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Alireza Tahbaz-Salehi

Researcher at Northwestern University

Publications -  77
Citations -  8348

Alireza Tahbaz-Salehi is an academic researcher from Northwestern University. The author has contributed to research in topics: Random graph & Consensus. The author has an hindex of 32, co-authored 73 publications receiving 6812 citations. Previous affiliations of Alireza Tahbaz-Salehi include Center for Economic and Policy Research & Columbia University.

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Systemic Risk and Stability in Financial Networks

TL;DR: In this article, the authors provide a framework for studying the relationship between the financial network architecture and the likelihood of systemic failures due to contagion of counterparty risk, and show that financial contagion exhibits a form of phase transition as interbank connections increase.
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The Network Origins of Aggregate Fluctuations

TL;DR: In this paper, the authors argue that in the presence of intersectoral input-output linkages, microeconomic idiosyncratic shocks may lead to aggregate fluctuations and that the rate at which aggregate volatility decays is determined by the structure of the network capturing such linkages.
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The Network Origins of Aggregate Fluctuations

TL;DR: Acemoglu, Ozdaglar and Tahbaz-Salehi as mentioned in this paper combined material from Carvalho's Ph.D. dissertation at the University of Chicago (Carvalho, 2008) and ACEmoglu et al. (2010).
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Systemic risk and stability in financial networks

TL;DR: In this article, the authors argue that the extent of financial contagion exhibits a form of phase transition: as long as the magnitude of negative shocks affecting financial institutions are sufficiently small, a more densely connected financial network (corresponding to a more diversified pattern of interbank liabilities) enhances financial stability.
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A Necessary and Sufficient Condition for Consensus Over Random Networks

TL;DR: In this paper, a necessary and sufficient condition for almost sure asymptotic consensus using simple ergodicity and probabilistic arguments is presented. This easily verifiable condition uses the spectrum of the average weight matrix.