Moment-Based Estimation of Diffusion and Adoption Parameters in Networks

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Date

4 septembre 2023

Type de document
Périmètre
Identifiant
  • 2309.01489
Collection

arXiv

Organisation

Cornell University




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L. S. Sanna Stephan, « Moment-Based Estimation of Diffusion and Adoption Parameters in Networks », arXiv - économie


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According to standard econometric theory, Maximum Likelihood estimation (MLE) is the efficient estimation choice, however, it is not always a feasible one. In network diffusion models with unobserved signal propagation, MLE requires integrating out a large number of latent variables, which quickly becomes computationally infeasible even for moderate network sizes and time horizons. Limiting the model time horizon on the other hand entails loss of important information while approximation techniques entail a (small) error that. Searching for a viable alternative is thus potentially highly beneficial. This paper proposes two estimators specifically tailored to the network diffusion model of partially observed adoption and unobserved network diffusion.

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