The Econometric Analysis of Network Data serves as an entry point for advanced students, researchers, and data scientists seeking to perform effective analyses of networks, especially inference problems. It introduces the key results and ideas in an accessible, yet rigorous way. While a multi-contributor reference, the work is tightly focused and disciplined, providing latitude for varied specialties in one authorial voice.

Answers both ‘why’ and ‘how’ questions in network analysis, bridging the gap between practice and theory allowing for the easier entry of novices into complex technical literature and computation
Fully describes multiple worked examples from the literature and beyond, allowing empirical researchers and data scientists to quickly access the ‘state of the art’ versioned for their domain environment, saving them time and money
Disciplined structure provides latitude for multiple sources of expertise while retaining an integrated and pedagogically focused authorial voice, ensuring smooth transition and easy progression for readers
Fully supported by companion site code repository
40+ diagrams of ‘networks in the wild’ help visually summarize key points

About the Authors

Bryan Graham is a Professor of Economics at the University of California – Berkeley. His research focuses on missing data, panel data and, especially, the analysis of social networks and spillovers. His work has appeared in Econometrica and the Review of Economic Studies. Bryan is a co-editor at the Review of Economics and Statistics.

Aureo de Paula is a Professor of Economics at University College London. His research focuses on the econometric analysis of games and networks. His work has appeared in Econometrica and the Review of Economic Studies. Aureo was also a co-editor at the Review of Economic Studies.

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