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Two-Step Estimation of a Strategic Network Formation Model with Clustering

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arxiv 2001.03838 v4 pith:NGW4PTHI submitted 2020-01-12 econ.EM

classification econ.EM
keywords linknetworkchoicesfunctionlargeutilitycommonfavor
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper explores strategic network formation under incomplete information using data from a single large network. We allow the utility function to be nonseparable in an individual's link choices to capture the spillover effects from friends in common. In a network with n individuals, an individual with a nonseparable utility function chooses between 2^{n-1} overlapping portfolios of links. We develop a novel approach that applies the Legendre transform to the utility function so that the optimal link choices can be represented as a sequence of correlated binary choices. The link dependence that results from the preference for friends in common is captured by an auxiliary variable introduced by the Legendre transform. We propose a two-step estimator that is consistent and asymptotically normal. We also derive a limiting approximation of the game as n grows large that simplifies the computation in large networks. We apply these methods to favor exchange networks in rural India and find that the direction of support from a mutual link matters in facilitating favor provision.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Single-Network Finite-Sample Inference in Strategic Network Formation Models

    econ.EM 2026-07 accept novelty 8.0 of 10

    A single observed network suffices for finite-sample valid confidence sets on the strategic-complementarity parameter in network formation models, via realization-wise sandwich inequalities and simulated critical values.

  2. Discrete Choice with Endogenous Peer Selection

    econ.EM 2025-11 conditional novelty 6.0 of 10

    A continuous-time discrete choice model with endogenous peer attention is shown to be nonparametrically identifiable from long choice panels using variation in the number of potential peers.

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