Forecasting Türkiye Local Inflation With Global Factors

This paper investigates whether inflation forecasting in emerging economies can be improved with the inclusion of a global inflation component. Focusing on the headline inflation rate of Türkiye, we implement a forecasting exercise using a large dataset describing domestic macroeconomic as well as global inflation dynamics. Our factor-augmented predictive regression results show that incorporating global inflation factors derived from other emerging markets' inflation rates enhances forecasting accuracy of the local headline inflation rate. The results are robust to using alternative dimension-reduction methods, including the elastic net technique. Our findings contribute to the current methodological toolkit available to policymakers for predicting inflation in an emerging market context.