标题： “后”预先分析计划：非预注册规范的有效推断 显示英文标题

标题： "Post" Pre-Analysis Plans: Valid Inference for Non-Preregistered Specifications

摘要： 先验分析计划（PAPs）在实验经济学研究中已成为标准，但研究人员仍然常见地偏离他们的PAP，以补充预先注册的估计值与非预先指定的发现。 虽然这种事后分析可以产生有价值的见解，但对于如何解释——或者甚至是否承认——非预先注册的结果存在广泛的不确定性。 在本文中，我们考虑了一位追求真理的研究者的情况，该研究者在看到数据后，真诚地希望在其PAP中预先注册的估计值之外报告额外的估计值。 我们表明，即使没有“恶意”行为，传统的置信区间和点估计器也是无效的，因为非预先注册的估计值仅在部分潜在的数据实现中被报告。 我们提出了考虑到这种条件性报告的推断程序。 我们将这些程序应用于Bessone等人（2021年），该研究探讨了城市贫困人口增加睡眠的经济影响。 我们证明，根据偏离的原因不同，我们程序的调整可能从没有差异到相对于传统做法具有经济上显著的差异。 最后，我们考虑了我们的程序对某些形式的误设定的稳健性，从而促使期刊可能采用一些启发式检查和规范。 显示英文摘要

摘要： Pre-analysis plans (PAPs) have become standard in experimental economics research, but it is nevertheless common to see researchers deviating from their PAPs to supplement preregistered estimates with non-prespecified findings. While such ex-post analysis can yield valuable insights, there is broad uncertainty over how to interpret -- or whether to even acknowledge -- non-preregistered results. In this paper, we consider the case of a truth-seeking researcher who, after seeing the data, earnestly wishes to report additional estimates alongside those preregistered in their PAP. We show that, even absent "nefarious" behavior, conventional confidence intervals and point estimators are invalid due to the fact that non-preregistered estimates are only reported in a subset of potential data realizations. We propose inference procedures that account for this conditional reporting. We apply these procedures to Bessone et al. (2021), which studies the economic effects of increased sleep among the urban poor. We demonstrate that, depending on the reason for deviating, the adjustments from our procedures can range from having no difference to an economically significant difference relative to conventional practice. Finally, we consider the robustness of our procedure to certain forms of misspecification, motivating possible heuristic checks and norms for journals to adopt.