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Asa Palley
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812-855-3654
apalley@indiana.edu
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HH4100
1309 E. 10th Street
Bloomington, IN
47405

Asa Palley

  • Assistant Professor
Department: Operations & Decision Technologies
Campus: Bloomington


Areas of Expertise

Decision Analysis; Wisdom of Crowds; Judgment and Decision Making; Forecasting

Academic Degrees

  • PhD, Duke University, 2016
  • MS, Carnegie Mellon University, 2010
  • MS, University of Maryland, College Park, 2009
  • AB, Bowdoin College, 2007

Professional Experience

  • Assistant Professor, Indiana University, Kelley School of Business, 2016 – present
  • Instructor, Duke University, Master of Engineering Management Program, 2014

Selected Publications

  • Palley, A.B., and Satopää, V. (2023). Boosting the Wisdom of Crowds Within a Single Judgment Problem: Weighted Averaging Based on Peer Predictions. Management Science, 69(9), 5128–5146. View Full Text
  • Palley, A.B., Steffen, T.D., Zhang, X.F. (2023). The Effect of Dispersion on the Informativeness of Consensus Analyst Target Prices. Management Science, accepted. View Full Text
  • Soll, J.B., Palley, A.B., Klayman, J., Moore, D.A. (2023). Overconfidence in Probability Distributions: People Know They Don’t Know but They Don’t Know What to Do About It. Management Science, in press. View Full Text
  • Soll, J.B., Palley, A.B., and Rader, C.A. (2022). The Bad Thing About Good Advice: Understanding When and How Advice Exacerbates Overconfidence. Management Science, 68(4), 2949–2969. View Full Text
  • Palley, A.B., and Soll, J.B. (2019). Extracting the Wisdom of Crowds When Information is Shared. Management Science, 65(5), 1949-2443. View Full Text

    Abstract

    Using the wisdom of crowds -- combining many individual judgments to obtain an aggregate estimate -- can be an effective technique for improving judgment accuracy. In practice, however, accuracy is limited by the presence of correlated judgment errors, which often emerge because information is shared. To address this problem, Asa and his colleague propose an aggregation procedure called pivoting that adjusts a crowd's average judgment away from the average estimate of the judgment that all other respondents will provide on average. Data from four studies suggests that pivoting can significantly outperform classical averaging procedures.

  • Offerman, T., and Palley, A.B. (2016). Lossed in Translation: An Off-the-Shelf Method to Recover Probabilistic Beliefs from Loss-Averse Agents. Experimental Economics, 19(1), 1–30. View Full Text
  • Palley, A.B., and Kremer, M. (2014). Sequential Search and Learning from Rank Feedback: Theory and Experimental Evidence. Management Science, 60(10), 2525-2542. View Full Text
  • Keeney, R.L., and Palley, A.B. (2013). Decision Strategies to Reduce Teenage and Young Adult Deaths in the United States. Risk Analysis, 33(9), 1661-1676. View Full Text

Edited on January 28, 2022

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