Template-type: ReDIF-Paper 1.0 Author-Name: Tamkin Nuriyev Author-Email: Author-Workplace-Name: Central Bank of the Republic of Azerbaijan Author-Workplace-Homepage: Author-Name: Aygun Garayeva Author-Email: Author-Workplace-Name: Central Bank of the Republic of Azerbaijan Author-Workplace-Homepage: Author-Name: Gulzar Tahirova Author-Email: Author-Workplace-Name: Central Bank of the Republic of Azerbaijan Author-Workplace-Homepage: Title: Construction and Forecasting of the Imported Food Price Index in Azerbaijan Abstract: Using 800,000 transaction-level customs records from January 2018 to February 2026, the paper constructs a trade-weighted Imported Food Price Index (IFPI), covering 34 items from the consumer basket with significant import dependence. The index is developed using the Fisher ideal methodology to provide a timely measure of external food price pressures. The results indicate that the IFPI leads official food Consumer Price Index (CPI) by approximately two months, with a maximum correlation of 0.81, highlighting its potential usefulness as an early indicator of domestic food inflation. Building on this, the paper develops a forecasting framework for the IFPI by combining non-parametric Binary Segmentation and Hidden Markov Models with a regularized machine-learning ensemble. The model employs an ensemble approach that combines Histogram-based Gradient Boosting Regression Tree, Random Forest, and Extreme Gradient Boosting, alongside rigorous time-series crossvalidation. The optimized ensemble achieves a 58% out-of-sample R² relative to a random walk benchmark, vastly outperforming traditional linear Autoregressive Distributed Lag (ARDL) (13.60%) and Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) (0.18%) baselines. The forecast results are intended to be incorporated into broader inflation forecasting models to improve short-term projections. Keywords: Import price index; Fisher Ideal index; Food price inflation; Machine learning forecasting; Hidden Markov models Classification-JEL: C43, C53, C55, E31, F14 Length: 20 pages Creation-Date: 2026-08-03 Revision-Date: Publication-Status: Number: 20-2026 File-URL: http://repec.graduateinstitute.ch/pdfs/Working_papers/HEIDWP20-2026.pdf File-Format: application/pdf File-Size: Handle: RePEc:gii:giihei:HEIDWP20-2026