Christopher P. Chambers, Yusufcan Masatlioglu, Christopher Turansick
arXiv 5 Jan 2025 · Theoretical Economics
arXiv:2501.02609 · PDF · DOI · OpenAlex · Extracted main text
The linear-in-means model is the standard empirical model of peer effects. Using choice data and exogenous group variation, we first develop a revealed preference style test for the linear-in-means model. This test is formulated as a linear program and can be interpreted as a no money pump condition with an additional incentive compatibility constraint. We then study the identification properties of the linear-in-means model. A key takeaway from our analysis is that there is a close relationship between the dimension of the outcome variable and the identifiability of the model. Importantly, when the outcome variable is one-dimensional, failures of identification are generic. On the other hand, when the outcome variable is multi-dimensional, we provide natural conditions under which identification is generic.
appendix boundary found by appendix_command · 66% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Manski, C. F (1993) Identification of Endogenous Social Effects: The Reflection Problem | 1.000 | 16 | 5 | 100% |
| 2 | Blume, L. E., W. A. Brock, S. N. Durlauf, and R. Jayaraman (2015) Linear Social Interactions Models | 0.928 | 4 | 3 | 100% |
| 3 | De Paula, A., I. Rasul, and P. C. Souza (2024) Identifying network ties from panel data: Theory and an application to tax competition | 0.811 | 4 | 2 | 100% |
| 4 | Lewbel, A., X. Qu, and X. Tang (2023) Social networks with unobserved links | 0.737 | 3 | 2 | 100% |
| 5 | Ushchev, P. and Y. Zenou (2020) Social norms in networks | 0.737 | 3 | 2 | 100% |
| 6 | Boucher, V. and B. Fortin (2016) Some challenges in the empirics of the effects of networks | 0.644 | 2 | 2 | 100% |
| 7 | Bramoullé, Y., H. Djebbari, and B. Fortin (2009) Identification of peer effects through social networks | 0.644 | 2 | 2 | 100% |
| 8 | Cerreia-Vioglio, S., D. Dillenberger, P. Ortoleva, and G. Riella (2019) Deliberately Stochastic | 0.644 | 2 | 2 | 100% |
| 9 | Fudenberg, D., R. Iijima, and T. Strzalecki (2015) Stochastic choice and revealed perturbed utility | 0.644 | 2 | 2 | 100% |
| 10 | Golub, B. and S. Morris (2020) Expectations, networks, and conventions | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 60 scored citations.