Econometrics Toolbox™ provides functions for analyzing and modeling time series data. It offers a wide range of visualizations and diagnostics for model selection, including tests for autocorrelation and heteroscedasticity, unit roots and stationarity, cointegration, causality, and structural change. You can estimate, simulate, and forecast economic systems using a variety of modeling frameworks. These frameworks include regression, ARIMA, state-space, GARCH, multivariate VAR and VEC, and switching models. The toolbox also provides Bayesian tools for developing time-varying models that learn from new data.
Learn the basics of Econometrics Toolbox
Format, plot, and transform time series data
Specification testing and model assessment
Bayesian linear regression models and regression models with nonspherical disturbances
Autoregressive (AR), moving average (MA), ARMA, ARIMA, ARIMAX, and seasonal models
GARCH, exponential GARCH (EGARCH), and GJR models
Cointegration analysis, vector autoregression (VAR), vector error-correction (VEC), and Bayesian VAR models
Discrete-time Markov chains, Markov-switching autoregression, and state-space models