windows::
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* On Debian GNU/Linux and Ubuntu::
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* On Mac OS X::
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* For other systems::
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@end menu
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@node On Windows
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@ -465,9 +465,9 @@ Wiki}.
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@section Configuration
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@menu
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* For MATLAB::
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* For GNU Octave::
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* Some words of warning::
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* For MATLAB::
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* For GNU Octave::
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* Some words of warning::
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@end menu
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@node For MATLAB
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@ -476,7 +476,7 @@ Wiki}.
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You need to add the @file{matlab} subdirectory of your Dynare
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installation to MATLAB path. You have two options for doing that:
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@itemize
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@itemize
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@item
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Using the @code{addpath} command in the MATLAB command window:
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@ -724,7 +724,7 @@ in a file called @file{@var{FILENAME}_results.mat}.
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@example
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dynare ramst
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dynare ramst.mod savemacro
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dynare ramst.mod savemacro
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@end example
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@end deffn
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@ -749,26 +749,26 @@ Structure containing the various results of the computations.
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@chapter The Model file
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@menu
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* Conventions::
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* Variable declarations::
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* Expressions::
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* Parameter initialization::
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* Model declaration::
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* Auxiliary variables::
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* Initial and terminal conditions::
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* Shocks on exogenous variables::
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* Other general declarations::
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* Steady state::
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* Getting information about the model::
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* Deterministic simulation::
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* Stochastic solution and simulation::
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* Estimation::
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* Forecasting::
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* Optimal policy::
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* Sensitivity and identification analysis::
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* Displaying and saving results::
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* Macro-processing language::
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* Misc commands::
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* Conventions::
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* Variable declarations::
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* Expressions::
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* Parameter initialization::
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* Model declaration::
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* Auxiliary variables::
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* Initial and terminal conditions::
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* Shocks on exogenous variables::
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* Other general declarations::
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* Steady state::
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* Getting information about the model::
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* Deterministic simulation::
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* Stochastic solution and simulation::
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* Estimation::
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* Forecasting::
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* Optimal policy::
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* Sensitivity and identification analysis::
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* Displaying and saving results::
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* Macro-processing language::
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* Misc commands::
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@end menu
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@node Conventions
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@ -785,7 +785,7 @@ are separated by commas.
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In the description of Dynare commands, the following conventions are
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observed:
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@itemize
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@itemize
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@item
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optional arguments or options are indicated between square brackets:
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@ -933,7 +933,7 @@ Dynare will concatenate them.
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varexo m gov;
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varexo_det tau;
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@end example
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@end deffn
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@ -1020,7 +1020,7 @@ the beginning of the period'' convention.
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The following two program snippets are strictly equivalent.
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@emph{Using default Dynare timing convention:}
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@emph{Using default Dynare timing convention:}
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@example
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var y, k, i;
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@ -1032,7 +1032,7 @@ k = i + (1-delta)*k(-1);
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end;
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@end example
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@emph{Using the alternative timing convention:}
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@emph{Using the alternative timing convention:}
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@example
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var y, k, i;
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@ -1114,9 +1114,9 @@ Represents infinity.
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@end deffn
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@menu
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* Parameters and variables::
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* Operators::
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* Functions::
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* Parameters and variables::
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* Operators::
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* Functions::
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@end menu
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@node Parameters and variables
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@ -1127,8 +1127,8 @@ typing their names. The semantics of parameters and variables is quite
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different whether they are used inside or outside the model block.
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@menu
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* Inside the model::
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* Outside the model::
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* Inside the model::
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* Outside the model::
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@end menu
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@node Inside the model
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@ -1177,7 +1177,7 @@ the value given in the most recent @code{initval} or @code{endval} block.
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The following operators are allowed in both @var{MODEL_EXPRESSION} and
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@var{EXPRESSION}:
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@itemize
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@itemize
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@item
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binary arithmetic operators: @code{+}, @code{-}, @code{*}, @code{/}, @code{^}
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@ -1215,8 +1215,8 @@ internally and how this affects the output.
