econci 0.1.2

Calculates Economic Complexity Indexes

econci

Calculates Economic Complexity Indexes

• Free software: MIT license

This package implements the indexes found in the Atlas of Economic Complexity [HaRH2014]. It also creates the Product Space.

Installation

pip install econci

Usage

import econci

comp = econci.Complexity(df, c='country', p='product', values='export')
comp.calculate_indexes()
eci = comp.eci
pci = comp.pci

# creating the product space
comp.create_product_space()

# the graphs are networkx.Graph objects
complete_graph = comp.complete_graph  # complete product space
max_spanning_tree = comp.maxst  # maximum spanning tree
prod_space = comp.product_space  # product space

# edges_nodes_to_csv saves one csv file with edges and weights
# and another file with nodes information
econci.edges_nodes_to_csv(prod_space, graph_name='prod_space', dir_path='./data/')

Complete list of calculated indexes:

• Economic Complexity Index: comp.eci

• Product Complexity Index: comp.pci

• Country Diversity: comp.diversity

• Product Ubiquity: comp.ubiquity

• Balassa’s RCA: comp.rca

• Proximity: comp.proximity

• Density: comp.density

• Distance: comp.distance

You can also vary the threshold of RCA value when creating the Mcp matrix. The Complexity class accepts the parameter m_cp_thresh, which by default is 1.0.

comp.create_product_space() also accepts the argument edge_weight_thresh, by default 0.65. This argument filters edges to be added to the maximum spanning tree by weight.

References

[HaRH2014]

Hausmann, R., Hidalgo, C. A., Bustos, S., Coscia, M., Chung, S., Jimenez, J., … Yildirim, M. A. (2014). The Atlas of Economic Complexity: Mapping Paths to Prosperity. MIT Press.

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

0.1.0 (2020-06-06)

• First release on PyPI.