Research

We provide systematic evidence on the economic damages from espionage to US firms and industries. Compiling a comprehensive dataset of publicly disclosed espionage incidents from 1995-2024, we establish that espionage has substantial negative effects on targeted firms. In an event-study design, revenues and R&D expenditures at targeted firms decline by roughly 40% within five years, with effects persisting for up to a decade. These effects do not appear for firms unsuccessfully targeted for espionage, supporting a causal interpretation. These firm-level damages translate into measurable aggregate effects on US industry: exports in targeted sectors decline by 40% over a decade. Given these substantial damages, we investigate whether firms restrict knowledge sharing in response to espionage. Across a wide range of outcomes, we find little evidence of such restrictions. Firms do not reduce their patenting with foreign inventors, do not discriminate in employment based on perceived espionage risk, do not change the geography of their business, and do not discuss how they adapt to espionage incidents. Overall, espionage has clear economic harms to targeted firms and US industry, but firms are puzzlingly unresponsive in how they manage innovation.

Statistical methods typically lack power to detect p-hacking and publication bias among individual researchers, making it difficult to detect how prevalent p-hacking is. We propose a novel empirical Bayes method to estimate researcher-level p-hacking prevalence. Using data from top medical journals, we find strong evidence these practices are widespread: at least 85% of researchers over-reject null hypotheses, with a conservative lower bound of 73%. Our approach identifies 20% of researchers as over-rejecting, whereas conventional tests detect none. These findings demonstrate that p-hacking and publication bias are systemic rather than isolated misconduct, underscoring the need for structural reforms in scientific practice.