I read so many answers in here that I should use IC(information criteria) to determine the optimal lag length in VAR/VECM.
But also it is important to check the residual of VAR/VECM has no-autocorrelation and no-heteroskedasticity.
I use trial and error to find the optimal lag length that makes residual stationary.
So IC is useless to me in some ways.
I wonder I'm doing wrong or not.
I need your advice.
Model Selection – Optimal Lag Length in VAR/VECM: Information Criterion vs Residual Test
aicdiagnosticmodel selectionvector-autoregressionvector-error-correction-model
Best Answer
The choice depends on what you want to do with the model. Different goals justify different selection criteria. Ignoring IC and going for well-behaved residuals may work fine for inference from the model. At the same time, this may be a poor way of finding a model that does well in forecasting (as it will likely be overfitted) or identifying the true data generating process if it happens to be among the candidate models (though this is hardly realistic in practice), and this is where ICs could come in handy.