来源：《经济学人》
原文刊登日期：2021年4月22日
Economists like to crunch numbers and build models to guide policymakers. But who guides them in turn? Isaiah Andrews of Harvard University has been trying to help. On April 20th the American Economic Association awarded him the John Bates Clark Medal, a prize for leading economists under the age of 40, for his efforts.
经济学家喜欢倒腾数据，建立模型来指导政策制定者。但反过来又是谁在引导他们呢？哈佛大学的以赛亚•安德鲁斯一直试图提供帮助。4月20日，美国经济协会授予他约翰·贝茨·克拉克奖章，这是一个奖励40岁以下杰出经济学家的奖项，以表彰他的努力。
Mr Andrews did not expect to become an econometrician (an economist who specialises in statistics). But during graduate study he was drawn towards questions about the lessons and limits of data. With Matthew Gentzkow of Stanford University and Jesse Shapiro of Brown University, he suggested a way to assess the quality of economists’ models. He also showed economists how to work out how much their findings might change under alternative assumptions, helping them fend off accusations that their results were a feature of their assumptions rather than the data.
安德鲁斯并没有想到自己会成为一名计量经济学家(专攻统计学的经济学家)。但在研究生学习期间，他被有关数据的教训和局限性的问题所吸引。他与斯坦福大学的马修•根茨科和布朗大学的杰西•夏皮罗一起提出了一种评估经济学家模型质量的方法。他还向经济学家展示了如何计算出在不同假设下，他们的发现可能会有多大的变化，帮助他们避免被指责他们的结果是假设的特征，而不是数据的特征。
In work with Maximilian Kasy, now of Oxford University, Mr Andrews cast light on the fact that economists are too eager to pursue striking results, and journal editors too prone to approve them. Studies that find that minimum wages have no significant effect on employment, for example, are only a third as likely to be published as those finding a stronger negative effect. The researchers developed a way to adjust reported results for this publication bias—and found that the average effect of a higher minimum wage on employment fell by half.
在与牛津大学的马克西米利安•卡西的合作中，安德鲁斯揭示了这样一个事实：经济学家太急于追求惊人的结果，而期刊编辑也过于倾向于认可这些结果。例如，发现最低工资对就业没有显著影响的研究，其发表的可能性仅为发现更强烈负面影响的研究的三分之一。两位研究人员开发了一种方法来调整发表结果中的偏差，并发现较高的最低工资对就业的平均影响下降了一半。
Mr Andrews, with others, also explored what is called the winner’s curse when it comes to choosing between policies: the policy that performs best in a trial may owe its top rank to chance, and will later be doomed to disappoint. To illustrate this the researchers turn to a trial that assesses the most effective ways of encouraging people to donate to charity. The researchers find that if the charity chooses the method that does best in a trial, it will always overestimate its donations. They suggest ways to make a more realistic estimate that takes account of the role of chance.
安德鲁斯和其他人也探讨了在政策选择上所谓的赢家诅咒：在试验中表现最好的政策可能由于偶然性而名列前茅，而以后注定会令人失望。为了说明这一点，研究人员进行了一项试验，评估鼓励人们捐款的最有效方式。安德鲁斯等研究人员发现，如果慈善机构选择了在试验中效果最好的方法，它总是会高估捐款数额。他们提出了一些方法，可以考虑到偶然性的作用，从而做出更现实的估计。
All told, the prize-giving committee concluded, Mr Andrews had helped turn econometrics “back towards the study of the most important problems faced in empirical research”.
颁奖委员会总结道，总而言之，安德鲁斯帮助计量经济学“重新转向实证研究中面临的最重要问题的研究”。