EZ-Climate model
Project description
# EZ-Climate
EZ-Climate is a model for pricing carbon dioxide emission. It explores the implications of these richer preference specifications for the optimal ![equation](http://latex.codecogs.com/gif.latex?CO_2) price. We develop the EZ-Climate model, a simple discrete-time model in which the representative agent has an Epstein-Zin preference specification, and in which uncertainty about the effect of ![equation](http://latex.codecogs.com/gif.latex?CO_2) emissions on global temperature and on eventual damages is gradually resolved over time. In the EZ-Climate model the optimal price is equal to the price of one ton of ![equation](http://latex.codecogs.com/gif.latex?CO_2) emitted at any given point in time that maximizes the utility of the representative agent at that time. We embed a number of features including tail risk, the potential for technological change, and backstop technologies. In contrast to most modeled carbon price paths, the EZ-Climate model suggests a high optimal carbon price today that is expected to decline over time. It also points to the importance of backstop technologies and to potentially very large.
## Downloads
You can find the most recent releases at: https://pypi.python.org/pypi/ezclimate/.
## Documentation See http://ezclimate.science for EZ-Climate documentation.
In order to get the tip documentation, change directory to the docs subfolder and type in make html, the documentation will be under ../../ez_climate_docs/html. You will need [Sphinx](http://sphinx.pocoo.org) to build the documentation.
See http://gwagner.com/ezclimate for the latest working paper employing this code.
## Installation
We encourage you to use pip to install ezclimate on your system.
`bash pip install ezclimate `
If you wish to build from sources, download or clone the repository.
`bash python setup.py install `
## Requirements
EZ-Climate is compatible with Python 2 and 3. [Numpy](http://www.numpy.org/) is required, and we recommend [matplotlib](http://www.matplotlib.org/) for visualization of results.
## Authors
Kent Daniel
Robert Litterman
Gernot Wagner
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