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An econometric model of network formation with degree heterogeneity

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  • Bryan S. Graham

    (Institute for Fiscal Studies and University of California, Berkeley)

Abstract

I introduce a model of undirected dyadic link formation which allows for assortative matching on observed agent characteristics (homophily) as well as unrestricted agent level heterogeneity in link surplus (degree heterogeneity). Like in fixed effects panel data analyses, the joint distribution of observed and unobserved agent-level characteristics is left unrestricted. Two estimators for the (common) homophily parameter, ß0 , are developed and their properties studied under an asymptotic sequence involving a single network growing large. The first, tetrad logit (TL), estimator conditions on a sufficient statistic for the degree heterogeneity. The second, joint maximum likelihood (JML), estimator treats the degree heterogeneity {Ai0}Ni=1 as additional (incidental) parameters to be estimated. The TL estimate is consistent under both sparse and dense graph sequences, whereas consistency of the JML estimate is shown only under dense graph sequences. Supplement for CWP 08/17

Suggested Citation

  • Bryan S. Graham, 2017. "An econometric model of network formation with degree heterogeneity," CeMMAP working papers CWP08/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:08/17
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    References listed on IDEAS

    as
    1. repec:hal:spmain:info:hdl:2441/dpido2upv86tqc7td18fd2mna is not listed on IDEAS
    2. Miyauchi, Yuhei, 2016. "Structural estimation of pairwise stable networks with nonnegative externality," Journal of Econometrics, Elsevier, vol. 195(2), pages 224-235.
    3. 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.
    4. Manski, Charles F, 1987. "Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data," Econometrica, Econometric Society, vol. 55(2), pages 357-362, March.
    5. Orazio Attanasio & Abigail Barr & Juan Camilo Cardenas & Garance Genicot & Costas Meghir, 2012. "Risk Pooling, Risk Preferences, and Social Networks," American Economic Journal: Applied Economics, American Economic Association, vol. 4(2), pages 134-167, April.
    6. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    7. Áureo de Paula & Seth Richards-Shubik & Elie Tamer, 2015. "Identification of preferences in network formation games," CeMMAP working papers CWP29/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Bloch, Francis & Jackson, Matthew O., 2007. "The formation of networks with transfers among players," Journal of Economic Theory, Elsevier, vol. 133(1), pages 83-110, March.
    9. Jackson, Matthew O. & López-Pintado, Dunia, 2013. "Diffusion and contagion in networks with heterogeneous agents and homophily," Network Science, Cambridge University Press, vol. 1(1), pages 49-67, April.
    10. Karyne B. Charbonneau, 2014. "Multiple Fixed Effects in Binary Response Panel Data Models," Staff Working Papers 14-17, Bank of Canada.
    11. Nicholas Christakis & James Fowler & Guido Imbens & Karthik Kalyanaraman, 2010. "An empirical model for strategic network formation," CeMMAP working papers CWP16/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. repec:hal:spmain:info:hdl:2441/5l8aj0dpmg9pbahnt8a4k2fcrh is not listed on IDEAS
    13. Benjamin Golub & Matthew O. Jackson, 2012. "How Homophily Affects the Speed of Learning and Best-Response Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1287-1338.
    14. J. M. C. Santos Silva & Silvana Tenreyro, 2006. "The Log of Gravity," The Review of Economics and Statistics, MIT Press, vol. 88(4), pages 641-658, November.
    15. Bryan S. Graham, 2015. "Methods of Identification in Social Networks," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 465-485, August.
    16. Ting Yan & Jinfeng Xu, 2013. "A central limit theorem in the β-model for undirected random graphs with a diverging number of vertices," Biometrika, Biometrika Trust, vol. 100(2), pages 519-524.
    17. Vaart,A. W. van der, 2000. "Asymptotic Statistics," Cambridge Books, Cambridge University Press, number 9780521784504, September.
    18. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers 52/15, Institute for Fiscal Studies.
    19. Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
    20. Elie Tamer, 2003. "Incomplete Simultaneous Discrete Response Model with Multiple Equilibria," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(1), pages 147-165.
    21. Bryan S. Graham, 2016. "Homophily and transitivity in dynamic network formation," CeMMAP working papers CWP16/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. repec:dau:papers:123456789/10840 is not listed on IDEAS
    23. Angelo Mele, 2010. "A structural model of segregation in social networks," CeMMAP working papers CWP32/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    24. Brian Lai & Dan Reiter, 2000. "Democracy, Political Similarity, and International Alliances, 1816-1992," Journal of Conflict Resolution, Peace Science Society (International), vol. 44(2), pages 203-227, April.
    25. Jackson Matthew O. & Rogers Brian W., 2007. "Relating Network Structure to Diffusion Properties through Stochastic Dominance," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 7(1), pages 1-16, February.
    26. Jeremy T. Fox, 2010. "Identification in matching games," Quantitative Economics, Econometric Society, vol. 1(2), pages 203-254, November.
    27. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 225-238.
    28. Jinyong Hahn & Whitney Newey, 2004. "Jackknife and Analytical Bias Reduction for Nonlinear Panel Models," Econometrica, Econometric Society, vol. 72(4), pages 1295-1319, July.
    29. Coren L. Apicella & Frank W. Marlowe & James H. Fowler & Nicholas A. Christakis, 2012. "Social networks and cooperation in hunter-gatherers," Nature, Nature, vol. 481(7382), pages 497-501, January.
    30. Marcel Fafchamps & Flore Gubert, 2007. "Risk Sharing and Network Formation," American Economic Review, American Economic Association, vol. 97(2), pages 75-79, May.
    31. Jackson, Matthew O. & Watts, Alison, 2002. "The Evolution of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 106(2), pages 265-295, October.
    32. repec:hal:wpspec:info:hdl:2441/dpido2upv86tqc7td18fd2mna is not listed on IDEAS
    33. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
    34. Honore, Bo E. & Powell, James L., 1994. "Pairwise difference estimators of censored and truncated regression models," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 241-278.
    35. B. Prakasa Rao, 2009. "Conditional independence, conditional mixing and conditional association," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(2), pages 441-460, June.
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    More about this item

    Keywords

    Network formation; homophily; degree heterogeneity; scale-free networks; incidental parameters; asymptotic bias; fixed effects; conditional likelihood; dependent U-Process;
    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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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