Alan Griffith

Working Papers

Random Assignment with Non-Random Peers: A Structural Approach to Counterfactual Treatment Assessment (submitted)

Economists' efforts to leverage peer effects by creative assignment have come up short due, in part, to endogenous peer choice. Even with random assignment, not accounting for agents' choice of peers may bias estimates of peer influence and, in turn, predictions of outcomes under alternative policies. To address this, I build a two-part model: (1) agents form a network by making continuous linking decisions; (2) conditional on the network, outcomes are determined allowing for peer effects and unobserved heterogeneity. I provide a method to recover unobserved heterogeneity in estimating the network formation process, leveraging new theoretical results. I estimate the model using innovative data from a randomized study in Indian schools, then assess the model's predictions against realized outcomes. This paper makes important contributions to the methodology of peer effects estimation, the theory and econometrics of network formation, and provides new links between structural and experimental approaches to policy evaluation.

Available here.

Network Partitioning and Social Exclusion under Different Selection Regimeswith Clara Delavallade and Rebecca Thornton

While most social programs are based on some form of exclusion of sub-populations, we know little about how being excluded, and the selection process, affect social inclusion. This paper compares peer effects of an after-school program, under three different (randomly assigned) network-formation regimes: endogenously formed, popularity vote, and randomly assigned. We find substantial evidence of homophily within endogenously-formed and elected networks. When participation was randomly assigned, we find segregation of friendships due to the program. We do not find this among elected networks, mainly because they were already highly partitioned. Lastly, we find that social exclusion – not being elected in a school with popular voting – reduced education aspirations and self-confidence.

Available here.

Participation, Learning, and Equity in Education -- Can We Have It All?with Clara Delavallade and Rebecca Thornton (submitted)

The Sustainable Development Goals set a triple educational objective: improving access to, quality of, and gender equity in education. This study is the first to document the effectiveness of a multifaceted educational program—delivered to 230 primary schools in rural India—on students’ participation and academic performance, while also examining heterogeneous impacts and sustainability. We find that the program reduced gender gaps in school retention and improved learning during the first year of implementation, but did not yield sustained effects on school attendance or learning, nor did it bridge gender inequalities in school performance over the two-year period.

Available here.

How Many Friends Do You Have? An Empirical Investigation into Censoring-Induced Bias in Social Network Data

In analyzing peer effects in a linear-in-means framework, identifying who interacts with whom is crucial. This suggests the need to collect detailed network data. However, taking a cue from AddHealth, many data-collection efforts only permit resondents to list up to a maximum number of links, leading to censoring and mismeasurement of peer groups. Within a linear-in-means framework, I document the extent of bias due to censoring analytically and by simulation. I then demonstrate that censoring-induced bias is present in empirical applications using data from AddHealth and an experiment in rural Nepal. After documenting the bias, I provide strategies to recover consistent estimates and discuss limitations of these strategies. This paper provides important contributions to the literature on design of network surveys as well as estimation of peer effects in the presence of data limitations.

Available here.

Selected Works in Progress

Equilibrium in Concave Network Formation Games

When Interventions Affect the Network: A Decomposition of Treatment Effects in a Partial Treatment Setting, with Clara Delavallade and Rebecca Thornton