Econometrics Toolbox provides functions for modeling economic data. You can select and estimate economic models for simulation and forecasting. For time series modeling and analysis, the toolbox includes univariate Bayesian linear regression, univariate ARIMAX/GARCH composite models with several GARCH variants, multivariate VARX models, and cointegration analysis. It also provides methods for modeling economic systems using state-space models and for estimating using the Kalman filter. You can use a variety of diagnostics for model selection, including hypothesis tests, unit root, stationarity, and structural change. This book develops VAR, VARX, VARMA, VARMAX and VEC time series models. The most important content is the following: - Vector Autoregression (VAR) Models - Types of Multivariate Time Series Models - Lag Operator Representation - Stable and Invertible Models - Building VAR Models - Multivariate Time Series Data Structures - Multivariate Time Series Data - Data Preprocessing - Partitioning Response Data - Multivariate Time Series Model Creation - Models for Multiple Time Series - Creating VAR Models - Create and Adjust VAR Model Using Shorthand Syntax - Create and Adjust VAR Model Using Longhand Syntax - Model Objects with Known Parameters - Model Objects with No Parameter Values - Model Objects with Selected Parameter Values - VAR Model Estimation - Preparing VAR Models for Fitting - Fitting Models to Data - Examining the Stability of a Fitted Model - Convert VARMA Model to VAR Model - Fit VAR Model of CPI and Unemployment Rate - Fit VAR Model to Simulated Data - VAR Model Forecasting, Simulation, and Analysis - VAR Model Forecasting - Data Scaling - Calculating Impulse Responses - Generate Impulse Responses for a VAR model - Compare Generalized and Orthogonalized Impulse Response Functions - Forecast VAR Model - Forecast VAR Model Using Monte Carlo Simulation - Forecast VAR Model Conditional Responses - Multivariate Time Series Models with Regression Terms - Design Matrix Structure for Including Exogenous Data - Estimation of Models that Include Exogenous Data - Implement Seemingly Unrelated Regression Analyses - Implement Seemingly Unrelated Regression - Estimate Capital Asset Pricing Model Using SUR - Simulate Responses of Estimated VARX Model - Simulate VAR Model Conditional Responses - Simulate Responses Using filter - VAR Model Case Study - Cointegration and Error Correction Analysis - Determine Cointegration Rank of VEC Model - Identifying Single Cointegrating Relations - The Engle-Granger Test for Cointegration - Limitations of the Engle-Granger Test - Test for Cointegration Using the Engle-Granger Test - Estimate VEC Model Parameters Using egcitest - Simulate and Forecast a VEC Model - Generate VEC Model Impulse Responses - Identifying Multiple Cointegrating Relations - Test for Cointegration Using the Johansen Test - Estimate VEC Model Parameters Using jcitest - Compare Approaches to Cointegration Analysis - Testing Cointegrating Vectors and Adjustment Speeds - Test Cointegrating Vectors - Test Adjustment Speeds