Solve, filter and estimate DSGE models with occasionaly binding constraints
Project description
A package for solving, filtering and estimating linear DSGE models with the ZLB (or other occasionally binding constraints).
Check out my 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.
Installation
Installing the stable version is as simple as typing
pip install pydsge
in your terminal (Linux/MacOS) or Anaconda Prompt (Win).
Documentation
Documentation can be found on ReadTheDocs:
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 for research papers using the package). Please cite it with
@TechReport{boehl2022meth,
title = {{Estimation of DSGE Models with the Effective Lower Bound}},
author = {Boehl, Gregor and Strobel, Felix},
year = 2022,
type = {CRC 224 Discussion Papers},
institution = {University of Bonn and University of Mannheim, Germany}
}
@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},
pages = 104523},
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. Journal of Economic Dynamics and Control
Project details
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