Vector Error-Correction Models
Vector-error correction (VEC) models, or cointegrated VAR models, address nonstationarity in multivariate time series resulting from co-movements of multiple response series. For an example of an analysis using VEC modeling tools, see Modeling the United States Economy.
Fit Model to Data
Convert Between Models
Generate Simulations or Impulse Responses
Generate Minimum Mean Square Error Forecasts
This example illustrates the use of a vector error-correction (VEC) model as a linear alternative to the Smets-Wouters Dynamic Stochastic General Equilibrium (DSGE) macroeconomic model, and applies many of the techniques of Smets-Wouters to the description of the United States economy.
Generate impulse responses from a VEC model.
Generate Monte Carlo and MMSE forecasts from a VEC model.