Lag length selection in vector autoregressive models: symmetric and asymmetric lags
This study used Monte Carlo simulations to study the performance of alternative lag selection criterion for symmetric lag and asymmetric lag vector autoregressive models. Lag models with short lags and with long lags were considered. The alternative criteria considered were the AIC, SIC, Phillips' Posterior Information Criterion, and Keating's modification of the AIC and SIC. The alternative criteria were evaluated by computing the frequency distribution of lags selected, by computing the out-of-sample forecasting performance of models with lags selected using each criterion, and by comparing the ability of models with lags selected using each criterion to mimic the 'true' impulse response functions for the lag model.