เปรียบเทียบวิธี

	การทดสอบสหการ (Johansen / Engle-Granger)	การถดถอยกำลังสองน้อยที่สุดสามัญ (OLS)	แบบจำลอง Vector Autoregression (VAR)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model	Regression model
ปีกำเนิด	1988	2019	2005
ผู้ริเริ่ม	Engle & Granger (1987); Johansen (1988)	Wooldridge (textbook treatment); classical least squares	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
ประเภท	Time-series cointegration test	Linear regression	Multivariate time-series model
แหล่งต้นตำรับ	Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
ชื่อเรียกอื่น	Johansen cointegration test, Engle-Granger cointegration test, long-run equilibrium test, Eşbütünleşme Testi (Johansen/Engle-Granger)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
ที่เกี่ยวข้อง	5	5	4
สรุป	The cointegration test examines whether non-stationary time series that each contain a unit root share a stable long-run equilibrium relationship. The single-equation residual approach was introduced by Engle and Granger (1987) and the system-based rank approach by Johansen (1988).	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).	Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).