Toward an explicit inflation target: anticipating inflation in Peru

This study examines the predictive power of various economic indicators regarding inflation in Peru, within the context of an inflation-targeting regime adopted by the Central Reserve Bank of Peru (BCRP) in 2002. Using an empirical approach, bivariate models are applied and leading indicators are constructed by combining information from a sample of 269 variables to forecast inflation in the short and medium term, with a special focus on the robustness of out-of-sample forecasts. The main results reveal that certain variables from the monetary sector, among others, exhibit strong predictive power. Particularly, combining forecasts and using composite factors improves the accuracy of the estimates, yielding a 12–14% improvement compared to individual forecasts. The analysis suggests that these tools are useful not only for forecasting inflation but also for formulating informed monetary policies. The implications highlight the importance of incorporating composite indices into policy design and the management of economic expectations. (Abstract and audio: Department of Economic Publications)