@@ -5,6 +5,8 @@ the [DynareWiki](http://www.dynare.org/DynareWiki/NewFeatures).
...
@@ -5,6 +5,8 @@ the [DynareWiki](http://www.dynare.org/DynareWiki/NewFeatures).
Dynare 6 (unstable)
Dynare 6 (unstable)
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- New perfect foresight simulation with expectation errors. In such a scenario, agents make expectation errors, in the sense that the path they had anticipated in period 1 does not realize exactly. More precisely, in some simulation periods, they may receive new information that makes them revise their anticipation for the path of future shocks. Also, under this scenario, it is assumed that agents behave as under perfect foresight, *i.e.* they take their decisions as if there was no uncertainty and they knew exactly the path of future shocks; the new information that they may receive comes as a total surprise to them. Implemented by new `perfect_foresight_with_expectation_errors_setup` and `perfect_foresight_with_expectation_errors_solver` commands, and `shocks(learnt_in=…)` and `endval(learnt_in=…)` blocks.
- New `log` option to the `var` statement. In addition to the endogenous variable(s) thus declared, this option also triggers the creation of auxiliary variable(s) equal to the log of the corresponding endogenous variable(s). For example, given a ``var(log) y`` statement, two endogenous will be created (``y`` and ``LOG_y``), and an auxiliary equation linking the two will also be added (equal to ``LOG_y = log(y)``). Moreover, every occurence of ``y`` in the model will be replaced by ``exp(LOG_y)``. This option is for example useful when one wants to perform a loglinear approximation of some variable(s) in the context of a first-order stochastic approximation; or when one wants to ensure the variable(s) stay(s) in the definition domain of the function defining the steady state or the dynamic residuals when the nonlinear solver is used. (#349)
- New `log` option to the `var` statement. In addition to the endogenous variable(s) thus declared, this option also triggers the creation of auxiliary variable(s) equal to the log of the corresponding endogenous variable(s). For example, given a ``var(log) y`` statement, two endogenous will be created (``y`` and ``LOG_y``), and an auxiliary equation linking the two will also be added (equal to ``LOG_y = log(y)``). Moreover, every occurence of ``y`` in the model will be replaced by ``exp(LOG_y)``. This option is for example useful when one wants to perform a loglinear approximation of some variable(s) in the context of a first-order stochastic approximation; or when one wants to ensure the variable(s) stay(s) in the definition domain of the function defining the steady state or the dynamic residuals when the nonlinear solver is used. (#349)
- Allows decomposition of the PAC target into an arbitrary number of components. (b297353b06c9c35223500439c0bc63321675768b)
- Allows decomposition of the PAC target into an arbitrary number of components. (b297353b06c9c35223500439c0bc63321675768b)
