dynare issueshttps://git.dynare.org/Dynare/dynare/issues2019-08-14T12:15:53Zhttps://git.dynare.org/Dynare/dynare/issues/827Feature request: Implement the algorithm of Ajevskis (2014) for perturbation ...2019-08-14T12:15:53ZTom HoldenFeature request: Implement the algorithm of Ajevskis (2014) for perturbation around a deterministic pathViktors Ajevskis has a [great new paper](https://ideas.repec.org/p/ltv/wpaper/201401.html) showing how the Lombardo pruning method may be extended to support perturbation around a deterministic path. This seems like a feature that would be a huge benefit to virtually all Dynare users, since it makes it possible to e.g.:
- Solve non-stationary DSGE models, such as those featuring structural change.
- Evaluate the welfare consequences of a permanent change in policy, without sacrificing accuracy along the transition path.
- Obtain increased accuracy for large impulse response exercises.
- Unify the stochastic and non-stochastic simulation engines in Dynare.
It would be great if this could be added to the bottom of your very long to do list!
https://ideas.repec.org/p/ltv/wpaper/201401.html
Viktors Ajevskis has a [great new paper](https://ideas.repec.org/p/ltv/wpaper/201401.html) showing how the Lombardo pruning method may be extended to support perturbation around a deterministic path. This seems like a feature that would be a huge benefit to virtually all Dynare users, since it makes it possible to e.g.:
- Solve non-stationary DSGE models, such as those featuring structural change.
- Evaluate the welfare consequences of a permanent change in policy, without sacrificing accuracy along the transition path.
- Obtain increased accuracy for large impulse response exercises.
- Unify the stochastic and non-stochastic simulation engines in Dynare.
It would be great if this could be added to the bottom of your very long to do list!
https://ideas.repec.org/p/ltv/wpaper/201401.html
5.0https://git.dynare.org/Dynare/dynare/issues/564ramsey policy at order 22019-08-14T12:17:39ZMichelJuillardramsey policy at order 2The code for computing a 2nd order approximation of Ramsey policy is already in place. I just need to complete the evaluation of objective function (at 3rd order).
The code for computing a 2nd order approximation of Ramsey policy is already in place. I just need to complete the evaluation of objective function (at 3rd order).
5.0MichelJuillardMichelJuillardhttps://git.dynare.org/Dynare/dynare/issues/1173Support estimation under optimal policy2019-09-20T06:36:13ZJohannes Pfeifer Support estimation under optimal policySee http://www.dynare.org/phpBB3/viewtopic.php?f=1&t=8071
See http://www.dynare.org/phpBB3/viewtopic.php?f=1&t=8071
5.0https://git.dynare.org/Dynare/dynare/issues/4Integrate algorithm for TBC by Holden and Paetz (2012)2019-06-19T15:37:43ZSébastien VillemotIntegrate algorithm for TBC by Holden and Paetz (2012)Request by Stéphane Moyen.
Paper at http://www.tholden.org/files/zlb.pdf?attredirects=0
Apparently the code has been posted on the Dynare forums. It's therefore a matter of dealing with copyright/license issues and integrating it.
Request by Stéphane Moyen.
Paper at http://www.tholden.org/files/zlb.pdf?attredirects=0
Apparently the code has been posted on the Dynare forums. It's therefore a matter of dealing with copyright/license issues and integrating it.
https://git.dynare.org/Dynare/dynare/issues/349Use preprocessor for loglinearization2019-06-19T15:37:41ZJohannes Pfeifer Use preprocessor for loglinearizationAn often heard request is a way to loglinearize a model instead of a linearization. Currently, the way to go is to put all variables in exp(). This is mechanic and error-prone work.
If it is easily doable, I would like to propose to use the preprocessor to make this substitution, similar to the predetermined_variables-command substituting the lag of the current period.
We could then add a command like
`model(loglinearize)`
to tell the preprocessor to loglinearize.
