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Code to reproduce figures in Bloch and Olckers (2020) "Friend-based Ranking" arXiv 1807.05093

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Friend-based Ranking

Analysis of social networks and simulations for Friend-based Ranking, a paper by Francis Bloch and Matthew Olckers.

Code is written in Python using Jupyter Notebooks and is executed in three steps:

extract_networks.ipynb

Extract the network data from India (Banerjee et al, 2013) and Indonesia (Alatas et al, 2020) and calculate various network statistics.

figures.ipynb

Produce figures from the network data and save the figures as PDFs.

homophily.ipynb

The homophily simulation and figure does not rely on the network data and is calculated in a separate notebook.

Each notebook is available as an html and PDF file to view the correct output of the code. You may also interact with the code online using Binder.

Binder

References

Banerjee, Abhijit; Chandrasekhar, Arun G.; Duflo, Esther; Jackson, Matthew O., 2013, "The Diffusion of Microfinance", https://doi.org/10.7910/DVN/U3BIHX, Harvard Dataverse, V9.

Alatas, Vivi, Banerjee, Abhijit, Chandrasekhar, Arun, Hanna, Rema, and Olken, Benjamin. Data and Code for: Network Structure and the Aggregation of Information: Theory and Evidence from Indonesia. Nashville, TN: American Economic Association [publisher], 2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-06-08. https://doi.org/10.3886/E119802V1

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Code to reproduce figures in Bloch and Olckers (2020) "Friend-based Ranking" arXiv 1807.05093

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