The importance of being honest

Abstract

This paper analyzes the case of a principal who wants to provide an agent with proper incentives to explore a hypothesis that can be either true or false. The agent can shirk, thus never proving the hypothesis, or he can avail himself of a known technology to produce fake successes. This latter option either makes the provision of incentives for honesty impossible or does not distort its costs at all. In the latter case, the principal will optimally commit to rewarding later successes even though he only cares about the first one. Indeed, after an honest success, the agent is more optimistic about his ability to generate further successes. This, in turn, provides incentives for the agent to be honest before a first success.

Experimentation and project selection: Screening and learning

“…Ederer (2013) extends his framework to a situation where a principal faces multiple agents. Klein (2015) considers a continuous-time version of Manso's two-period model. In his model, the principal either cannot implement the innovative activity at all, or implements it at zero costs by making the exploitative activity sufficiently unappealing to the agent.…”

Optimal Contracts for Experimentation

“…authors are given; Kuzyk (2006) notes that publishing houses try to assess an author's chances of succeeding when determining these terms.…”

Strategic experimentation with asymmetric players

“…Das (2019) analyses an R&D race in a strategic bandit setting in which on the risky arm, players can learn both privately and publicly. Guo (2016) and Zambrano (2017) analyse the problem of a principal delegating the operation of a two-armed bandit to an agent; in Klein (2016), the bandit the agent operates has three arms. Banks et al (1997) provide an experimental test of a single-agent two-armed bandit problem; Hoelzemann and Klein (2018) do so in a strategic setting.…”