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Econometric methods for the analysis of networks.

Project description

netrics: a Python 2.7 package for econometric analysis of networks

by Bryan S. Graham, UC - Berkeley, e-mail:

This package includes a Python 2.7 implementation of the two econometric network formation models introduced in Graham (2014, NBER).

This package is offered “as is”, without warranty, implicit or otherwise. While I would appreciate bug reports, suggestions for improvements and so on, I am unable to provide any meaningful user-support. Please e-mail me at

Please cite both the code and the underlying source articles listed below when using this code in your research.

A simple example script to get started is:

>>>> # Import numpy in order to correctly read test data
>>>> import numpy as np

>>>> # Import urllib in order to download test data from Github repo
>>>> import urllib

>>>> # Append location of netrics module base directory to system path
>>>> # NOTE: only required if permanent install not made
>>>> # NOTE: edit path to location on netrics package on local machine
>>>> import sys
>>>> sys.path.append('/Users/bgraham/Dropbox/Sites/software/netrics/')

>>>> # Load netrics module
>>>> import netrics as netrics

>>>> # Download Nyakatoke test dataset from GitHub
>>>> download =  '/Users/bgraham/Dropbox/' # Edit to location on your machine
>>>> url = ''
>>>> urllib.urlretrieve(url, download + "Nyakatoke_Example.npz")

>>>> # Open dataset
>>>> NyakatokeTestDataset = np.load(download + "Nyakatoke_Example.npz")

>>>> # Extract adjacency matrix
>>>> D = NyakatokeTestDataset['D']

>>>> # Initialize list of dyad-specific covariates as elements
>>>> # W = [W0, W1, W2,...WK-1]
>>>> W = []

>>>> # Initialize list with covariate labels
>>>> cov_names = []

>>>> # Construct list of regressor matrices and corresponding variable names
>>>> for matrix in NyakatokeTestDataset.files:
>>>>     if matrix != 'D':
>>>>         W.append(NyakatokeTestDataset[matrix])
>>>>         cov_names.append(matrix)

>>>> # Apply tetrad logit procedure to dataset
>>>> [beta_TL, vcov_beta_TL, tetrad_frac_TL, success] = \
         netrics.tetrad_logit(D, W, dtcon=None, silent=False, W_names=cov_names)


Graham, Bryan S. (2016). “netrics: a Python 2.7 package for econometric analysis of

networks,” (Version 0.0.1) [Computer program]. Available at (Accessed 04 September 2016)


Graham, Bryan S. (2014). “An econometric model of link formation with degree

heterogeneity,” NBER Working Paper No. w20341.

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