Econometrics Toolbox
Description
- Introduction and Key Features
- Time-Series Modeling
- Model Identification and Analysis
- Parameter Estimation
- Monte Carlo Simulation
- Forecasting
- Cointegration Modeling
- Volatility Modeling
Introduction
Econometrics Toolbox™ provides functions for modeling economic data. You can select and calibrate economic models for simulation and forecasting. Time series capabilities include univariate ARMAX/GARCH composite models with several GARCH variants, multivariate VARMAX models, and cointegration analysis. The toolbox provides Monte Carlo methods for simulating systems of linear and nonlinear stochastic differential equations and a variety of diagnostics for model selection, including hypothesis, unit root, and stationarity tests.
Key Features
- Univariate ARMAX/GARCH composite models, including EGARCH, GJR, and other variants
- Multivariate simulation and forecasting of VAR, VEC, and cointegrated models
- Monte Carlo simulation of stochastic differential equations (SDEs), including Brownian motion, CEV, CIR, Hull-White, Vasicek, Heston stochastic volatility, and user-defined SDEs
- Tests for unit root (Dickey-Fuller, Phillips-Perron) and stationarity (Leybourne-McCabe, KPSS)
- Statistical tests, including likelihood ratio, LM, Wald, Engle's ARCH, and Ljung-Box Q
- Cointegration tests, including Engle-Granger and Johansen
- Diagnostics and utilities, including AIC/BIC model selection and partial-, auto-, and cross-correlations
- Hodrick-Prescott filter for business-cycle analysis
