Vector Autoregression Models
Stationary multivariate linear models including exogenous predictor
variables
A vector autoregression (VAR) model is a system of simultaneous linear equations that describes the evolution of multiple stationary response series. Equations in the system are functions of constants, time trends, lagged responses, and exogenous predictor variables. For an example of an analysis using VAR modeling tools, see VAR Model Case Study.
To convert your VAR model analysis code from using
vgx
functions to using the varm
object and its object
functions, see Convert from vgx Functions to Model Objects.
Apps
Econometric Modeler | Analyze and model econometric time series |
Functions
Topics
Interactive
- Analyze Time Series Data Using Econometric Modeler
Interactively visualize and analyze univariate or multivariate time series data. - Specifying Multivariate Lag Operator Polynomials and Coefficient Constraints Interactively
Specify multivariate lag operator polynomial terms for time series model estimation using Econometric Modeler. - Estimate Vector Autoregression Model Using Econometric Modeler
Interactively fit several multivariate vector autoregression (VAR) models to data. Then, select an estimated model and export it to the command line for further analysis.
Create Model
- Create and Adjust VAR Model Using Shorthand Syntax
This example shows how to create a three-dimensional VAR(4) model with unknown parameters usingvarm
and the shorthand syntax. - Create and Adjust VAR Model Using Longhand Syntax
This example shows how to create a three-dimensional VAR(4) model with unknown parameters usingvarm
and the longhand syntax. - Vector Autoregression (VAR) Model Creation
Represent a vector autoregression (VAR) model using avarm
object. - Vector Autoregression (VAR) Models
A vector autoregression (VAR) model is a multivariate time series model containing a system of n equations of n distinct, stationary response variables as linear functions of lagged responses and other terms. - Convert from vgx Functions to Model Objects
Convert common tasks that use thevgx
functions to the newer functionality.
Fit Model to Data
- Format Multivariate Time Series Data
Prepare your data for a multivariate time series analysis. - VAR Model Estimation Overview
Decide on a set of VAR candidates to models, fit each model to the data, choose the model with the best fit, and then determine whether the AR polynomial of the estimated model is stable. - Fit VAR Model to Simulated Data
Simulate data from a known VAR model, then fit a VAR model to the simulated data. - Fit VAR Model of CPI and Unemployment Rate
Estimate a VAR model composed of the consumer price index and unemployment rate. - Implement Seemingly Unrelated Regression
Include exogenous predictors in a VAR model to estimate a regression component along with all other parameters. - Estimate Capital Asset Pricing Model Using SUR
Implement the capital asset pricing model (CAPM) using the Econometrics Toolbox™ VAR model framework. - VAR Model Case Study
Analyze a VAR model.
Impulse Response Functions and Granger Causality
- Generate VAR Model Impulse Responses
Generate impulse responses of an interest rate shock on real GDP. - Compare Generalized and Orthogonalized Impulse Response Functions
Demonstrate differences between orthogonal and generalized impulse response functions.
Convert Between Models
- Convert VARMA Model to VAR Model
Create a VARMA model, and then convert it to a pure VAR model.
Generate Simulations or Impulse Responses
- VAR Model Forecasting, Simulation, and Analysis
Use models to extrapolate the behavior of time series. - Simulate VAR Model Conditional Responses
Forecast CPI growth rates given known values of the unemployment rate using Monte Carlo simulation. - Simulate Responses Using filter
Reproduce the results ofsimulate
usingfilter
. - Simulate Responses of Estimated VARX Model
Estimate a multivariate time series model that contains lagged endogenous and exogenous variables and simulate responses. - Forecast VAR Model Using Monte Carlo Simulation
Generate forecasts from a VAR model using Monte Carlo simulation.
Generate Minimum Mean Square Error Forecasts
- Forecast VAR Model
Generate forecasts with error estimates. - Forecast VAR Model Using Monte Carlo Simulation
Generate forecasts from a VAR model using Monte Carlo simulation. - Forecast VAR Model Conditional Responses
Forecast responses given contemporaneous information about other response values in the forecast horizon. - Incorporate Macroeconomic Scenario Projections in Loan Portfolio ECL Calculations
Generate macroeconomic scenarios and perform expected credit loss (ECL) calculations for a portfolio of loans.