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@subsection Functions
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@menu
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* Built-in Functions::
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* External Functions::
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* Built-in Functions::
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* External Functions::
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@end menu
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@node Built-in Functions
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@ -1566,7 +1566,7 @@ appended to the variable names, as LaTeX subscripts.
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Note that the model written in the TeX file will differ from the model
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declared by the user in the following dimensions:
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@itemize
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@itemize
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@item
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the timing convention of predetermined variables
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@ -1762,7 +1762,7 @@ This steady state will be used as the initial condition at all the
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periods preceeding the first simulation period for the two possible
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types of simulations in stochastic mode:
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@itemize
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@itemize
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@item
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in @code{stoch_simul}, if the @code{periods} options is specified
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@ -1922,7 +1922,7 @@ and the number of lags of the model (for example, with 50 simulation
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periods, in a model with 2 lags and 1 lead, the paths must have a
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length of 53). Note that these paths cover two different things:
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@itemize
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@itemize
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@item
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the constraints of the problem, which are given by the path for
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@ -1936,7 +1936,7 @@ initial and terminal conditions)
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The command accepts three file formats:
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@itemize
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@itemize
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@item
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M-file (extension @file{.m}): for each endogenous and exogenous
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@ -1998,7 +1998,7 @@ The block should contain one or more occurrences of the following
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group of three lines:
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@example
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var @var{VARIABLE_NAME};
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var @var{VARIABLE_NAME};
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periods @var{INTEGER}[:@var{INTEGER}] [[,] @var{INTEGER}[:@var{INTEGER}]]@dots{};
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values @var{DOUBLE} | (@var{EXPRESSION}) [[,] @var{DOUBLE} | (@var{EXPRESSION}) ]@dots{};
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@end example
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@ -2120,7 +2120,7 @@ The syntax is the same than @code{shocks} in a deterministic context.
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This command is only meaningful in two situations:
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@itemize
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@itemize
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@item
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on exogenous variables with a non-zero steady state, in a deterministic setup,
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@ -2207,8 +2207,8 @@ give more guidance to Dynare, using your knowledge of the model, by
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providing it with a ``steady state file''.
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@menu
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* Finding the steady state with Dynare nonlinear solver::
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* Using a steady state file::
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* Finding the steady state with Dynare nonlinear solver::
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* Using a steady state file::
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@end menu
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@node Finding the steady state with Dynare nonlinear solver
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@ -2332,7 +2332,7 @@ variable:
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Contains the computed steady state.
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Endogenous variables are ordered in order of declaration used in
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@code{var} command (which is also the order used in @code{M_.endo_names}).
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@code{var} command (which is also the order used in @code{M_.endo_names}).
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@end defvr
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@ -2490,7 +2490,7 @@ steady_state_model;
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dA = exp(gam);
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gst = 1/dA; // A temporary variable
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m = mst;
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// Three other temporary variables
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khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
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xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
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@ -2508,7 +2508,7 @@ steady_state_model;
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// You can use MATLAB functions which return several arguments
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[W, e] = my_function(l, n);
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gp_obs = m/dA;
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gy_obs = dA;
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end;
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@ -2567,7 +2567,7 @@ command.
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This command provides information about:
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@itemize
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@itemize
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@item
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the normalization of the model: an endogenous variable is attributed
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@ -2758,11 +2758,11 @@ details of the Dynare implementation of the first order solution are
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given in @cite{Villemot (2011)}.
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@menu
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* Computing the stochastic solution::
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* Typology and ordering of variables::
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* First order approximation::
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* Second order approximation::
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* Third order approximation::
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* Computing the stochastic solution::
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* Typology and ordering of variables::
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* First order approximation::
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* Second order approximation::
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* Third order approximation::
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@end menu
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@node Computing the stochastic solution
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@ -2838,7 +2838,7 @@ Transform used in the HP filter computation. It may be necessary to
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increase it for highly autocorrelated processes. Default: @code{512}.
