Test Design Under Falsification

Working Paper: CEPR ID: DP15627

Authors: Vasiliki Skreta; Eduardo Perez-Richet

Abstract: We study the optimal design of tests with manipulable inputs: data, actions, reports. An agent can, at a cost, falsify the input into the test, or state of the world, so as to influence the downstream binary decision of a receiver informed by the test. We characterize receiver-optimal tests under different constraints. Under covert falsification, the receiver-optimal test is inefficient. With a rich state space, it involves equilibrium falsification at a possibly large cost to the agent, and may therefore exert a negative social externality. The receiver-optimal test that is immune to falsification, while also inefficient, strictly improves the payoff of the agent. When the falsification strategy of the agent is observable, or can be committed to, the receiver-optimal test is efficient, uses a rich signal space, and gives the receiver at least half of his full information payoff.

Keywords: information design; falsification; tests; manipulation; cheating; bayesian persuasion

JEL Codes: C72; D82


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
costs of falsification (M48)receiver's decision-making process (D79)
receiver's decision-making process (D79)efficiency of the tests (C52)
covert falsification (Y50)receiver-optimal test is inefficient (H21)
receiver-optimal test is inefficient (H21)negative social externalities (D62)
receiver-optimal test immune to falsification (C52)agent's payoff improves (C73)

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