Econometrics Toolbox

Model Identification and Analysis

With Econometrics Toolbox, you can select and test models by specifying a model structure, identifying the model order, estimating parameters, and evaluating residuals. A variety of pre- and post-estimation diagnostics and tests support these analyses, including:

  • Likelihood ratio, Wald, and Lagrange multiplier tests for model specification
  • Akaike and Bayesian information criteria for model order selection
  • Engle’s test for the presence of ARCH/GARCH effects
  • Sample autocorrelation, cross-correlation, and partial autocorrelation functions
  • Ljung-Box Q (portmanteau) test for autocorrelation
  • Dickey-Fuller and Phillips-Perron unit root tests
  • KPSS and Leybourne-McCabe stationarity tests
  • Engle-Granger and Johansen tests for cointegration
  • Variance ratio test for random walks
Testing of NASDAQ Composite Index price series and returns for autocorrelation and partial autocorrelation.

Testing of NASDAQ Composite Index price series and returns (left) for autocorrelation and partial autocorrelation. The raw return series does not have any correlation (top right), and correlation is present in the squared return (bottom right).

Next: State-Space Modeling and Parameter Estimation

Try Econometrics Toolbox

Get trial software

Multilevel Mixed-Effects Modeling Using MATLAB

View webinar