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Team Networks with Partially Observed Links

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  • Yang Xu

Abstract

This paper studies a linear production model in team networks with missing links. In the model, heterogeneous workers, represented as nodes, produce jointly and repeatedly within teams, represented as links. Links are omitted when their associated outcome variables fall below a threshold, resulting in partial observability of the network. To address this, I propose a Generalized Method of Moments estimator under normally distributed errors and develop a distribution-free test for detecting link truncation. Applied to academic publication data, the estimator reveals and corrects a substantial downward bias in the estimated scaling factor that aggregates individual fixed effects into team-specific fixed effects. This finding suggests that the collaboration premium may be systematically underestimated when missing links are not properly accounted for.

Suggested Citation

  • Yang Xu, 2025. "Team Networks with Partially Observed Links," Papers 2505.08405, arXiv.org, revised Oct 2025.
    • Handle: RePEc:arx:papers:2505.08405
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    References listed on IDEAS

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    1. Lena Abou El-Komboz & Thomas A. Fackler & Moritz Goldbeck & Thomas Fackler, 2024. "Productivity Spillovers among Knowledge Workers in Agglomerations: Evidence from GitHub," CESifo Working Paper Series 11277, CESifo.
    2. Katharine A. Anderson & Seth Richards-Shubik, 2022. "Collaborative Production in Science: An Empirical Analysis of Coauthorships in Economics," The Review of Economics and Statistics, MIT Press, vol. 104(6), pages 1241-1255, November.
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