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Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data

Author

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  • Emily Breza
  • Arun G. Chandrasekhar
  • Tyler H. McCormick
  • Mengjie Pan

Abstract

Social network data are often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD): responses to questions of the form "how many of your links have trait k?" Our method uses ARD to recover parameters of a network formation model, which permits sampling from a distribution over node- or graph-level statistics. We replicate the results of two field experiments that used network data and draw similar conclusions with ARD alone.

Suggested Citation

  • Emily Breza & Arun G. Chandrasekhar & Tyler H. McCormick & Mengjie Pan, 2020. "Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data," American Economic Review, American Economic Association, vol. 110(8), pages 2454-2484, August.
    • Handle: RePEc:aea:aecrev:v:110:y:2020:i:8:p:2454-84
    DOI: 10.1257/aer.20170861
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    Cited by:

    1. Roland Pongou & Guy Tchuente & Jean-Baptiste Tondji, 2020. "An Economic Model of Health-vs-Wealth Prioritization During COVID-19: Optimal Lockdown, Network Centrality, and Segregation," Working Papers 2009E Classification-E61,, University of Ottawa, Department of Economics.
    2. de Paula, Aureo & Rasul, Imran & Souza, Pedro, 2018. "Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition," CEPR Discussion Papers 12792, C.E.P.R. Discussion Papers.
    3. Chih‐Sheng Hsieh & Xu Lin, 2021. "Social interactions and social preferences in social networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 165-189, March.
    4. Mathieu Lambotte & Sandrine Mathy & Anna Risch & Carole Treibich, 2022. "Spreading active transportation: peer effects and key players in the workplace," Post-Print hal-03702684, HAL.
    5. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    6. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised Dec 2023.
    7. Mathieu Lambotte & Sandrine Mathy & Anna Risch & Carole Treibich, 2022. "Spreading active transportation: peer effects and key players in the workplace," Working Papers 2022-02, Grenoble Applied Economics Laboratory (GAEL).
    8. Xu, Hai-Chuan & Wang, Zhi-Yuan & Jawadi, Fredj & Zhou, Wei-Xing, 2023. "Reconstruction of international energy trade networks with given marginal data: A comparative analysis," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    9. Davide Viviano & Lihua Lei & Guido Imbens & Brian Karrer & Okke Schrijvers & Liang Shi, 2023. "Causal clustering: design of cluster experiments under network interference," Papers 2310.14983, arXiv.org, revised Jan 2024.
    10. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    11. Junhui Cai & Dan Yang & Wu Zhu & Haipeng Shen & Linda Zhao, 2021. "Network regression and supervised centrality estimation," Papers 2111.12921, arXiv.org.
    12. Björkegren, Daniel & Karaca, Burak Ceyhun, 2022. "Network adoption subsidies: A digital evaluation of a rural mobile phone program in Rwanda," Journal of Development Economics, Elsevier, vol. 154(C).
    13. Erol, Selman & Parise, Francesca & Teytelboym, Alexander, 2023. "Contagion in graphons," Journal of Economic Theory, Elsevier, vol. 211(C).
    14. Lina Zhang, 2020. "Spillovers of Program Benefits with Missing Network Links," Papers 2009.09614, arXiv.org, revised Apr 2023.
    15. Chen, Denghui & Kiefer, Hua & Liu, Xiaodong, 2022. "Estimation of discrete choice network models with missing outcome data," Regional Science and Urban Economics, Elsevier, vol. 97(C).
    16. Alejandro Sanchez-Becerra, 2022. "The Network Propensity Score: Spillovers, Homophily, and Selection into Treatment," Papers 2209.14391, arXiv.org.
    17. Francesca Parise & Asuman Ozdaglar, 2023. "Graphon Games: A Statistical Framework for Network Games and Interventions," Econometrica, Econometric Society, vol. 91(1), pages 191-225, January.
    18. Christiern Rose & Lizi Yu, 2021. "Identification of Peer Effects with Miss-specified Peer Groups: Missing Data and Group Uncertainty," Papers 2104.10365, arXiv.org, revised May 2022.
    19. Donia Kamel & Laura Pollacci, 2023. "Academic Migration and Academic Networks: Evidence from Scholarly Big Data and the Iron Curtain," CESifo Working Paper Series 10377, CESifo.
    20. José Tudón, 2022. "Distilling network effects from Steam," Quantitative Marketing and Economics (QME), Springer, vol. 20(3), pages 293-312, September.
    21. Victor Sellemi, 2022. "Risk in Network Economies," Papers 2208.01467, arXiv.org.
    22. Candelaria, Luis E. & Ura, Takuya, 2023. "Identification and inference of network formation games with misclassified links," Journal of Econometrics, Elsevier, vol. 235(2), pages 862-891.

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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