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Robust Network Targeting with Multiple Nash Equilibria

Guanyi Wang

arXiv 28 Oct 2024 · Econometrics

arXiv:2410.20860 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Many policy problems involve designing individualized treatment allocation rules to maximize the equilibrium social welfare of interacting agents. Focusing on large-scale simultaneous decision games with strategic complementarities, we develop a method to estimate an optimal treatment allocation rule that is robust to the presence of multiple equilibria. Our approach remains agnostic about changes in the equilibrium selection mechanism under counterfactual policies, and we provide a closed-form expression for the boundary of the set-identified equilibrium outcomes. To address the incompleteness that arises when an equilibrium selection mechanism is not specified, we use the maximin welfare criterion to select a policy, and implement this policy using a greedy algorithm. We establish a performance guarantee for our method by deriving a welfare regret bound, which accounts for sampling uncertainty and the use of the greedy algorithm. We demonstrate our method with an application to the microfinance dataset of Banerjee et al. (2013).

Citation extraction

121
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in-text mentions
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distinct cited
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main-text words

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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Bajari, P., H. Hong, J. Krainer, and D. Nekipelov (2010) a): Estimating static models of strategic interactions1.00083100%
2Leung, M. P (2015) Two-step estimation of network-formation models with incomplete information1.00074100%
3Brock, W. A. and S. N. Durlauf (2001) Discrete choice with social interactions1.00063100%
4Ridder, G. and S. Sheng (2020) Two-step estimation of a strategic network formation model with clustering1.00053100%
5Tamer, E (2003) Incomplete simultaneous discrete response model with multiple equilibria1.00053100%
6Banerjee, A., A. G. Chandrasekhar, E. Duflo, and M. O. Jackson (2013) The Diffusion of Microfinance0.9619489%
7Chamberlain, G (2000) a): Econometric applications of maxmin expected utility0.92843100%
8Galeotti, A., B. Golub, and S. Goyal (2020) Targeting interventions in networks0.92843100%
9de Paula, A. and X. Tang (2012) Inference of signs of interaction effects in simultaneous games with incomplete information0.87452100%
10Kitagawa, T. and G. Wang (2023) a): Individualized Treatment Allocation in Sequential Network Games0.87452100%

Showing the top 10 of 121 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Individualized Treatment Allocation in Sequential Network Games0.51121