Название: The Econometric Analysis of Network Data
Автор: Bryan Graham, Aureo de Paula
Издательство: Academic Press
Год: 2020
Страниц: 268
Язык: английский
Формат: pdf (true), djvu
Размер: 10.1 MB

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

Readership:
Graduate students, first year PhDs, and active researchers in economics, computer science, statistics and related fields. Also relevant to data scientists in industry including Google, Amazon, Facebook and startups

Table of Contents:

Introduction
2. Dyadic regression
3. Strategic network formation
4. Testing for externalities in network formation using simulation
5. Econometric analysis of bipartite networks
6. An empirical model for strategic network formation
7. Econometric analysis of models with social interactions
8. Many player asymptotics for large network formation problems