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Vector Error-Correction Models

Multivariate linear models including cointegrating relations and exogenous predictor variables

Vector-error correction (VEC) models, or cointegrated VAR models, address nonstationarity in multivariate times 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.


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vecmCreate vector error-correction (VEC) model
estimateFit vector error-correction (VEC) model to data
inferInfer vector error-correction (VEC) model innovations
summarizeDisplay estimation results of vector error-correction (VEC) model
arma2arConvert ARMA model to AR model
arma2maConvert ARMA model to MA model
vec2varConvert VEC model to VAR model
var2vecConvert VAR model to VEC model
varmConvert vector error-correction (VEC) model to vector autoregression (VAR) model
simulateMonte Carlo simulation of vector error-correction (VEC) model
filterFilter disturbances through vector error-correction (VEC) model
irfGenerate vector error-correction (VEC) model impulse responses
fevdGenerate vector error-correction (VEC) model forecast error variance decomposition (FEVD)
forecastForecast vector error-correction (VEC) model responses


Modeling the United States Economy

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 VEC Model Impulse Responses

Generate impulse responses from a VEC model.

VEC Model Monte Carlo Forecasts

Generate Monte Carlo and MMSE forecasts from a VEC model.