The AMSE Summer School 2020 covers recent theories and empirical approaches that economists have designed to study complex interactions within networks of individuals, firms and governments.
Networks permeate our daily lives. Individuals learn about new products and job opportunities through family, friends, neighbors and colleagues. Firms’ choice of technology is heavily influenced by spillovers from nearby firms and competitors. Governments’ policies are shaped by international alliances and institutions. In these examples, the behaviour of agents (individuals, firms and governments) affects other agents, whose response might affect other agents, and so on. Economists study how these interactions develop through complex networks and have profound effects in different areas -- labour markets, competition among firms, political beliefs and outcomes, to name a few.
During the three days of the Summer School, students will get rigorous and in-depth exposure to the most recent theories and empirical methods in the economics of networks. Lectures will be given by leading experts in the field: Lori Beaman (Northwestern University), Sanjeev Goyal (University of Cambridge), Yann Bramoullé (CNRS, AMSE) and Habiba Djebbari (Aix-Marseille University, AMSE).
This year’s summer school should be of interest to graduate students or academics who want to expand their knowledge in this thriving area of research and to practitioners who want to familiarize themselves with the key issues affecting network structures. Faculty is available to discuss research projects and ideas and to provide feedback throughout the three days of the Summer School.
The Summer School starts on Wednesday, July 7th in the morning and ends on Friday, July 9th in the afternoon.
DAY-1 Network interventions and inequality: Theory and experimental evidence (S. Goyal)
In this module, we will study the implications of interventions within a network. Over the past two decades, research has clarified the empirical structure of networks and how this shapes individual behaviour and collective outcomes. Given the widespread externalities inherent in many contexts, a natural next step is to examine ways in which a government or a firm can intervene in a network in pursuit of its goals. Inequality is another well-established feature of prominent economic networks.
We will analyse models of network formation that can account for inequality in connections, which give rise to social influence and disparities in payoffs. The presentation of formal models will be accompanied by a discussion of the related empirical evidence. In particular, we will refer to recent experimental studies that highlight new findings on learning rules and on the salience of unequal networks. By the end of this module, students should be familiar with the structure of the most important models of economic networks and able to assess their predictions in different empirical settings.
DAY-2 Networks in developing countries (L. Beaman)
In this module, we will discuss how social networks play an important role in facilitating social and economic interactions in communities in developing countries. A key difference in the economic landscape between rich and poor countries is that many developing countries lack formal institutions such as insurance and government safety nets. Social networks play a crucial role in filling in - albeit imperfectly – these gaps.
We will start by discussing how the broader literature on social learning and diffusion applies to developing country contexts. We will then focus on two key sectors: agriculture and credit/savings. This module will emphasize the interplay between theory and empirics, particularly experimental approaches. We will also discuss measurement challenges and recent innovations in generating social network data in developing country contexts. By the end of this module, students should be able to identify important economic questions related to social networks in developing countries and generate experimental approaches to answer them.
DAY-3 Peer effects in networks (Y. Bramoullé and H. Djebbari)
In this module, we will review the approaches that economists have adopted to identify and estimate peer effects in networks. Individuals appear to be affected by their peers in many contexts including labour supply, academic achievement, consumption, voting and obesity. Causal identification of peer effects is challenging, however, because of unobserved correlated shocks, for instance due to network endogeneity, and of the reflection problem.
We will study the different methods and models used by applied researchers to address these challenges, with a focus on the advantages and drawbacks of network data and network interactions. We will discuss the micro-foundations of the econometric models and the relationship between network theory and the econometrics of peer effects. We will provide an overview of state-of-the-art statistical and econometric approaches developed to analyze peer effects in networks, including random peers, randomized treatments in the presence of network spillovers and models of peer effects in endogenous networks. By the end of this module, students should be able to identify the main challenges in identifying and estimating peer effects in networks and propose viable econometric approaches.
Workshop and poster sessions
Students are strongly encouraged to present their research in workshop and poster sessions during the Summer School. This is a unique opportunity to have focused and valuable feedback from peers and from distinguished faculty. The schedule of paper presentations and poster sessions will be distributed in due course.
At the conclusion of the Summer School, participants will receive a certificate of attendance outlining the number of hours attended. Interested students should check with their universities to see if these hours are transferable into ECTS credits.
For more information click "LINK TO ORIGINAL" below.