Effort without Evidence

Abstract

Advice can determine not only how past evidence is interpreted but whether new evidence will be produced. I study a sequence of decision makers who observe public success or failure but not one another's effort, and who pass costless causal assessments to their successors. Because a sender values success while underweighting her successor's effort cost, she has a reason to recommend more demanding actions. This motive can make encouragement uninformative. After an ambiguous failure, every equilibrium may induce inactivity, so experimentation and learning stop. When maximal effort makes outcomes insensitive to the underlying technology, the same force produces the opposite-looking trap: everyone works hard, but nobody tests whether less would suffice. Collapse is monotone in motivational bias, whereas moderate motivation preserves causal disagreement and the identifying experiment. In the threshold application, stronger motivation raises observed success while reducing long-run welfare. Motivation therefore selects costly actions, not informative experiments: a society may stop learning either because nobody tries or because everyone tries too hard.