This release is a pre-release and may not be stable for production use.
dsgekit
A Python toolkit for Dynamic Stochastic General Equilibrium (DSGE) modeling.
Status
- Version:
0.1.0rc1(release candidate pre-release) - API stability: evolving
- Minimum Python version:
3.13(frompyproject.toml)
What Is Included
- Model loading from
.mod, YAML, and Python dict/API sources - Linear workflow: linearization, QZ/BK solving, IRFs, simulation, moments, FEVD
- State-space pipeline: Kalman filter, RTS smoother, forecasting, historical decomposition
- Estimation: MLE, MAP, MCMC (with diagnostics), marginal data density
- Nonlinear solvers: first-, second-, and third-order perturbation (with pruning)
- Deterministic workflows: perfect foresight and one-constraint
occbin-lite - Policy and welfare tooling: OSR sweeps, Ramsey/discretionary LQ, welfare comparisons
- Baseline regression harness and CI workflow for compatibility checks
Installation
From source (recommended at this stage)
git clone https://github.com/gustavovargas/dsgekit.git
cd dsgekit
python3.13 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
Optional extras
pip install -e ".[plot]" # plotting
pip install -e ".[sym]" # symbolic derivatives
pip install -e ".[speed]" # numba acceleration
pip install -e ".[all]" # all optional extras
Quick Start
from dsgekit import load_model
from dsgekit.simulate import irf
from dsgekit.solvers import solve_linear
from dsgekit.transforms import linearize
model, cal, ss = load_model("tests/fixtures/models/ar1.yaml")
solution = solve_linear(linearize(model, ss, cal))
responses = irf(solution, "e", periods=20)
print(responses.data.head())
CLI Overview
dsgekit info model.mod
dsgekit solve model.mod
dsgekit irf model.mod -s e -p 20
dsgekit simulate model.mod -n 200 --seed 42
dsgekit estimation model.mod --method mle --params rho
dsgekit forecast model.mod -p 12
dsgekit decompose model.mod
dsgekit osr model.mod --grid phi_pi=1.0:3.0:9 --loss pi=1.0 --loss y=0.5
dsgekit baseline_regression --baselines tests/fixtures/baselines
Documentation Map
docs/quickstart.mddocs/formats.mddocs/first_order_perturbation.mddocs/second_order_perturbation.mddocs/third_order_perturbation.mddocs/perfect_foresight.mddocs/occbin_lite.mddocs/forecast_decomposition.mddocs/osr.mddocs/ramsey_lq.mddocs/discretion_lq.mddocs/welfare.mddocs/performance.mddocs/mod_workflow_migration.md
Full index: docs/index.md
Examples
python examples/ar1_pipeline.py
python examples/nk_forward_looking.py
python examples/nonlinear_girf.py
python examples/occbin_zlb_toy.py
python examples/reference_model_zoo.py
Contributing and Security
- Contribution guide:
CONTRIBUTING.md - Code of conduct:
CODE_OF_CONDUCT.md - Security policy:
SECURITY.md
Legal
dsgekitis an independent project and is not affiliated with third-party tool maintainers.- Implementation provenance and attribution policy:
docs/legal_and_attribution.md. - Naming policy for third-party references:
docs/brand_naming_policy.md. - Dependency notices:
THIRD_PARTY_NOTICES.md.
License
Apache-2.0
Metadata
Release files for dsgekit 0.1.0rc1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| dsgekit-0.1.0rc1.tar.gz | 177.6 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dsgekit-0.1.0rc1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 332.7 kB
Release files / dsgekit-0.1.0rc1.tar.gz
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