Andrin Pelican, Bryan S. Graham
arXiv 1 Sep 2020 · Econometrics · 3 citations (OpenAlex)
arXiv:2009.00212 · PDF · DOI · OpenAlex · Extracted main text
Consider a setting where $N$ players, partitioned into $K$ observable types, form a directed network. Agents' preferences over the form of the network consist of an arbitrary network benefit function (e.g., agents may have preferences over their network centrality) and a private component which is additively separable in own links. This latter component allows for unobserved heterogeneity in the costs of sending and receiving links across agents (respectively out- and in- degree heterogeneity) as well as homophily/heterophily across the $K$ types of agents. In contrast, the network benefit function allows agents' preferences over links to vary with the presence or absence of links elsewhere in the network (and hence with the link formation behavior of their peers). In the null model which excludes the network benefit function, links form independently across dyads in the manner described by \cite{Charbonneau_EJ17}. Under the alternative there is interdependence across linking decisions (i.e., strategic interaction). We show how to test the null with power optimized in specific directions. These alternative directions include many common models of strategic network formation (e.g., "connections" models, "structural hole" models etc.). Our random utility specification induces an exponential family structure under the null which we exploit to construct a similar test which exactly controls size (despite the the null being a composite one with many nuisance parameters). We further show how to construct locally best tests for specific alternatives without making any assumptions about equilibrium selection. To make our tests feasible we introduce a new MCMC algorithm for simulating the null distributions of our test statistics.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Charbonneau, K. B (2017) Multiple fixed effects in binary response panel data models | 1.000 | 13 | 5 | 100% |
| 2 | Kleinberg, J., Suri, S., Tardos, É., and Wexler, T (2008) Strategic network formation with structural holes | 1.000 | 10 | 4 | 100% |
| 3 | De Weerdt, J (2004) Insurance Against Poverty, chapter Risk-sharing and endogenous network formation, pages 197 – 216 | 1.000 | 8 | 5 | 100% |
| 4 | Goyal, S (2022) Networks: An economics approach | 1.000 | 5 | 4 | 100% |
| 5 | Bala, V. and Goyal, S (2000) A noncooperative model of network formation | 1.000 | 5 | 3 | 100% |
| 6 | Blitzstein, J. and Diaconis, P (2011) A sequential importance sampling algorithm for generating random graphs with prescribed degrees | 1.000 | 5 | 3 | 100% |
| 7 | Lehmann, E. L. and Romano, J. P (2005) Testing Statistical Hypotheses | 1.000 | 5 | 3 | 100% |
| 8 | Jackson, M. O (2008) Social and Economic Networks | 0.928 | 4 | 4 | 100% |
| 9 | Burt, R. S (1995) Structural Holes: The Social Structure of Competition | 0.928 | 4 | 3 | 100% |
| 10 | Jackson, M. O. and Wolinsky, A (1996) A strategic model of social and economic networks | 0.928 | 4 | 3 | 100% |
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