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Fixed-Effect Regressions on Network Data

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  • Jochmans, K.
  • Weidner, M.

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

  • Jochmans, K. & Weidner, M., 2019. "Fixed-Effect Regressions on Network Data," Cambridge Working Papers in Economics 1938, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:1938
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    Cited by:

    1. Philippe Choné & Lionel Wilner, 2015. "Complementarity or substitutability in networks? Methodology and application to the hospital industry," Working Papers 2015-07, Center for Research in Economics and Statistics.
    2. Katarína Borovičková & Robert Shimer, 2017. "High Wage Workers Work for High Wage Firms," NBER Working Papers 24074, National Bureau of Economic Research, Inc.
    3. Thibaut Lamadon & Elena Manresa & Stephane Bonhomme, 2016. "Discretizing Unobserved Heterogeneity," 2016 Meeting Papers 1536, Society for Economic Dynamics.
    4. 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.
    5. Patrick Kline & Raffaele Saggio & Mikkel Sølvsten, 2020. "Leave‐Out Estimation of Variance Components," Econometrica, Econometric Society, vol. 88(5), pages 1859-1898, September.
    6. Kramarz, Francis & Martin, Julien & Mejean, Isabelle, 2020. "Volatility in the small and in the large: The lack of diversification in international trade," Journal of International Economics, Elsevier, vol. 122(C).
    7. Jochmans, K., 2019. "Heteroskedasticity-Robust Inference in Linear Regression Models," Cambridge Working Papers in Economics 1957, Faculty of Economics, University of Cambridge.
    8. Arthur Lewbel & Samuel Norris & Krishna Pendakur & Xi Qu, 2018. "Consumption Peer Effects and Utility Needs in India," Boston College Working Papers in Economics 958, Boston College Department of Economics, revised 30 Apr 2020.
    9. Esteves, Rui & Geisler Mesevage, Gabriel, 2019. "Social Networks in Economic History: Opportunities and Challenges," Explorations in Economic History, Elsevier, vol. 74(C).

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    More about this item

    Keywords

    connectivity; fixed effects; graph; Laplacian; limited mobility; teacher value-added; two-way regression model;

    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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