Dear all,
I and my research companion are working on a DSGE model for the philippine economy. However, the Philippines do not have some important observable variables causing the model to have more shock variables than observables. This results to parameter estimates that are not significant. Is this a usual problem? If so, what are ways to deal with such a problem?
Thanks so much,
Maureen
Hi Jpfeifer,
I’ve looked into Smets Wouters 2007 paper, their model have 7 observable variables and 7 exogenous disturbances. They also mentioned matching the number of structural shocks to the number of observables. Do you think it matters whether or not the number of observable variables and number of shocks used are the same? (Hi, If anyone had encountered this situation, please feel free to post. Thanks y’all.)
Also, thanks for pointing out the reasoning behind the testing of parameter estimates.
Regards,
Maureen
Dear Maureen,
sorry, I forgot that Smets/Wouters do not have measurement error. Regarding your question: It clearly does not matter.The only condition is that you have at least as many disturbances as you have observed series as otherwise stochastic singularity would occur. That’s the reason why Smets/Wouters match the number of shocks to the number of variables. There is for example the Schmitt-Grohe/Uribe (2009)-paper “What’s news in business cycles?”. They have several exogenous disturbances and add additional measurement error to each observed variable:
columbia.edu/~mu2166/news_in_bc/paper.pdf
This gives you more shocks than observed variables.
Best
Johannes
Thanks Johannes, a pleasure to get your reply.
Regards,
Maureen