Multiple Equation Analysis: System Estimation & Var Modeling скачать в хорошем качестве

Multiple Equation Analysis: System Estimation & Var Modeling

Welcome to our presentation on Multiple Equation Analysis, focusing on system estimation and Vector Autoregression modeling in EViews. As the EViews User Guide highlights, the structural approach uses economic theory to model the relationships among variables. This allows us to understand how different economic factors interact within a system rather than in isolation. We'll explore the methodologies and practical application using EViews. In the real world, economic variables are deeply interconnected and rarely move in isolation. For example, GDP influences interest rates, but interest rates also influence GDP. A major limitation of standard single-equation O-L-S is its assumption that predictors are exogenous, meaning they are not influenced by the dependent variable. This is often violated in macroeconomics. The solution is system estimation, such as a V-A-R model, which treats all variables as endogenous, acknowledging their mutual influence. In macroeconomics, variables are often both independent and dependent. V-A-Rs, or Vector Autoregressions, sidestep identification problems by treating every endogenous variable as a function of the lagged values of all endogenous variables in the system. This decision matrix provides a clear roadmap for selecting the appropriate time series model when working with multiple time series data. The first critical question to address is whether your data is stationary. As the decision logic highlights, stationarity is essential for the stability of a standard Vector Autoregression, or VAR, model. If your data is indeed stationary,... #eviews #timesseries