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@item irf = @var{INTEGER}
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@anchor{irf}
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@anchor{irf}
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Number of periods on which to compute the IRFs. Setting @code{irf=0},
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suppresses the plotting of IRF's. Default: @code{40}.
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@ -3120,7 +3120,7 @@ where @math{y^s} is the steady state value of @math{y} and
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The coefficients of the decision rules are stored as follows:
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@itemize
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@itemize
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@item
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@vindex oo_.dr.ys
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@ -3158,7 +3158,7 @@ variance of future shocks.
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The coefficients of the decision rules are stored in the variables
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described for first order approximation, plus the following variables:
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@itemize
|
||||
@itemize
|
||||
|
||||
@item
|
||||
@vindex oo_.dr.ghs2
|
||||
|
|
@ -3204,7 +3204,7 @@ M_.exo_nbr}.
|
|||
|
||||
The coefficients of the decision rules are stored as follows:
|
||||
|
||||
@itemize
|
||||
@itemize
|
||||
|
||||
@item
|
||||
@vindex oo_.dr.ys
|
||||
|
|
@ -3530,7 +3530,7 @@ stderr VARIABLE_NAME | corr VARIABLE_NAME_1, VARIABLE_NAME_2 | PARAMETER_NAME
|
|||
This command runs Bayesian or maximum likelihood estimation.
|
||||
|
||||
The following information will be displayed by the command:
|
||||
@itemize
|
||||
@itemize
|
||||
|
||||
@item
|
||||
results from posterior optimization (also for maximum likelihood)
|
||||
|
|
@ -3941,7 +3941,7 @@ Lower bound of a 90% HPD interval@footnote{See option @ref{conf_sig}
|
|||
to change the size of the HPD interval}
|
||||
|
||||
@item HPDsup
|
||||
Upper bound of a 90% HPD interval
|
||||
Upper bound of a 90% HPD interval
|
||||
|
||||
@item Mean
|
||||
Mean of the posterior distribution
|
||||
|
|
@ -4280,7 +4280,7 @@ end;
|
|||
|
||||
stoch_simul(irf=0);
|
||||
|
||||
forecast;
|
||||
forecast;
|
||||
@end example
|
||||
|
||||
@end deffn
|
||||
|
|
@ -4618,13 +4618,13 @@ Sensitivity analysis results are saved locally in @code{<mod_file>/GSA},
|
|||
where @code{<mod_file>.mod} is the name of the DYNARE model file.
|
||||
|
||||
@menu
|
||||
* Sampling::
|
||||
* Stability Mapping::
|
||||
* Reduced Form Mapping::
|
||||
* RMSE::
|
||||
* Screening Analysis::
|
||||
* Identification Analysis::
|
||||
* Performing Sensitivity and Identification Analysis::
|
||||
* Sampling::
|
||||
* Stability Mapping::
|
||||
* Reduced Form Mapping::
|
||||
* RMSE::
|
||||
* Screening Analysis::
|
||||
* Identification Analysis::
|
||||
* Performing Sensitivity and Identification Analysis::
|
||||
@end menu
|
||||
|
||||
@node Sampling
|
||||
|
|
@ -5302,10 +5302,10 @@ types: integer, character string, array of integers, array of
|
|||
strings.
|
||||
|
||||
@menu
|
||||
* Macro expressions::
|
||||
* Macro directives::
|
||||
* Typical usages::
|
||||
* MATLAB/Octave loops versus macro-processor loops::
|
||||
* Macro expressions::
|
||||
* Macro directives::
|
||||
* Typical usages::
|
||||
* MATLAB/Octave loops versus macro-processor loops::
|
||||
@end menu
|
||||
|
||||
@node Macro expressions
|
||||
|
|
@ -5434,7 +5434,7 @@ end;
|
|||
@deffn {Macro directive} @@#if @var{MACRO_EXPRESSION}
|
||||
@deffnx {Macro directive} @@#else
|
||||
@deffnx {Macro directive} @@#endif
|
||||
Conditional inclusion of some part of the @file{.mod} file.
