Information Spillovers Among Resource Extractors∗

Whilst the study of resource extraction under uncertainty has a long history in resource economics, there has been less attention paid to endogenous efforts to reduce uncertainty through learning and information acquisition. An unresolved empirical question is the degree to which individual extractors learn from the behavior of other extractors. The question is difficult to resolve because there is always the possibility that an unobserved influence on an individual extractor happens to be correlated with the behavior of other extractors. The difficulty is further compounded by the fact that an unobserved influence on one individual indirectly affects everyone who is influenced by that individual. We propose an identification strategy to overcome this concern by isolating individuals who have strong incentives to pay attention to their peer group but who do not themselves influence their peer group. The approach is particularly well-suited to natural resources that experience a gold rush of new entrants. Fueled by a booming Japanese economy, the northern California sea urchin fishery experienced a surge of new entrants in the late 1980s and early 1990s. We use these new entrants to cleanly identify strong information spillovers.