A code library for solving and simulating consumption-saving models in Python using Numba JIT compiled functions. The consav package provides:
- A ConsumptionSavingModel class with predefined methods for e.g. saving and loading
- A multi-linear interpolation module
- Optimizers such as golden section search and newton-raphson
- An upper envelope function for using the endogenous grid point method in non-convex models
- Functions for interfacing easily with c++
All of the above is written to be Numba compatible.
The repository ConsumptionSavingNotebooks contains a number of examples on using the various tools and two models:
- The canonical buffer-stock consumption model
- A durable consumption models with non-convex adjustment costs
The library is still early in its development, contributions are very welcome!
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Interested in other numerical tools for economists in Python? Try out QuantEcon.
The package can be installed with
pip install git+https://github.com/NumEconCopenhagen/ConsumptionSaving
To develop the package follow these steps:
- Install watchdog,
pip install watchdog - Clone this repository
- Locate the cloned repostiory in a terminal
- Run
python setyp.py watch
This re-installs the package whenever you make any changes.