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
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Bryan S. Grahama; Ăureo de PaulabaDepartment of Economics, University of California - Berkeley, Berkeley, CA, United States bUniversity College London, CeMMAP, IFS and CEPR, London, United Kingdom
Abstract
In this chapter we provide the foundational vocabulary for discussing, describing and summarizing network data. The chapter includes basic definitions, concepts such as centrality and a discussion of phenomena such as homophily and the social multiplier.
In this chapter we provide the foundational vocabulary for discussing, describing and summarizing network data like that shown in Fig. 1.1. This figure depicts buyerâsupplier relationships among publicly traded firms in the United States. Each dot (node or vertex) in the figure corresponds to a firm. If a firm, say, United Technologies Corporation, supplies inputs to another firm, say Boeing Corporation, then there exists a directed edge (also referred to as link or tie)
from United Technologies to Boeing. The supplying firm (left node) is called the tail of the edge, while the buying firm (right node) is its head. The set of all such supplierâbuyer relationships forms the graph
, a directed network or digraph defined on
vertices or agents (here publicly traded firms). The set
includes all agents (firms) in the network and
the set of all directed links (supplierâbuyer relationships) among them.1,2 The number of nodes N is sometimes referred to as the order of the digraph and
, its size.3
Figure 1.1 US buyerâsupplier production network, 2015. Sources: Compustat â Capital IQ and authors' calculations.
If i directs an edges to j, and j likewise directs and edge back to i, we say the link is reciprocated. In some sett...
Table of contents
Cover image
Title page
Table of Contents
Copyright
Preface
List of contributors
Chapter 1: Introduction
Chapter 2: Dyadic regression
Chapter 3: Strategic network formation
Chapter 4: Testing for externalities in network formation using simulation
Chapter 5: Econometric analysis of bipartite networks
Chapter 6: An empirical model for strategic network formation
Chapter 7: Econometric analysis of models with social interactions
Chapter 8: Many player asymptotics for large network formation problems