From 996dcd70fb07d9b53b930b1f5d7a07777aea8e8a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?St=C3=A9phane=20Adjemia=20=28Scylla=29?= Date: Sun, 17 Feb 2019 00:23:02 +0100 Subject: [PATCH] Document variance decomposition with measurement error. Manually cherry-picked from a1222a1d1bb827db4a8c631e7c5ed67f66d4dcc1. --- src/source/the-model-file.rst | 114 +++++++++++++++++++++++++++------- 1 file changed, 90 insertions(+), 24 deletions(-) diff --git a/src/source/the-model-file.rst b/src/source/the-model-file.rst index 7be90e0c7..600363849 100644 --- a/src/source/the-model-file.rst +++ b/src/source/the-model-file.rst @@ -3151,17 +3151,25 @@ Computing the stochastic solution The results are stored in ``oo_.conditional_variance_decomposition`` (see - :mvar:`oo_.conditional_variance_decomposition`). The variance - decomposition is only conducted, if theoretical moments are - requested, i.e. using the ``periods=0`` option. In case of - ``order=2``, Dynare provides a second-order accurate + :mvar:`oo_.conditional_variance_decomposition`). In the + presence of measurement error, the + ``oo_.conditional_variance_decomposition`` field will contain + the variance contribution after measurement error has been + taken out, i.e. the decomposition will be conducted of the + actual as opposed to the measured variables. The variance + decomposition of the measured variables will be stored in + ``oo_.conditional_variance_decomposition_ME`` (see + :mvar:`oo_.conditional_variance_decomposition_ME`). The + variance decomposition is only conducted, if theoretical + moments are requested, *i.e.* using the ``periods=0``-option. + In case of ``order=2``, Dynare provides a second-order accurate approximation to the true second moments based on the linear - terms of the second-order solution (see *Kim, Kim, Schaumburg - and Sims (2008)*). Note that the unconditional variance - decomposition (i.e. at horizon infinity) is automatically - conducted if theoretical moments are requested and if - ``nodecomposition`` is not set (see - :mvar:`oo_.variance_decomposition`) + terms of the second-order solution (see *Kim, Kim, + Schaumburg and Sims (2008)*). Note that the unconditional + variance decomposition *i.e.* at horizon infinity) is + automatically conducted if theoretical moments are requested + and if ``nodecomposition`` is not set (see + :mvar:`oo_.variance_decomposition`). .. option:: pruning @@ -3402,7 +3410,7 @@ Computing the stochastic solution ``oo_.gamma{nar+2}`` Unconditional variance decomposition, see - mvar:`oo_.variance_decomposition`. + :mvar:`oo_.variance_decomposition`. ``oo_.gamma{nar+3}`` @@ -3415,14 +3423,33 @@ Computing the stochastic solution .. matvar:: oo_.variance_decomposition - |br| After a run of ``stoch_simul`` when requesting theoretical moments - (``periods=0``), contains a matrix with the result of the + |br| After a run of ``stoch_simul`` when requesting theoretical + moments (``periods=0``), contains a matrix with the result of the unconditional variance decomposition (i.e. at horizon infinity). The first dimension corresponds to the endogenous - variables (in the order of declaration) and the second dimension - corresponds to exogenous variables (in the order of - declaration). Numbers are in percent and sum up to 100 across - columns. + variables (in the order of declaration after the command or in + ``M_.endo_names``) and the second dimension corresponds to + exogenous variables (in the order of declaration). Numbers are in + percent and sum up to 100 across columns. In the presence of + measurement error, the field will contain the variance + contribution after measurement error has been taken out, *i.e.* + the decomposition will be conducted of the actual as opposed to + the measured variables. + +.. matvar:: oo_.variance_decomposition_ME + + |br| Field set after a run of ``stoch_simul`` when requesting + theoretical moments (``periods=0``) if measurement error is + present. It is similar to :mvar:`oo_.variance_decomposition`, but + the decomposition will be conducted of the measured variables. The + field contains a matrix with the result of the unconditional + variance decomposition (*i.e.* at horizon infinity). The first + dimension corresponds to the observed endoogenous variables (in + the order of declaration after the command) and the second + dimension corresponds to exogenous variables (in the order of + declaration), with the last column corresponding to the + contribution of measurement error. Numbers are in percent and sum + up to 100 across columns. .. matvar:: oo_.conditional_variance_decomposition @@ -3431,8 +3458,28 @@ Computing the stochastic solution three-dimensional array with the result of the decomposition. The first dimension corresponds to forecast horizons (as declared with the option), the second dimension corresponds to endogenous - variables (in the order of declaration), the third dimension - corresponds to exogenous variables (in the order of declaration). + variables (in the order of declaration after the command or in + ``M_.endo_names`` if not specified), the third dimension + corresponds to exogenous variables (in the order of + declaration). In the presence of measurement error, the field will + contain the variance contribution after measurement error has been + taken out, *i.e.* the decomposition will be conductedof the actual + as opposed to the measured variables. + +.. matvar:: oo_.conditional_variance_decomposition_ME + + |br| Field set after a run of ``stoch_simul`` with the + ``conditional_variance_decomposition`` option if measurement error + is present. It is similar to + :mvar:`oo_.conditional_variance_decomposition`, but the + decomposition will be conducted of the measured variables. It + contains a three-dimensional array with the result of the + decomposition. The first dimension corresponds to forecast + horizons (as declared with the option), the second dimension + corresponds to observed endogenous variables (in the order of + declaration), the third dimension corresponds to exogenous + variables (in the order of declaration), with the last column + corresponding to the contribution of the measurement error. .. matvar:: oo_.contemporaneous_correlation @@ -5309,9 +5356,15 @@ block decomposition of the model (see :opt:`block`). :math:`var(y_{t+k}\vert t)`. For period 1, the conditional variance decomposition provides the decomposition of the effects of shocks upon impact. The results are stored in - ``oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition``, - but currently there is no displayed output. Note that this - option requires the ``moments_varendo`` to be specified. + ``oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition``.. Note + that this option requires the option ``moments_varendo`` to be + specified. In the presence of measurement error, the field will + contain the variance contribution after measurement error has + been taken out, *i.e.* the decomposition will be conducted of the + actual as opposed to the measured variables. The variance + decomposition of the measured variables will be stored in + ``oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecompositionME``. + .. option:: filtered_vars @@ -6291,8 +6344,21 @@ block decomposition of the model (see :opt:`block`). ``ConditionalVarianceDecomposition`` - Only if the ``conditional_variance_decomposition`` option has - been specified. + Only if the ``conditional_variance_decomposition`` + option has been specified. In the presence of + measurement error, the field will contain the variance + contribution after measurement error has been taken + out, i.e. the decomposition will be conducted of the + actual as opposed to the measured variables. + + ``ConditionalVarianceDecompositionME`` + + Only if the ``conditional_variance_decomposition`` + option has been specified. Same as + ``ConditionalVarianceDecomposition``, but contains the + decomposition of the measured as opposed to the actual + variable. The joint contribution of the measurement + error will be saved in a field names ``ME``. .. matvar:: oo_.posterior_density