Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics
研究了固定平滑渐近方法在Diebold-Mariano检验中的应用，使小样本下预测精度检验更准确，并发现专业预测者调查的预测能力部分虚假。
Summary We consider fixed‐smoothing asymptotics for the Diebold and Mariano ( Journal of Business and Economic Statistics , 1995, 13 (3), 253–263) test of predictive accuracy. We show that this approach delivers predictive accuracy tests that are correctly sized even when only a small number of out‐of‐sample observations is available. We apply the fixed‐smoothing asymptotics to the Diebold and Mariano test to evaluate the predictive accuracy of the Survey of Professional Forecasters (SPF) and of the European Central Bank Survey of Professional Forecasters (ECB SPF) against a simple random walk. Our results show that the predictive abilities of the SPF and of the ECB SPF were partially spurious.