Explosive Threshold VAR
Posted: Sat Apr 16, 2011 12:23 pm
Hello,
I am somewhat new to estimating threshold VARs but I am having a strange problem. Any insight or suggestion is appreciated. I have a simple 4 variable VAR (ordered: log difference of real GDP, log difference CPI, fed funds rate, credit market variable) all data is monthly from 1980:01 to 2011:01. I am estimating a threshold VAR with the threshold variable being the credit market variable. I am having no problem estimating the threshold break. However when I estimate the sample above the threshold the impulse responses are explosive. When I estimate the sample below the threshold the impulse responses are well behaved. When I estimate over the entire sample (a traditional VAR) the impulse responses are well behaved.
I can not figure out why the VAR is becoming non-stationary over this sub-sample. The way the threshold is being identified the sub-sample above the break includes 80 of the 360 observations. Below the break the sub-sample is obviously the remaining 280 observations. I don't see how this is related to sample size though.
Any suggestions?
Thanks,
Lee
I am somewhat new to estimating threshold VARs but I am having a strange problem. Any insight or suggestion is appreciated. I have a simple 4 variable VAR (ordered: log difference of real GDP, log difference CPI, fed funds rate, credit market variable) all data is monthly from 1980:01 to 2011:01. I am estimating a threshold VAR with the threshold variable being the credit market variable. I am having no problem estimating the threshold break. However when I estimate the sample above the threshold the impulse responses are explosive. When I estimate the sample below the threshold the impulse responses are well behaved. When I estimate over the entire sample (a traditional VAR) the impulse responses are well behaved.
I can not figure out why the VAR is becoming non-stationary over this sub-sample. The way the threshold is being identified the sub-sample above the break includes 80 of the 360 observations. Below the break the sub-sample is obviously the remaining 280 observations. I don't see how this is related to sample size though.
Any suggestions?
Thanks,
Lee