Hello everyone,
I am currently working on the replication of an article called "The Impact of Oil Price Shocks on the US Stock Market" (2009) by Kilian and Park. In this paper, the authors used a VAR with 24 lags on monthly data.
I have used the MATLAB function varorder by Ruey S. Tsay to detect the minimizing information criterion AIC (and find the optimal lag length for the VAR model), but it seems that the optimal lag would be around 2,3, not 24! (see picture below). The results are even more striking using BIC or HQ.
AIC Screenshot
Do you know what could justify to that such a long lag?
nb: the paper is investigating impulse response functions and forecast error variance decomposition
I am currently working on the replication of an article called "The Impact of Oil Price Shocks on the US Stock Market" (2009) by Kilian and Park. In this paper, the authors used a VAR with 24 lags on monthly data.
I have used the MATLAB function varorder by Ruey S. Tsay to detect the minimizing information criterion AIC (and find the optimal lag length for the VAR model), but it seems that the optimal lag would be around 2,3, not 24! (see picture below). The results are even more striking using BIC or HQ.
AIC Screenshot
Do you know what could justify to that such a long lag?
nb: the paper is investigating impulse response functions and forecast error variance decomposition