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Estimating Models with Dynamic Network Interactions and Unobserved Heterogeneity

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Abstract

In this paper, we propose an approach to estimate models with network interactions in the presence of individual unobserved heterogeneity. The latter may impact the formation of ties and/or exogenous effects, thereby undermining identification of the associated parameters. In a panel setting, we devise a way to cope with these sources of endogeneity by relying on observable variations. When exogenous effects are involved, one can control for unobserved heterogeneity by including time-averages of the endogenous variables. When unobserved individual traits affect the process of network formation, it is possible to explore the role of network statistics. We derive a 2SLS estimator in order to address simultaneity bias, relying on sources of variation provided by the product between successive powers of the network matrix and the matrix of exogenous covariates; we assess the performances of the method via a Monte Carlo exercise, considering various combination of models and different ranges of parameters for both network interactions and the social multiplier. We also separately assess the cases in which unobserved sources hit the network structure only or act on exogenous effects as well. Focusing on the former case, our approach may be also applied when a simple cross-section is available. More generally, it does not require full knowledge of the spectrum of agents' interactions.

Suggested Citation

  • Luisa Corrado & Salvatore Di Novo, 2018. "Estimating Models with Dynamic Network Interactions and Unobserved Heterogeneity," CEIS Research Paper 439, Tor Vergata University, CEIS, revised 06 Nov 2018.
  • Handle: RePEc:rtv:ceisrp:439
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    1. Paul Goldsmith-Pinkham & Guido W. Imbens, 2013. "Social Networks and the Identification of Peer Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 253-264, July.
    2. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    3. à ureo de Paula & Seth Richards†Shubik & Elie Tamer, 2018. "Identifying Preferences in Networks With Bounded Degree," Econometrica, Econometric Society, vol. 86(1), pages 263-288, January.
    4. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2014. "Spatial lag models with nested random effects: An instrumental variable procedure with an application to English house prices," Journal of Urban Economics, Elsevier, vol. 80(C), pages 76-86.
    5. Steven N. Durlauf, 1993. "Nonergodic Economic Growth," Review of Economic Studies, Oxford University Press, vol. 60(2), pages 349-366.
    6. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    7. Lung-fei Lee, 2003. "Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 307-335.
    8. Gibbons, Steve & Overman, Henry G. & Patacchini, Eleonora, 2015. "Spatial Methods," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 115-168, Elsevier.
    9. Blume Lawrence E., 1993. "The Statistical Mechanics of Strategic Interaction," Games and Economic Behavior, Elsevier, vol. 5(3), pages 387-424, July.
    10. Horrace, William C. & Liu, Xiaodong & Patacchini, Eleonora, 2016. "Endogenous network production functions with selectivity," Journal of Econometrics, Elsevier, vol. 190(2), pages 222-232.
    11. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2011. "Criminal Networks: Who is the Key Player?," Research Papers in Economics 2011:7, Stockholm University, Department of Economics.
    12. Bryan S. Graham, 2015. "Methods of Identification in Social Networks," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 465-485, August.
    13. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    14. Bryan S. Graham, 2017. "An Econometric Model of Network Formation With Degree Heterogeneity," Econometrica, Econometric Society, vol. 85, pages 1033-1063, July.
    15. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    16. William A. Brock, 1993. "Pathways to randomness in the economy: Emergent nonlinearity and chaos in economics and finance," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 8(1), pages 3-55.
    17. Wansbeek, Tom & Kapteyn, Arie, 1982. "A Class of Decompositions of the Variance-Covariance Matrix of a Generalized Error Components Model," Econometrica, Econometric Society, vol. 50(3), pages 713-724, May.
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    More about this item

    Keywords

    Networks; Individual Unobserved Heterogeneity; Dynamic Network Formation; network Statistics.;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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