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Reversals of signal-posterior monotonicity imply a bias of screening

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  • Sander Heinsalu

Abstract

This note strengthens the main result of Lagziel and Lehrer (2019) (LL) "A bias in screening" using Chambers Healy (2011) (CH) "Reversals of signal-posterior monotonicity for any bounded prior". LL show that the conditional expectation of an unobserved variable of interest, given that a noisy signal of it exceeds a cutoff, may decrease in the cutoff. CH prove that the distribution of a variable conditional on a lower signal may first order stochastically dominate the distribution conditional on a higher signal. The nonmonotonicity result is also extended to the empirically relevant exponential and Pareto distributions, and to a wide range of signals.

Suggested Citation

  • Sander Heinsalu, 2019. "Reversals of signal-posterior monotonicity imply a bias of screening," Papers 1910.03117, arXiv.org, revised Nov 2019.
    • Handle: RePEc:arx:papers:1910.03117
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    1. Andreas Fagereng & Martin Blomhoff Holm & Benjamin Moll & Gisle Natvik, 2019. "Saving Behavior Across the Wealth Distribution: The Importance of Capital Gains," NBER Working Papers 26588, National Bureau of Economic Research, Inc.
    2. Annette Alstadsæter & Niels Johannesen & Gabriel Zucman, 2019. "Tax Evasion and Inequality," American Economic Review, American Economic Association, vol. 109(6), pages 2073-2103, June.
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    4. Niels Johannesen & Patrick Langetieg & Daniel Reck & Max Risch & Joel Slemrod, 2020. "Taxing Hidden Wealth: The Consequences of US Enforcement Initiatives on Evasive Foreign Accounts," American Economic Journal: Economic Policy, American Economic Association, vol. 12(3), pages 312-346, August.
    5. Chambers, Christopher P. & Healy, Paul J., 2011. "Reversals of signal-posterior monotonicity for any bounded prior," Mathematical Social Sciences, Elsevier, vol. 61(3), pages 178-180, May.
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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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