Field Experiments, Social Networks, and Development

This chapter explores the use of field experiments as a tool to study the economics of social networks, with an emphasis on applications in development economics. Field experiments can be powerful vehicles to measure causal treatment effects. However, when treatments “spill over” onto others in the social network, many new considerations arise. The chapter begins with a discussion of methodological challenges involved in conducting social network experiments. The chapter then explores how field experiments have begun to shed light on five key issues in the economics of networks, including social learning and diffusion, other-regarding preferences, peer monitoring and enforcement, risk sharing, and network formation.

Games Played on Networks

This chapter studies games played on fixed networks. These games capture a wide variety of economic settings, including local public goods, peer effects, and technology adoption. The chapter establishes a common analytical framework to study a wide game class. The authors review and advance existing results by showing how they tie together within the common framework. The chapter discusses the game-theoretic underpinnings of key notions including Bonacich centrality and the lowest and largest eigenvalue. The text discusses the interplay of individual heterogeneity and the network and develops a new notion—interdependence—to analyze how a shock to one agent affects the action of another agent.

Networked Experiments

This chapter considers the design and analysis of networked experiments. As a result of digitization, the scale, scope, and complexity of networked experiments have expanded significantly in recent years, creating a need for more robust design and analysis strategies. This chapter first reviews innovations in networked experimental design, assessing the implications of the experimental setting, sampling, randomization procedures, and treatment assignment. Then the analysis of networked experiments is discussed, with particular emphasis on modeling treatment response assumptions, inference, and estimation, and recent approaches to interference and uncertainty in dependent data. The chapter concludes by discussing important challenges facing the future of networked experimentation, focusing on adaptive treatment assignment, novel randomization techniques, linking online treatments to offline responses, and experimental validation of observational methods. I hope this framework can help guide future work toward a cumulative research tradition in networked experimentation.

Learning in Social Networks

This survey covers models of how agents update behaviors and beliefs using information conveyed through social connections. The chapter begins with sequential social learning models, in which each agent makes a decision once and for all after observing a subset of prior decisions; the discussion is organized around the concepts of diffusion and aggregation of information. Next, the chapter presents the DeGroot framework of average-based repeated updating, whose long- and medium-run dynamics can be completely characterized in terms of measures of network centrality and segregation. Finally, the chapter turns to various models of repeated updating that feature richer optimizing behavior, and concludes by urging the development of network learning theories that can deal adequately with the observed phenomenon of persistent disagreement.

Diffusion in Networks

This chapter examines models of diffusion in networks, and specifically how the topology of the network impacts the spreading process. The chapter begins by discussing epidemiological models and how stochastic dominance relations can be used to understand the effect of the degree distribution of the network. The chapter then turns to more sophisticated models of social influence, including threshold models and models of social learning. A key insight that emerges from the collection of models discussed is that not only does network structure matter, but how the network matters depends on the way in which agents influence one another. Network features that facilitate contagion under one model of influence can inhibit diffusion in another. The chapter concludes with thoughts on directions for future research.

Strategic Models of Intermediation Networks

This chapter surveys a set of papers that analyze strategic intermediation in networks. In all these papers, the architecture of the network has an impact on how surplus is shared across trading parties by determining the level of competition and outside options of traders,. The chapter emphasizes the insights that are most recurrent in the literature .

Repeated Games and Networks

The chapter provides an overview of recent results on infinitely repeated games in which monitoring and interactions are local. The chapter surveys Folk Theorems for games with local monitoring, and results characterizing optimal punishments in separable local public goods games. The relationship between the monitoring structure and the equilibrium correspondence is a key topic of enquiry. Results clarify the roles played by contagion, ostracism, and communication in shaping equilibrium outcomes. Understanding how network measures of social cohesion and of information diffusion can affect trust in communities is the main applied aim of the literature.

Social Networks and the Labor Market

This chapter provides an overview of the role of social networks in the labor market. Both workers and firms report widespread use of social contacts in labor market search. The objective of the chapter is to survey various models for why firms and workers use social contacts, with a focus on empirical predictions. The main explanations explored include: search costs, imperfect information about worker productivity or match quality, and peer effects. The chapter then turns to summarizing the empirical evidence related to the existing theoretical predictions. The chapter concludes by highlighting holes in the existing literature and the need for additional empirical and theoretical work.

Models of Bilateral Trade in Networks

This chapter reviews the research on bilateral trade in markets with a network structure. The survey focuses on the following questions: how do local prices depend on global network architecture? When does the law of one price hold? How do competitive forces in different segments of the market influence the bargaining power of each position in the network? Is trade efficient? How does the network evolve as traders reach agreements and exit the market? If forming links is costly for the traders, what networks will emerge? How does the underlying market mechanism affect payoffs and allocations?

Economic Features of the Internet and Network Neutrality

The chapter discusses the issue of a possible abolition of network neutrality and the introduction of paid prioritization by residential broadband access networks. In short-run analysis where bandwidth is fixed and in the absence of congestion, network neutrality tends to maximize total surplus. When an ISP violates network neutrality and invests the extra profits to bandwidth expansion, the presence of more bandwidth alleviates the allocative distortion, and can even reverse it. The chapter discusses the network neutrality issue under the assumption of congestion, and characterizes the set of utility functions for which network neutrality is optimal, as well as utility functions where it is optimal to prioritize. The chapter also reviews regulatory rules in the United States on network neutrality.