Alternative methods for estimating potential GDP: an application to the case of Peru

This article examines methodologies for estimating potential gross domestic product (GDP) in the Peruvian context, evaluating its relationship with inflation and its implications for economic policy. Five non-structural methods (Hodrick-Prescott Filter, Segmented Trend, Nonparametric Smoothing, Baxter and King, and Beveridge-Nelson) and two structural methods (Production Function and Structural VAR) are compared, using annual data from 1950 to 2005. The results show that these methodologies allow for the identification of output gaps and changes in potential GDP, although they differ in the magnitude of these estimates. The relationship between the output gap and inflation is weak, suggesting that other factors have a greater influence on changes in inflation. It is concluded that, while these methods offer valuable information for economic decision-making, the uncertainty inherent in their estimates must be taken into account when implementing monetary policies. Therefore, the importance of appropriately selecting the estimation method according to the specific objective of economic policy is emphasized. (Abstract and audio: Department of Economic Publications)