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灾难、延迟与学习

Catastrophes, Delays, and Learning
Review of Economic Studies · 2026 · Matti Liski、François Salanié

中文摘要

我们提出了一个简单而一般的实验模型:在该模型中,达到某个存量变量此前未经尝试的水平,可能在经历一段随机延迟后引发灾难。因此,在任一时点,由于过去的实验,一场灾难很可能已经在酝酿之中。我们说明如何根据先验信念与存量水平的历史记录来衡量这种由过去遗留下来的影响。我们将最优政策刻画为该遗留影响的函数,并表明它导出了一种新的规划规程,可适用于一类一般性问题,涵盖对疫情或气候变化的研究。由此得出若干具有原创性的政策预测,例如,实验可以中止,但随后又可重新启动。

Abstract

Abstract We propose a simple and general model of experimentation in which reaching untried levels of a stock variable may, after a stochastic delay, lead to a catastrophe. Hence, at any point in time a catastrophe might well be under way, due to past experiments. We show how to measure this legacy of the past from prior beliefs and the chronicle of stock levels. We characterize the optimal policy as a function of the legacy and show that it leads to a new protocol for planning that applies to a general class of problems, encompassing the study of pandemics or climate change. Several original policy predictions follow, e.g. experimentation can stop but resume later.
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