|
||||
Conditional inclusion of some part of the @file{.mod} file.
|
||||
The lines between @code{@@#if} and the next @code{@@#else} or
|
||||
@code{@@#end} is executed only if the condition evaluates to a
|
||||
non-null integer. The @code{@@#else} branch is optional and, if
|
||||
|
|
@ -5496,10 +5496,10 @@ and to abort. The argument must evaluate to a string.
|
|||
@subsection Typical usages
|
||||
|
||||
@menu
|
||||
* Modularization::
|
||||
* Indexed sums or products::
|
||||
* Multi-country models::
|
||||
* Endogeneizing parameters::
|
||||
* Modularization::
|
||||
* Indexed sums or products::
|
||||
* Multi-country models::
|
||||
* Endogeneizing parameters::
|
||||
@end menu
|
||||
|
||||
@node Modularization
|
||||
|
|
@ -5613,7 +5613,7 @@ In the model, @math{\alpha} is a (share) parameter, and
|
|||
@code{lab_rat} is an endogenous variable.
|
||||
|
||||
It is clear that calibrating @math{\alpha} is not straigthforward; but
|
||||
on the contrary, we have real world data for @code{lab_rat}, and
|
||||
on the contrary, we have real world data for @code{lab_rat}, and
|
||||
it is clear that these two variables are economically linked.
|
||||
|
||||
The solution is to use a method called @emph{variable flipping}, which
|
||||
|
|
@ -5727,7 +5727,7 @@ Sets the seed used for random number generation.
|
|||
For all parameters, endogenous and exogenous variables, stores
|
||||
their value in a text file, using a simple name/value associative table.
|
||||
|
||||
@itemize
|
||||
@itemize
|
||||
|
||||
@item
|
||||
for parameters, the value is taken from the last parameter
|
||||
|
|
@ -5778,7 +5778,7 @@ directive to share the model equations between the two files
|
|||
For all parameters, endogenous and exogenous variables, loads
|
||||
their value from a file created with @code{save_params_and_steady_state}.
|
||||
|
||||
@itemize
|
||||
@itemize
|
||||
|
||||
@item
|
||||
for parameters, their value will be initialized as if they
|
||||
|
|
@ -5823,7 +5823,7 @@ option1 = choice1
|
|||
|
||||
[command1]
|
||||
option0 = choice0
|
||||
option1 = choice1
|
||||
option1 = choice1
|
||||
@end example
|
||||
|
||||
The configuration file follows a few conventions (self-explanatory
|
||||
|
|
@ -5851,7 +5851,7 @@ Is @code{true} or @code{false}.
|
|||
@end table
|
||||
|
||||
@menu
|
||||
* Parallel Configuration::
|
||||
* Parallel Configuration::
|
||||
@end menu
|
||||
|
||||
@node Parallel Configuration
|
||||
|
|
@ -6063,7 +6063,7 @@ CPUnbr = [2:4]
|
|||
UserName = usern
|
||||
RemoteDirectory = /home/usern/Remote
|
||||
DynarePath = /home/usern/dynare/matlab
|
||||
MatlabOctavePath = matlab
|
||||
MatlabOctavePath = matlab
|
||||
@end example
|
||||
|
||||
@end deffn
|
||||
|
|
@ -6169,7 +6169,7 @@ a relaxation algorithm,'' CEPREMAP, @i{Couverture Orange}, 9602.
|
|||
Kim, Jinill, Sunghyun Kim, Ernst Schaumburg, and Christopher A. Sims
|
||||
(2008): ``Calculating and using second-order accurate solutions of
|
||||
discrete time dynamic equilibrium models,'' @i{Journal of Economic
|
||||
Dynamics and Control}, 32(11), 3397--3414.
|
||||
Dynamics and Control}, 32(11), 3397--3414.
|
||||
|
||||
@item
|
||||
Koopman, S. J. and J. Durbin (2003): ``Filtering and Smoothing of
|
||||
|
|
|
|||
Loading…
Reference in New Issue