مقایسهٔ روش‌ها

	مدل تعادل عمومی قابل محاسبه (CGE)	مدل خودرگرسیون برداری ساختاری (SVAR)	مدل خودرگرسیون برداری (VAR)
حوزه	اقتصادسنجی	اقتصادسنجی	اقتصادسنجی
خانواده	Regression model	Regression model	Regression model
سال پیدایش	2002	1980	2005
پدیدآور	Lofgren, Harris & Robinson (standard IFPRI CGE model in GAMS); Walrasian general equilibrium theory	Sims (1980); identification schemes by Blanchard & Quah (1989)	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
نوع	Numerical general equilibrium model	Multivariate time series model	Multivariate time-series model
منبع بنیادین	Lofgren, H., Harris, R.L. & Robinson, S. (2002). A Standard Computable General Equilibrium (CGE) Model in GAMS. IFPRI Microcomputers in Policy Research, 5.	Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673.	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
نام‌های دیگر	computable general equilibrium, applied general equilibrium model, Hesaplanabilir Genel Denge Modeli (CGE)	SVAR, structural vector autoregression, identified VAR, structural VAR model	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
مرتبط	3	5	4
خلاصه	A Computable General Equilibrium model is a numerical equilibrium framework that represents the input-output relationships among all sectors, factors of production, households, and foreign trade in an economy through a Social Accounting Matrix (SAM). Grounded in Walrasian general equilibrium theory and formalised in the standard IFPRI model of Lofgren, Harris and Robinson (2002), it simulates the economy-wide effects of policy shocks such as tax reform, trade liberalisation, or environmental policy.	Structural VAR extends the reduced-form VAR by imposing economic theory-based restrictions that identify orthogonal structural shocks. This allows researchers to disentangle the causal effects of distinct economic disturbances — such as supply versus demand shocks — and trace their dynamic propagation through a system of variables via impulse response functions and forecast error variance decompositions.	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).