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When to Request Evidence?

Andres Espitia, Edwin Muñoz-Rodríguez

TL;DR

This paper analyzes how a principal should schedule verifiable information requests when information is obtained through an agent with biased incentives, in a deterministic two-period mechanism without transfers. It shows that baseline, payoff-relevant policies can invite strategic testing and selective disclosure, and that optimal mechanisms must be history-dependent, conditioning both testing and assignment decisions on prior reports to curb manipulation. The authors characterize incentive-compatible mechanisms and identify regimes where either a history-dependent RD1 approach or a baseline-like policy is optimal, with extensions to a continuum of agents. The findings offer guidance for designing information-update schedules in settings like organ allocation and other domains with exogenous timing and verifiable information.

Abstract

Appropriate decisions depend on information gathered beforehand, yet such information is often obtained through intermediaries with biased preferences. Motivated by settings such as testing and recertification in organ transplantation, we study the problem faced by a decision-maker who can only access costly information through an agent with misaligned preferences. In a dynamic framework with exogenous decision timing, we ask how requests for verifiable information (evidence) should be scheduled and their implications for the quality of attained choices. When the agent's incentives are ignored, evidence requests do not condition on previously reported information. However, such policies may be susceptible to strategic manipulation by the agent. We show that, in these cases, optimal requests should be biased: additional evidence is more likely to be sought when previous reports favor the agent's preferred outcome.

When to Request Evidence?

TL;DR

This paper analyzes how a principal should schedule verifiable information requests when information is obtained through an agent with biased incentives, in a deterministic two-period mechanism without transfers. It shows that baseline, payoff-relevant policies can invite strategic testing and selective disclosure, and that optimal mechanisms must be history-dependent, conditioning both testing and assignment decisions on prior reports to curb manipulation. The authors characterize incentive-compatible mechanisms and identify regimes where either a history-dependent RD1 approach or a baseline-like policy is optimal, with extensions to a continuum of agents. The findings offer guidance for designing information-update schedules in settings like organ allocation and other domains with exogenous timing and verifiable information.

Abstract

Appropriate decisions depend on information gathered beforehand, yet such information is often obtained through intermediaries with biased preferences. Motivated by settings such as testing and recertification in organ transplantation, we study the problem faced by a decision-maker who can only access costly information through an agent with misaligned preferences. In a dynamic framework with exogenous decision timing, we ask how requests for verifiable information (evidence) should be scheduled and their implications for the quality of attained choices. When the agent's incentives are ignored, evidence requests do not condition on previously reported information. However, such policies may be susceptible to strategic manipulation by the agent. We show that, in these cases, optimal requests should be biased: additional evidence is more likely to be sought when previous reports favor the agent's preferred outcome.
Paper Structure (28 sections, 18 theorems, 48 equations)

This paper contains 28 sections, 18 theorems, 48 equations.

Table of Contents

  1. Introduction
  2. Related literature
  3. Motivating facts
  4. Model
  5. Preliminaries
  6. Information acquisition and transmission
  7. Timing
  8. Ex-post payoffs
  9. Mechanisms
  10. Baseline mechanism
  11. Punishments
  12. Agent's behavior under the baseline mechanism
  13. Improvements over the baseline mechanism
  14. Optimal mechanisms
  15. Incentive compatibility
  16. ...and 13 more sections

Key Result

Proposition 1

The baseline mechanism pairs the efficient assignments $\hat{x}^*$ with the following testing policy: $\sigma_1^*=0$ and Moreover, if $\kappa= 0$, then always testing is optimal.

Theorems & Definitions (44)

  • Definition 1: Efficient assignments
  • Proposition 1: Baseline mechanism
  • Lemma 1
  • Definition 2: Deviation strategy
  • Proposition 2: Profitable deviation from baseline
  • Lemma 2: Inducing full disclosure under efficient assignments
  • Lemma 3: Minimum cost of full disclosure under efficient assignments
  • Definition 3: Incentive compatible mechanisms
  • Proposition 3
  • Example 1
  • ...and 34 more