Problem
Research questions and friction points this paper is trying to address.
noisy signaling
screening accuracy
precision paradox
statistical discrimination
strategic signaling
Pitfall of Precision in Noisy Signaling
🤖 AI Summary
This study investigates the counterintuitive phenomenon wherein enhancing signal precision in noisy screening environments can paradoxically degrade screening efficacy and reduce decision-maker welfare. By developing a principal-agent model grounded in game theory, mechanism design, and information economics, the paper uncovers a “precision trap”: highly precise signals incentivize low-quality agents to strategically mimic high-quality types, thereby distorting selection outcomes. The analysis further reveals that heterogeneity in noise levels can reverse statistical discrimination patterns. The findings demonstrate that an excessive pursuit of signal accuracy may be counterproductive and propose a commitment mechanism as an effective remedy. This work offers novel insights into the trade-off between efficiency and fairness in information-constrained screening settings.
📝 Abstract
A principal decides whether to approve an agent based on a noisy signal (e.g., test scores) generated by the agent. High-quality agents can produce high signals on average at lower cost, but the realizations are subject to noise that depends on the screening technology's precision. We uncover a paradoxical "pitfall of precision": when precision is already high, further improvements reduce screening accuracy and lower the principal's welfare. This occurs because greater precision incentivizes strategic signaling from more low-quality agents, outweighing the direct benefit from improved precision. The pitfall of precision also has implications for statistical discrimination: groups with noisier technologies face lower approval rates yet may be favored ex ante -- a reversal of discrimination. We also examine how commitment power helps mitigate the pitfall.
Innovation
Methods, ideas, or system contributions that make the work stand out.
precision trap
noisy signaling
strategic behavior
statistical discrimination
screening accuracy
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