Following Doménech and Gómez (2006), and using quarterly Peruvian data for 1979:1-2007:4, I estimate a model that exploits the information contained in the inflation, unemployment and private investment rates in order to estimate nonobservable variables as output gap, the NAIRU and the core infflation. The unknown parameters are estimated by maximun likelihood using a Kalman filter initialized with a partially diffuse prior, and the unobserved components are estimated using a smoothing algorithm. The results suggest that only the inflation 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 statistic filters gives poor approximations.