Model Selection

To begin selecting models for time series data, conduct hypothesis tests for stationarity, autocorrelation, and heteroscedasticity. After estimating the models, compare the fits using, for example, information criteria or a likelihood ratio test. You can also assess whether the models violate any assumptions by analyzing the residuals. For a multiple linear regression model, you can assess whether there is a structural change in the model, or address heteroscedasticity when estimating the regression coefficients.