An index tracking imported food prices in Azerbaijan can provide signals on the formation of food inflation in the country approximately two months in advance. The findings are outlined in a study titled “Construction and Forecasting of the Imported Food Price Index in Azerbaijan” prepared by Central Bank of Azerbaijan (CBA) employees Temkin Nuriyev, Aygun Garayeva and Gulzar Tahirova. As part of the study, the researchers developed the Imported Food Price Index (IFPI) to more accurately monitor price changes for imported food products in Azerbaijan.
The index covers the period from January 2018 to February 2026 and was based on data from around 800,000 customs transactions selected from approximately 16 million raw import records. The new index was developed taking into account the structure of the consumer basket and includes 34 major product categories and 44 product types with a high degree of import dependence. According to the authors, this approach helps reduce the aggregation problem that may arise in traditional import price indicators calculated across broad product groups and allows for a more accurate assessment of how external price changes affect domestic food prices.
One of the key findings of the study is that the relationship between the IFPI and the official food consumer price index (CPI) has a leading time pattern. According to calculations, the correlation coefficient between the two indicators reaches 0.81 with a two-month lag. This indicates that changes in imported food prices can provide advance signals about future food price dynamics in Azerbaijan.
Customs data becomes available on average 20–25 days after the reference month. Meanwhile, food CPI data from the State Statistics Committee is usually published 10–15 days after the end of the month. As a result, once the IFPI for a given month becomes available, it can provide an information advantage of approximately 6–7 weeks compared with the release of the official food CPI indicator for the following period,” the study said.
The research also developed a machine learning-based approach to forecasting imported food prices. The authors noted that this approach produced more accurate forecasting results compared with traditional linear models. According to the study, global changes in food, energy and fertilizer prices also have a significant impact on imported food price dynamics.
The correlation between the IFPI and the FAO Food Price Index stands at 0.70, while the correlation with fertilizer prices is 0.66 and with natural gas prices is 0.62. The authors noted that food products account for approximately 43% of Azerbaijan’s consumer basket. Therefore, more accurate and timely monitoring of external price shocks is important for forecasting food inflation and broader inflation trends.
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