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This indicator gives regular price information on a basket of goods to help ensure appropriate measures can be taken to offset food price anomalies

The indicator of food price anomalies (IFPA) identifies markets prices that are abnormally high. The IFPA relies on a weighted compound growth rate that accounts for both within year and across year price growth. The indicator directly evaluates growth in prices over a particular month over many years, taking into account seasonality in agricultural markets and inflation, allowing to answer the question of whether or not a change in price is abnormal for any particular period.

Ministry of Agriculture

Ministry of Agriculture

Food commodity prices in the FPMA tool are updated monthly. Food Price Indices in FAOSTAT are updated quarterly.

US Currency

The thresholds for the 𝐼𝐹𝑃𝐴𝑦 are expressed as the normalized difference of the compound growth rate of prices from their historical mean for the predefined period. The indicator of price anomalies (IFPA) relies on two compound growth rates (CGR’s), a quarterly compound growth rate (CQGR) and an annual compound growth rate (CAGR). A CGR is a geometric mean that assumes that a random variable grows at a steady rate, compounded over a specific period of time. Because it assumes a steady rate of growth the CGR smooth the effect of volatility of price changes. The CGR is the growth in any random variable from the price at the beginning of the period to the price at the end of the period, raised to the power of one over the length of the period of time being considered

The indicator of price anomalies (IFPA) relies on two compound growth rates (CGR’s), a quarterly compound growth rate (CQGR) and an annual compound growth rate (CAGR). A CGR is a geometric mean that assumes that a random variable grows at a steady rate, compounded over a specific period of time. Because it assumes a steady rate of growth the CGR smoothes the effect of volatility of price changes. The CGR is the growth in any random variable from time period  to , raised to the power of one over the length of the period of time being considered

Where: 
𝐶𝑋𝐺𝑅_t is the quarterly or annual compound growth rate in month t 
𝑃_tA  is the price at the beginning of the period 
𝑃_tB is the price at the end of the period,  
𝑡_B − 𝑡_A  is the time in months between periods 𝐴 and 𝐵. 
The quarterly (𝑄𝐼𝐹𝑃𝐴_yt) and annual (𝐴𝐼𝐹𝑃𝐴_yt) indicators of food price anomalies are then defined as: 

𝐶𝑋𝐺𝑅𝑦𝑡 is either the quarterly or annual compound growth rate in month t for year y 

𝑊_𝐶𝑋𝐺𝑅𝑡 is the weighted average of either the quarterly or annual compound growth rate for month t across years y 

𝜎 ̂𝑊_𝐶𝑋𝐺𝑅𝑡 is the weighted standard deviation of either the quarterly or annual compound growth rate for month t over years y, 

𝑋𝐼𝐹𝑃𝐴𝑦𝑡 is either the quarterly or annual indicator of a price anomaly.

The 𝐼𝐹𝑃𝐴𝑦 and its subcomponents.

Mathematically the IFPA for a particular year 𝑦 in month 𝑡  is calculated as the weighted sum of the quarterly indicator of food price anomalies (𝑄𝐼𝐹𝑃𝐴𝑦𝑡), and the annual indicator of food price anomalies(𝐴𝐼𝐹𝑃𝐴𝑦𝑡) as stated in equation 1. 

𝐼𝐹𝑃𝐴𝑦𝑡 = 𝛾𝑄𝐼𝐹𝑃𝐴𝑦𝑡 + (1 − 𝛾)𝐴𝐼𝐹𝑃𝐴𝑦𝑡 

Where:  
𝐼𝐹𝑃𝐴𝑦𝑡 is the indicator of food price anomalies in year 𝑦 and month 𝑡  
𝑄𝐼𝐹𝑃𝐴𝑦𝑡 is the quarterly indicator of food price anomalies in year 𝑦 and month 𝑡 
𝐴𝐼𝐹𝑃𝐴𝑦𝑡 is the annual indicator of food price anomalies in year 𝑦 and month 𝑡 
𝛾 is a weight with a value of 0.4. 

The weight 𝛾 establishes the relative importance of quarterly (𝑄𝐼𝐹𝑃𝐴𝑡 ) anomalies to the year-onyear price variations (𝐴𝐼𝐹𝑃𝐴𝑦𝑡). The weight𝛾 (1 − 𝛾)--SDG indicator 2.c.1 is then calculated as the arithmetic mean over 𝑡 months of the 

Where:  
𝐼𝐹𝑃𝐴𝑦 is the annual indicator of food price anomalies in year 𝑦  
𝐼𝐹𝑃𝐴𝑦𝑡 is the indicator of food price anomalies in year 𝑦 and month 𝑡 
𝑡  is the number of months in a year 

To identify markets prices that are abnormally high.

It is appropriate to caution the reader that the indicator is just a guide to understanding market dynamics. As such, one cannot rely on it as the sole element to determine whether a food price in a particular market at a given time is abnormally high or low due to the direct effects of local policies. Results must be weighed with other available information on market fundamentals, macroeconomic context and external shocks.

All the metadata shown in this document was gathered from United Nation Statistics Division. The metadata was extracted from https://unstats.un.org/sdgs/metadata/.