State space and NAIRU estimation
Posted: Tue Oct 11, 2011 4:21 am
Hi,
I some questions regarding the fomulation of my state space for use in NAIRU estimation using the Kalman filter. First, I'd like to ask some more general type questions. I have no issue with setting up the state space model and estimating it, but my results are not believable so I'm sure I have to make some ammendments. Particularily I'm unsure of how to specify the errors in my signal- and state equation. Let's say I have one signal equation modeling inflation as a function of the unemployment gap and other factors. My state equation models the beaviour of the NAIRU (random walk for now). So the state space could look something like this:
@signal inflation=c(1)*inflation(-1)+c(2)*inflation(-2)+c(3)*(uenmployment-NAIRU)+c(4)*(supply shock)+error
@state NAIRU=NAIRU(-1)+error2
First, I would like to make sure that both my errors are defined as N(0,variance). What's the code for doing that? As far as I've understood, the results are very sensitive to the signal/noise ratio, i.e. var(error2)/var(error1). How can I set a particular value for the signal/noise ratio? How can I make sure that there is a long-run Phillips curve by limiting c(1)+c(2)=1?
Any suggestions for estimating the signal/noise ratio for my particular data?
Thanks for your help!
Halfdan
I some questions regarding the fomulation of my state space for use in NAIRU estimation using the Kalman filter. First, I'd like to ask some more general type questions. I have no issue with setting up the state space model and estimating it, but my results are not believable so I'm sure I have to make some ammendments. Particularily I'm unsure of how to specify the errors in my signal- and state equation. Let's say I have one signal equation modeling inflation as a function of the unemployment gap and other factors. My state equation models the beaviour of the NAIRU (random walk for now). So the state space could look something like this:
@signal inflation=c(1)*inflation(-1)+c(2)*inflation(-2)+c(3)*(uenmployment-NAIRU)+c(4)*(supply shock)+error
@state NAIRU=NAIRU(-1)+error2
First, I would like to make sure that both my errors are defined as N(0,variance). What's the code for doing that? As far as I've understood, the results are very sensitive to the signal/noise ratio, i.e. var(error2)/var(error1). How can I set a particular value for the signal/noise ratio? How can I make sure that there is a long-run Phillips curve by limiting c(1)+c(2)=1?
Any suggestions for estimating the signal/noise ratio for my particular data?
Thanks for your help!
Halfdan