Econometrics for Weather and Climate Applications & Education
Project description
Eco4Weather : Econometrics for Weather and Climate Applications & Education
This repository provides tools for exploration of economical application as social planner applied in mitigation to facilitate the academic use and the dissemination. The models are in Python and illustrated in Jupyter notebooks.
Codes are available under CeCILL-B
Examples
The package can be used to illustrate numerical solution of social planner problem. For instance:
Ramsey model
see Exploration of the Ramsey model
Hoel-Kverndokk simplified model for tax setting
see Exploration of a simplified version of Hoel & Kverndokk model
Installation
pip install eco4weather
or from github
git clone https://github.com/opannekoucke/eco4weather.git
How to cite
O. Pannekoucke, "Eco4Weather : Econometrics for Weather and Climate Applications & Education", https://github.com/opannekoucke/eco4weather
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file eco4weather-1.0.1.tar.gz.
File metadata
- Download URL: eco4weather-1.0.1.tar.gz
- Upload date:
- Size: 14.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.9.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c26040b0adfb5df6a7063dac5a1da6d2525632c64b406fdafd2d395789754cbb
|
|
| MD5 |
914288095d91e19f9e11c08c98b135f4
|
|
| BLAKE2b-256 |
d95249aa58a52032b7cb0190b29453fe82cdcb466c2f2284ae5ab743fdf8cecb
|
File details
Details for the file eco4weather-1.0.1-py3-none-any.whl.
File metadata
- Download URL: eco4weather-1.0.1-py3-none-any.whl
- Upload date:
- Size: 15.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.9.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2665ba426738e100dbb86df39e9d515bd528387605ef69eb7e3767073b3dea09
|
|
| MD5 |
288e60ab1c56936714cbfc4903f02734
|
|
| BLAKE2b-256 |
8e43ad64d2478a76e151beae172c64fdadafcc089eb02252f3c68aebd485bec5
|