pycge: a Python package for CGE modeling

This package provides an interface for solving a Computable General Equilibrium (CGE) model in Python, using the package pyomo as the back end.

The aim of this package is to separate model analysis from model definition. For a given a model definition, pycge provides a common interface for analysis, including: generating model instances with different data sets; modifying model instances to simulate "shocks"; solving model instances; and post-processing solutions (e.g., conducting comparative statics).

Requirements

python-3.x and pyomo 5.2

Setup and installation

See ./docs/index.rst

Quick Start

A quick summary of a standard workflow::

 # create model definition object
 testdef = ModelDef()

 # create pycge object
 testcge = PyCGE(testdef)
 
 # add data
 testcge.load_data(path/to/data)

 # create base instance
 testcge.model_instance()

 # calibrate base instance
 testcge.model_calibrate(solver, mgr='') 

 # create sim instance to modify
 testcge.model_sim() 

 # modify sim instance
 testcge.model_modify_instance(...) # modify some value
 testcge.model_modify_instnace(...) # modify another value
 
 # solve sim instance
 testcge.model_solve(solver, mgr='') 

 # compare base and sim equilibria
 testcge.model_compare()

Credits

The package is maintained by Juan Fung <juan.fung@nist.gov>

Developers

• Charles Burtwistle