• Graduate Program
  • Research
  • Browse our Courses
  • Events
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • Summer School
      • Deep Learning
      • Economics of Blockchain and Digital Currencies
      • Foundations of Machine Learning with Applications in Python
      • Marketing Research with Purpose
      • Modern Toolbox for Spatial and Functional Data
      • Sustainable Finance
      • Tuition Fees and Payment
      • Tinbergen Institute Summer School Program
    • Annual Tinbergen Institute Conference archive
  • News
  • Summer School
    • Deep Learning
    • Economics of Blockchain and Digital Currencies
    • Foundations of Machine Learning with Applications in Python
    • Marketing Research with Purpose
    • Modern Toolbox for Spatial and Functional Data
    • Sustainable Finance
  • Alumni

Aydogan, I., Baillon, A., Kemel, E. and Li, C. (2025). How much do we learn?: Measuring symmetric and asymmetric deviations from Bayesian updating through choices Quantitative Economics, 16(1):329--365.


  • Affiliated author
  • Publication year
    2025
  • Journal
    Quantitative Economics

Belief-updating biases hinder the correction of inaccurate beliefs and lead to suboptimal decisions. We complement Rabin and Schrag's (1999) portable extension of the Bayesian model by including conservatism in addition to confirmatory bias. Additionally, we show how to identify these two forms of biases from choices. In an experiment, we found that the subjects exhibited confirmatory bias by misreading 19% of the signals that contradicted their priors. They were also conservative and acted as if they missed 28% of the signals.