Document variance decomposition with measurement error.

Manually cherry-picked from a1222a1d1b.
time-shift
Stéphane Adjemia (Scylla) 2019-02-17 00:23:02 +01:00
parent 8383a9cbd2
commit 996dcd70fb
Signed by untrusted user who does not match committer: stepan
GPG Key ID: A6D44CB9C64CE77B
1 changed files with 90 additions and 24 deletions

View File

@ -3151,17 +3151,25 @@ Computing the stochastic solution
The results are stored in The results are stored in
``oo_.conditional_variance_decomposition`` (see ``oo_.conditional_variance_decomposition`` (see
:mvar:`oo_.conditional_variance_decomposition`). The variance :mvar:`oo_.conditional_variance_decomposition`). In the
decomposition is only conducted, if theoretical moments are presence of measurement error, the
requested, i.e. using the ``periods=0`` option. In case of ``oo_.conditional_variance_decomposition`` field will contain
``order=2``, Dynare provides a second-order accurate 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 approximation to the true second moments based on the linear
terms of the second-order solution (see *Kim, Kim, Schaumburg terms of the second-order solution (see *Kim, Kim,
and Sims (2008)*). Note that the unconditional variance Schaumburg and Sims (2008)*). Note that the unconditional
decomposition (i.e. at horizon infinity) is automatically variance decomposition *i.e.* at horizon infinity) is
conducted if theoretical moments are requested and if automatically conducted if theoretical moments are requested
``nodecomposition`` is not set (see and if ``nodecomposition`` is not set (see
:mvar:`oo_.variance_decomposition`) :mvar:`oo_.variance_decomposition`).
.. option:: pruning .. option:: pruning
@ -3402,7 +3410,7 @@ Computing the stochastic solution
``oo_.gamma{nar+2}`` ``oo_.gamma{nar+2}``
Unconditional variance decomposition, see Unconditional variance decomposition, see
mvar:`oo_.variance_decomposition`. :mvar:`oo_.variance_decomposition`.
``oo_.gamma{nar+3}`` ``oo_.gamma{nar+3}``
@ -3415,14 +3423,33 @@ Computing the stochastic solution
.. matvar:: oo_.variance_decomposition .. matvar:: oo_.variance_decomposition
|br| After a run of ``stoch_simul`` when requesting theoretical moments |br| After a run of ``stoch_simul`` when requesting theoretical
(``periods=0``), contains a matrix with the result of the moments (``periods=0``), contains a matrix with the result of the
unconditional variance decomposition (i.e. at horizon unconditional variance decomposition (i.e. at horizon
infinity). The first dimension corresponds to the endogenous infinity). The first dimension corresponds to the endogenous
variables (in the order of declaration) and the second dimension variables (in the order of declaration after the command or in
corresponds to exogenous variables (in the order of ``M_.endo_names``) and the second dimension corresponds to
declaration). Numbers are in percent and sum up to 100 across exogenous variables (in the order of declaration). Numbers are in
columns. 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 .. matvar:: oo_.conditional_variance_decomposition
@ -3431,8 +3458,28 @@ Computing the stochastic solution
three-dimensional array with the result of the decomposition. The three-dimensional array with the result of the decomposition. The
first dimension corresponds to forecast horizons (as declared with first dimension corresponds to forecast horizons (as declared with
the option), the second dimension corresponds to endogenous the option), the second dimension corresponds to endogenous
variables (in the order of declaration), the third dimension variables (in the order of declaration after the command or in
corresponds to exogenous variables (in the order of declaration). ``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 .. 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 :math:`var(y_{t+k}\vert t)`. For period 1, the conditional
variance decomposition provides the decomposition of the variance decomposition provides the decomposition of the
effects of shocks upon impact. The results are stored in effects of shocks upon impact. The results are stored in
``oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition``, ``oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition``.. Note
but currently there is no displayed output. Note that this that this option requires the option ``moments_varendo`` to be
option requires the ``moments_varendo`` to be specified. 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 .. option:: filtered_vars
@ -6291,8 +6344,21 @@ block decomposition of the model (see :opt:`block`).
``ConditionalVarianceDecomposition`` ``ConditionalVarianceDecomposition``
Only if the ``conditional_variance_decomposition`` option has Only if the ``conditional_variance_decomposition``
been specified. 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 .. matvar:: oo_.posterior_density