Following Doménech and Gómez (2006), and using quarterly Peruvian data for 1970:1-2007:4, I estimate a model that exploits the information contained in the inflation, unemployment and private investment rates in order to estimate non-observable variables as output gap, the NAIRU and the core inflation. The unknown parameters are esti- mated by maximun likelihood using a Kalman filter initialized with a partially difuse prior, and the unobserved components are estimated using a smoothing algorithm. The results suggest that only the infla- tion rate contains useful information in order to estimate the output gap. Estimates suggest poor performance for the unemployment and private investment rates. I explain this issue as related to the poor quality of the construction of these variables. In order to perform a sensitivity analysis, I estimate the output gap using other alternative methods. The correlations are very different and very far away from the estimates obtained in this paper. It is clear that estimates obtained from simple statistical filters give poor approximations.