Construction and Forecasting of the Imported Food Price Index in Azerbaijan

Tamkin Nuriyev, Aygun Garayeva and Gulzar Tahirova
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Tamkin Nuriyev: Central Bank of the Republic of Azerbaijan
Aygun Garayeva: Central Bank of the Republic of Azerbaijan
Gulzar Tahirova: Central Bank of the Republic of Azerbaijan

No 20-2026, IHEID Working Papers from Economics Section, The Graduate Institute of International Studies

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 (search for similar items in EconPapers)
JEL-codes: C43 C53 C55 E31 F14 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2026-08-03
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