On the Wisdom of Crowds (of Economists)
经济学家群体的智慧：预测平均与分散化收益AI 解读 ↓
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AI 根据所提供的论文材料归类：摘要直接分析增长与通胀的调查预测组合及预测表现，属于宏观预测。
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经济学家群体的智慧：预测平均与分散化收益
- 研究问题
- 宏观调查预测取平均时，增加预测者人数能带来多大改进？增长与通胀预测的分散化收益有何差别，等相关误差模型又解释了什么？
- 方法与思路
- 作者构造预测表现随群体规模变化的特征图，结合美国专业预测者调查与等相关误差模型，比较直接计算和模型计算并推导解析表达。
- 材料陈述的贡献
- 摘要称，特定参数下两类特征图可解析地一致；通胀预测的分散化收益大于增长预测，纳入五至十名代表性预测者后收益大体耗尽。
- 阅读关注点
- 应核对特征图的损失指标、预测者组合与代表性的定义、解析一致性所需条件，以及结论对预测期限、样本时期和共同误差的敏感性。
- 阅读边界
- 所给来源为 arXiv 预印本，同行评审或期刊接收未获核实；摘要未说明完整样本与不确定性，拟合优良也不足以证明误差确实等相关。
原文摘要
We study the properties of macroeconomic survey forecast response averages as the number of survey respondents grows. Such averages are ``portfolios" of forecasts. We characterize the speed and pattern of the gains from diversification as a function of portfolio size (the number of survey respondents) in both (1) the key real-world data-based environment of the U.S. Survey of Professional Forecasters, and (2) the theoretical model-based environment of equicorrelated forecast errors. We proceed by proposing and comparing various direct and model-based ``crowd size signature plots", which summarize the forecasting performance of $k$-average forecasts as a function of $k$, where $k$ is the number of forecasts in the average. We then estimate the equicorrelation model for growth and inflation forecast errors by choosing model parameters to minimize the divergence between direct and model-based signature plots. The results indicate near-perfect equicorrelation model fit for both growth and inflation, which we explicate by showing analytically that, under very weak conditions, the direct and fitted equicorrelation model-based signature plots are identical at a particular model parameter configuration. That parameter configuration immediately suggests an analytic closed-form estimator for the direct signature plot, so that equicorrelation ultimately emerges as a device for convenient calculation of direct signature plots, rather than a separate ``model" producing separate signature plots. In any event we find that the gains from survey diversification are greater for inflation forecasts than for growth forecasts, and that they are largely exhausted with inclusion of 5-10 representative forecasters.