Journal of Development Economics · 2026 · David Rhys Bernard、Philipp Schoenegger、Ezra Karger、Philipp Schoenegger
中文摘要
随机对照试验（RCT）是因果推断的金标准。然而，决策者在评估影响长期结果的干预措施时，很难依赖随机对照试验。我们收集了505名参与者作出的25,980项预测，以检验人们预测随机对照试验长期结果的能力；参与者事先并不知道这些试验的结果。经验丰富的预测者、学术专家和非专业人士对七项随机对照试验的结果进行了预测，每项试验均测量了至少五年后的长期结果。经验丰富的预测者和学术专家的预测比非专业人士更准确，而经验丰富的预测者又优于学术专家，这至少部分归因于前者更好的校准。汇总预测优于个体预测，显示出明显的群体智慧效应，但经验丰富的预测者和学术专家均未能始终优于简单基准。我们没有发现证据表明，随机向参与者提供有关良好预测实践的额外信息、随机对照试验干预措施的细节或当地研究情境的具体信息，能够提高预测准确性。
Abstract
Randomized controlled trials (RCTs) are the gold standard in causal inference. However, it is difficult for decision-makers to rely on RCTs when evaluating interventions that affect long-run outcomes. We elicit 25,980 forecasts from 505 participants to test the ability of people to predict the long-run outcomes of RCTs whose results were unknown to participants. Experienced forecasters, academic experts, and laypeople predict the outcomes of seven RCTs, each of which measured long-run outcomes at time horizons of at least five years. Experienced forecasters and academics were more accurate than laypeople, and experienced forecasters outperformed academics, at least in part due to their superior calibration. Aggregated forecasts outperform individual forecasts, showing a clear wisdom-of-the-crowd effect, but neither experienced forecasters nor academics consistently outperform simple benchmarks. We see no evidence of improved forecasting accuracy from randomly providing participants with additional information about good forecasting practices, details about the RCT interventions, or specifics about the local study context.