So sánh phương pháp

	Hồi quy Lượng-trên-Lượng Bayes	Mô hình ARDL phi tuyến (NARDL)
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	2015–2019	2014
Người khởi xướng	Bayesian QQ framework combines Sim & Zhou (2015) QQ regression with Bayesian quantile regression (Yu & Moyeed, 2001)	Shin, Yu & Greenwood-Nimmo
Loại	Nonparametric quantile regression with Bayesian estimation	Nonlinear cointegration 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.	Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281–314). Springer.
Tên gọi khác	Bayesian QQR, Bayesian QQ regression, Bayes quantile-on-quantile, BQQ regression	NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model
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 Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically.