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Fixed-Effect Regressions on Network Data

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  • Koen Jochmans
  • Martin Weidner

Abstract

This paper considers inference on fixed effects in a linear regression model estimated from network data. An important special case of our setup is the two-way regression model. This is a workhorse technique in the analysis of matched data sets, such as employer-employee or student-teacher panel data. We formalize how the structure of the network affects the accuracy with which the fixed effects can be estimated. This allows us to derive sufficient conditions on the network for consistent estimation and asymptotically-valid inference to be possible. Estimation of moments is also considered. We allow for general networks and our setup covers both the dense and sparse case. We provide numerical results for the estimation of teacher value-added models and regressions with occupational dummies.

Suggested Citation

  • Koen Jochmans & Martin Weidner, 2016. "Fixed-Effect Regressions on Network Data," Papers 1608.01532, arXiv.org, revised Apr 2019.
  • Handle: RePEc:arx:papers:1608.01532
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    3. Thibaut Lamadon & Elena Manresa & Stephane Bonhomme, 2016. "Discretizing Unobserved Heterogeneity," 2016 Meeting Papers 1536, Society for Economic Dynamics.
    4. Ajay Bhaskarabhatla & Luis Cabral & Deepak Hegde & Thomas Peeters, 2021. "Are Inventors or Firms the Engines of Innovation?," Management Science, INFORMS, vol. 67(6), pages 3899-3920, June.
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    6. Vanessa Alviarez & Keith Head & Thierry Mayer, 2020. "Global giants and local stars: How changes in brand ownership affect competition," Sciences Po Economics Discussion Papers 2020-04, Sciences Po Departement of Economics.
    7. Patrick Kline & Raffaele Saggio & Mikkel Sølvsten, 2020. "Leave‐Out Estimation of Variance Components," Econometrica, Econometric Society, vol. 88(5), pages 1859-1898, September.
    8. Faia, Ester & Ottaviano, Gianmarco & Spinella, Saverio, 2022. "Robot Adoption, Worker-Firm Sorting and Wage Inequality: Evidence from Administrative Panel Data," CEPR Discussion Papers 17451, C.E.P.R. Discussion Papers.
    9. Weidner, Martin & Zylkin, Thomas, 2021. "Bias and consistency in three-way gravity models," Journal of International Economics, Elsevier, vol. 132(C).
    10. Jochmans, K., 2019. "Heteroskedasticity-Robust Inference in Linear Regression Models," Cambridge Working Papers in Economics 1957, Faculty of Economics, University of Cambridge.
    11. Halvarsson, Daniel & Lark, Olga & Gustavsson Tingvall, Patrik, 2022. "Foreign Ownership and Transferring of Gender Norms," Working Paper Series 1433, Research Institute of Industrial Economics.
    12. Katarína Borovičková & Robert Shimer, 2017. "High Wage Workers Work for High Wage Firms," NBER Working Papers 24074, National Bureau of Economic Research, Inc.
    13. Halvarsson, Daniel & Lark, Olga & Gustavsson Tingvall, Patrik, 2022. "Foreign Ownership and Transferring of Gender Norms," Working Papers 2022:6, Lund University, Department of Economics.
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    15. Michael P. Leung, 2023. "Network Cluster‐Robust Inference," Econometrica, Econometric Society, vol. 91(2), pages 641-667, March.
    16. Peeters, Thomas & van Ours, Jan C., 2022. "International Assortative Matching in the European Labor Market," IZA Discussion Papers 15521, Institute of Labor Economics (IZA).
    17. repec:hal:wpspec:info:hdl:2441/6q707l4svn8k3bt630nhgdqgdu is not listed on IDEAS
    18. Esteves, Rui & Geisler Mesevage, Gabriel, 2019. "Social Networks in Economic History: Opportunities and Challenges," Explorations in Economic History, Elsevier, vol. 74(C).
    19. Philippe CHONÉ & Lionel WILNER, 2019. "Competition on Unobserved Attributes: The Case of the Hospital Industry," Working Papers 2019-21, Center for Research in Economics and Statistics.
    20. Arthur Lewbel & Samuel Norris & Krishna Pendakur & Xi Qu, 2022. "Consumption peer effects and utility needs in India," Quantitative Economics, Econometric Society, vol. 13(3), pages 1257-1295, July.
    21. Junhui Cai & Dan Yang & Wu Zhu & Haipeng Shen & Linda Zhao, 2021. "Network regression and supervised centrality estimation," Papers 2111.12921, arXiv.org.
    22. Bartanen, Brendan & Husain, Aliza N., 2022. "Connected networks in principal value-added models," Economics of Education Review, Elsevier, vol. 90(C).

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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