Examining Selection Pressures in the Publication Process through the Lens of Sniff Tests

• 成果类型: Article
• 署名作者: Snyder, Christopher M.; Zhuo, Ran
• 署名单位: Dartmouth College; National Bureau of Economic Research; University of Michigan System; University of Michigan
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/rest_a_01410
• 发表日期: 2026
• 关键词: credibility; balance; BIAS

摘要

Economics papers increasingly report balance, pretrend, placebo, and other sniff tests, rejection of which is bad news for authors, undermining the credibility of their main results. We derive nonparametric bounds on the latent proportion of significant sniff tests removed by the publication process (whether by p-hacking or relegation to the file drawer) and the proportion whose significance was due to true misspecification, not bad luck. Using a hand-collected sample of nearly 30,000 sniff tests, we estimate a removal rate of more than 30% for balance tests in randomized controlled trials and a misspecification rate of more than 40% for other tests.