Contains the functions and classes for solving, filtering and estimating DSGE models at the ZLB (or with other occasionally binding constraints).
A collection of models that can (and were) used with this package can be found in another repo.
The code is in alpha state and provided for reasons of collaboration, replicability and code sharing in the spirit of open science. It does not (and for now, can not) have a toolbox character. The code is operational, but (yet) not ready for public use and I can not provide any support. You are however very welcome to get in touch if you are interested working with the package.
Installing the repo version is as simple as
pip install pydsgeThere is some preliminary documentation out there.
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 for research papers using the package). Please cite it with
@techreport{boehl2021method,
Title = {Efficient Solution and Computation of Models with Occasionally Binding Constraints},
Author = {Gregor Boehl},
Year = {2021},
institution = {Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS)},
type = {IMFS Working Paper Series},
number = {148},
url = {https://gregorboehl.com/live/obc_boehl.pdf},
}
We appreciate citations for pydsge because it helps us to find out how people have been using the package and it motivates further work.
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.
Boehl, Gregor (2021). Efficient Solution and Computation of Models with Occasionally Binding Constraints. IMFS Working Paper