ABSTRACT Bayesian methods are used to compare the predictions of probabilistic risk assessment—the theoretical tool used by the nuclear industry to predict the frequency of nuclear accidents—with empirical data. The existing record of accidents with some simplifying assumptions regarding their probability distribution is sufficient to rule out the validity of the industry’s analyses at a very high confidence level. This conclusion is shown to be robust against any reasonable assumed variation of safety standards over time, and across regions. The debate on nuclear liability indicates that the industry has independently arrived at this conclusion. Paying special attention to the case of India, the article shows that the existing operating experience provides insufficient data to make any reliable claims about the safety of future reactors. Finally, policy implications of the article findings are briefly discussed.

中文翻译：

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估计核事故的频率

摘要 贝叶斯方法用于将概率风险评估（核工业用于预测核事故频率的理论工具）的预测与经验数据进行比较。现有的事故记录及其概率分布的一些简化假设足以排除行业分析在非常高的置信水平下的有效性。事实证明，这一结论对于任何合理假设的安全标准随时间和跨地区的变化都是可靠的。关于核责任的辩论表明，该行业已经独立得出了这一结论。文章特别关注印度的案例，表明现有的运行经验提供的数据不足以对未来反应堆的安全性做出任何可靠的声明。最后，