At the same time, we need a command like `non_logarithmic_variables` similar to the `predetermined_variables` command to exclude already logarithmic variables (like e.g. technology) or variables with a negative steady state. I think this is a better option than specifying explicitly which variables to substitute.
If possible, a design issue we would need to discuss is the behavior in steady state computation. I would suggest that the `model(loglinearize)` automatically triggers taking the log of the corresponding initvals so that users can enter the model in nonlinear standard form and Dynare takes care of the rest.
An often heard request is a way to loglinearize a model instead of a linearization. Currently, the way to go is to put all variables in exp(). This is mechanic and error-prone work.
If it is easily doable, I would like to propose to use the preprocessor to make this substitution, similar to the predetermined_variables-command substituting the lag of the current period.
We could then add a command like
`model(loglinearize)`
to tell the preprocessor to loglinearize.
At the same time, we need a command like `non_logarithmic_variables` similar to the `predetermined_variables` command to exclude already logarithmic variables (like e.g. technology) or variables with a negative steady state. I think this is a better option than specifying explicitly which variables to substitute.
If possible, a design issue we would need to discuss is the behavior in steady state computation. I would suggest that the `model(loglinearize)` automatically triggers taking the log of the corresponding initvals so that users can enter the model in nonlinear standard form and Dynare takes care of the rest.
5.0https://git.dynare.org/Dynare/dynare/issues/147Accuracy checks2019-06-19T15:37:43ZSébastien VillemotAccuracy checks5.0https://git.dynare.org/Dynare/dynare/issues/251SMM: create preprocessor interface, make it compatible with Octave2019-06-19T15:37:42ZSébastien VillemotSMM: create preprocessor interface, make it compatible with OctaveIn particular, the current code is not compatible with Octave since it uses RandStream at several places.
In particular, the current code is not compatible with Octave since it uses RandStream at several places.
https://git.dynare.org/Dynare/dynare/issues/568Integrate DMM2018-11-08T11:49:07ZHoutan BastaniIntegrate DMMhttp://ipsc.jrc.ec.europa.eu/?id=790
http://ipsc.jrc.ec.europa.eu/fileadmin/repository/sfa/finepro/software/DMMmanual.pdf
http://ipsc.jrc.ec.europa.eu/?id=790
http://ipsc.jrc.ec.europa.eu/fileadmin/repository/sfa/finepro/software/DMMmanual.pdf
5.0MichelJuillardMichelJuillardhttps://git.dynare.org/Dynare/dynare/issues/162Global method: stochastic simulation approach2019-06-19T15:37:43ZSébastien VillemotGlobal method: stochastic simulation approachAs advocated by Judd, Maliar & Maliar in recent NBER WP.
For the IMF.
As advocated by Judd, Maliar & Maliar in recent NBER WP.
For the IMF.
https://git.dynare.org/Dynare/dynare/issues/569Integrate OccBin2019-09-12T14:48:25ZHoutan BastaniIntegrate OccBinhttps://github.com/lucashare/occbin
https://www2.bc.edu/matteo-iacoviello/research_files/TOOLKIT_PAPER.pdf
https://github.com/lucashare/occbin
https://www2.bc.edu/matteo-iacoviello/research_files/TOOLKIT_PAPER.pdf
5.0MichelJuillardMichelJuillardhttps://git.dynare.org/Dynare/dynare/issues/824Add an interface for joint priors.2018-11-08T10:32:51ZStéphane Adjemianstepan@dynare.orgAdd an interface for joint priors.Only available for the new estimation syntax. Something like:
``` example
[alpha, beta].prior(shape=gaussian, mean=Vector, variance=Matrix, ...)
```
This interface is needed for Dirichlet priors over probabilities.
Only available for the new estimation syntax. Something like:
``` example
[alpha, beta].prior(shape=gaussian, mean=Vector, variance=Matrix, ...)
```
This interface is needed for Dirichlet priors over probabilities.
5.0Houtan BastaniHoutan Bastani