方法对比

	Diebold-Mariano Test	模型置信集 (MCS)
领域	计量经济学	计量经济学
方法族	Hypothesis test	Hypothesis test
起源年份	1995	2011
提出者	Francis Diebold & Roberto Mariano	Hansen, Lunde & Nason
类型	Non-parametric forecast comparison test	Sequential hypothesis testing procedure for model comparison
开创性文献	Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263.	Hansen, P. R., Lunde, A., & Nason, J. M. (2011). The model confidence set. Econometrica, 79(2), 453–497.
别名	DM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi	MCS Procedure, Superior Set of Models, Model Selection Confidence Set, Model Güven Kümesi
相关	3	3
摘要	The Diebold-Mariano (DM) test, introduced by Diebold and Mariano in 1995, is a widely used non-parametric procedure for formally comparing the predictive accuracy of two competing forecasting models. It evaluates whether the difference in forecast errors between two models is statistically significant, without requiring nested models or specific distributional assumptions about the forecasts, making it broadly applicable across economics, finance, and time-series analysis.	The Model Confidence Set (MCS) is a sequential hypothesis-testing procedure introduced by Hansen, Lunde, and Nason (2011) that identifies the smallest collection of forecasting or predictive models statistically indistinguishable from the best-performing model at a given confidence level. Instead of selecting a single winner, MCS returns a set of superior models, making it especially valuable in econometric forecast comparisons where the true best model is unknown.