So sánh phương pháp

	Hồi quy Lượng-trên-Lượng Bayes	Mô hình Hiệu chỉnh Sai số Tích chập Bayes (Bayesian VECM)
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	2015–2019	2002–2005
Người khởi xướng	Bayesian QQ framework combines Sim & Zhou (2015) QQ regression with Bayesian quantile regression (Yu & Moyeed, 2001)	Kleibergen & Paap; Villani
Loại	Nonparametric quantile regression with Bayesian estimation	Bayesian multivariate time series model
Công trình gốc	Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1–8.	Kleibergen, F., & Paap, R. (2002). Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration. Journal of Econometrics, 111(2), 223–249.
Tên gọi khác	Bayesian QQR, Bayesian QQ regression, Bayes quantile-on-quantile, BQQ regression	Bayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correction
Liên quan	6	5
Tóm tắt	Bayesian Quantile-on-Quantile (BQQ) Regression extends the Sim-Zhou quantile-on-quantile framework by replacing frequentist local linear estimation with Bayesian posterior inference. For each pair of quantiles (theta of the outcome, tau of the predictor), the method yields a full posterior distribution over the slope, enabling uncertainty quantification across the entire bivariate quantile surface — a key advantage when sample sizes are moderate and tail quantiles are sparse.	The Bayesian VECM combines the classical Vector Error Correction Model — which captures both short-run dynamics and long-run cointegrating relationships among non-stationary multivariate time series — with Bayesian prior distributions over the cointegrating rank and coefficient matrices. This allows principled uncertainty quantification, incorporation of economic theory as priors, and coherent inference even in small samples.