pydsge 0.2.6
Solve, filter and estimate DSGE models with occasionaly binding constraints
License: MIT


pydsge
======

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    :target: https://badge.fury.io/py/pydsge

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    :target: https://github.com/gboehl/pydsge/actions/workflows/continuous-integration.yml


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----

A package for solving, filtering and estimating **linear** DSGE models with the ZLB (or other occasionally binding constraints).

The set of methods is introduced in the paper `Estimation of DSGE Models with the Effective Lower Bound <https://gregorboehl.com/live/bczlb_BS.pdf>`_ *(Gregor Boehl & Felix Strobel, 2023, JEDC)*, where we also estimate the medium-scale New Keynesian model to post-2008 US data.

Check out my `Econpizza <https://github.com/gboehl/econpizza>`_ package if you are interested in simulating **nonlinear** DSGE models with (or without) **heterogeneous agents**.

A collection of models that can be (and were) used with this package can be found in `another repo <https://github.com/gboehl/projectlib/tree/master/yamls>`_.

Installation
-------------

Installing the stable version is as simple as typing

.. code-block:: bash

   pip install pydsge

in your terminal (Linux/MacOS) or Anaconda Prompt (Win). 

Documentation
-------------

Documentation can be found on `ReadTheDocs <https://pydsge.readthedocs.io/en/latest/index.html>`_:

- `Installation Guide <https://pydsge.readthedocs.io/en/latest/installation_guide.html>`_
- `Getting Started <https://pydsge.readthedocs.io/en/latest/getting_started.html>`_
- `Module Documentation <https://pydsge.readthedocs.io/en/latest/modules.html>`_

Citation
--------

**pydsge** is developed by Gregor Boehl to simulate, filter, and estimate DSGE models with the zero lower bound on nominal interest rates in various applications (see `my website <https://gregorboehl.com>`_ for research papers using the package). Please cite it with

.. code-block:: latex

    @TechReport{boehl2022meth,
      title = {{Estimation of DSGE Models with the Effective Lower Bound}},
      author = {Boehl, Gregor and Strobel, Felix},
      journal = {Journal of Economic Dynamics and Control},
      volume = {158},
      year = {2022},
      publisher = {Elsevier}
    }

.. code-block:: latex

    @techreport{boehl2022obc,
      title = Efficient solution and computation of models with occasionally binding constraints},
      author = {Boehl, Gregor},
      journal = {Journal of Economic Dynamics and Control},
      volume = {143},
      year = {2022},
      publisher = {Elsevier}
    }


We appreciate citations for **pydsge** because it helps us to find out how people have
been using the package and it motivates further work.


Parser
------

The parser originally was a fork of Ed Herbst's fork from Pablo Winant's (excellent) package **dolo**. 

See https://github.com/EconForge/dolo and https://github.com/eph.


References
----------

Boehl, Gregor (2022). `Efficient Solution and Computation of Models with Occasionally Binding Constraints <http://gregorboehl.com/live/obc_boehl.pdf>`_. *Journal of Economic Dynamics and Control*