Tahbaz-Salehi_Alireza 03152018
Alireza Tahbaz-Salehi

Associate Professor of Managerial Economics & Decision Sciences

Print Overview

Alireza Tahbaz-Salehi joined the Managerial Economics and Decision Sciences Department at the Kellogg School of Management in 2017. Prior to joining Kellogg, he was the Daniel W. Stanton Associate Professor of Business at Columbia Business School. His research focuses on the implications of network economies for information aggregation, business cycle fluctuations, and financial stability.

Print Vita
PhD, 2009, Electrical and Systems Engineering, University of Pennsylvania
MA, 2008, Economics, University of Pennsylvania
MSE, 2006, Electrical Engineering, University of Pennsylvania
Bsc, 2004, Electrical Engineering, Sharif University of Technology

Academic Positions
Associate Professor, Managerial Economics & Decision Sciences, Kellogg School of Management, Northwestern University, 2017-present
Daniel W. Stanton Associate Professor of Business, Columbia University, Columbia University, 2015-2017
Associate Professor, Columbia Business School, Columbia University, 2015-2015
Assistant Professor, Columbia Business School, Columbia University, 2011-2015

Honors and Awards
Pew Presidential Prize, Department of Economics, University of Pennsylvania
International Economic Review Fellowship, Department of Economics, University of Pennsylvania, 2007-2008
Judith Rodin Fellowship, School of Arts and Sciences, University of Pennsylvania, 2008-2009
Best Student Paper Award Finalist, IEEE Conference on Decision and Control
Joseph, D'16 and Rosaline Wolf Award for Best Dissertation, Department of Electrical and Systems Engineering, University of Pennsylvania
Outstanding Referee Award, Journal of Economic Dynamics & Control

Print Research
Molavi, Pooya, Alireza Tahbaz-Salehi and Ali Jadbabaie. 2018. A Theory of Non-Bayesian Social Learning. Econometrica. 86(2): 445-490.
Acemoglu, Daron, Asuman Ozdaglar and Alireza Tahbaz-Salehi. 2017. Microeconomic Origins of Macroeconomic Tail Risks. American Economic Review. 107(1): 54-108.
Mueller, Philippe, Alireza Tahbaz-Salehi and Andrea Vedolin. 2017. Exchange Rates and Monetary Policy Uncertainty. Journal of Finance. 72(3): 1213-1252.
Dahleh, Munther, Alireza Tahbaz-Salehi, John Tsitsiklis and Spyros Zoumpoulis. 2016. Coordination with Local Information. Operations Research. 64(3): 622-637.
Acemoglu, Daron, Asuman Ozdaglar and Alireza Tahbaz-Salehi. 2015. Systemic Risk and Stability in Financial Networks. American Economic Review. 105(2): 564-608.
Tahbaz-Salehi, Alireza. 2015. Discussion of "Centrality-Based Capital Allocations". International Journal of Central Banking. 11(3): 379-384.
Acemoglu, Daron, Vasco Carvalho, Asuman Ozdaglar and Alireza Tahbaz-Salehi. 2012. The Network Origins of Aggregate Fluctuations. Econometrica. 80(5): 1977-2016.
Jadbabaie, Ali, Pooya Molavi, Alvaro Sandroni and Alireza Tahbaz-Salehi. 2012. Non-Bayesian Social Learning. Games and Economic Behavior. 76(1): 210-225.
Working Papers
Breza, Emily, Arun Chandrasekhar and Alireza Tahbaz-Salehi. 2018. Seeing Forest for the Trees? An Investigation of Network Knowledge.
Carvalho, Vasco, Makoto Nirei, Yukiko Saito and Alireza Tahbaz-Salehi. 2017. Supply Chain Disruptions: Evidence from the Great East Japan Earthquake.
Di Maggio, Marco and Alireza Tahbaz-Salehi. 2017. Collateral Shortage and Intermediation Networks.
Bimpikis, Kostas and Alireza Tahbaz-Salehi. 2014. Inefficient Diversification and Systemic Bank Runs.
Acemoglu, Daron, Asuman Ozdaglar and Alireza Tahbaz-Salehi. 2014. Systemic Risk in Endogenous Financial Networks.
Book Chapters
Acemoglu, Daron, Asuman Ozdaglar and Alireza Tahbaz-Salehi. 2016. "Networks, Shocks, and Systemic Risk." In The Oxford Handbook of the Economics of Networks, edited by Yann Bramoulle, Andrea Galeotti, Brian Rogers, Chapter 21, 569-607. Oxford University Press.

Print Teaching
Full-Time / Evening & Weekend MBA
Business Analytics I (DECS-430-5)
This course was formerly known as DECS 430-A/DECS 430-B
This course is equivalent to the MMM core course MMM Business Analytics (DECS-440) Analytics is the discovery and communication of meaningful patterns in data. This course will provide students with an analytics toolkit, reinforcing basic probability and statistics while throughout emphasizing the value and pitfalls of reasoning with data. Applications will focus on connections among analytical tools, data, and business decision-making.

Full-Time students are required to complete the Business Analytics Prep Course

Part-Time Students are required to complete the Business Analytics Prep Course