This page provides a deeper and more elaborate explanation of the methods for each of the four indicators used by Food Monitor. Should you have further questions regarding the methods for any of the indicators described below, you can contact us at info(at)foodmonitor.org.
When there is trade between different regions, prices typically converge as traders engage in arbitrage, thereby eliminating price differences away from the trade costs. Changes in prices are then transmitted from the region where they initially occurred to other regions. Such price changes may be a result of an unusual harvest, an unexpected change in consumption or other factors. If a scarcity of food occurs in a particular region, this region benefits from arbitrageur activities that help stabilize the supply. Other regions may, however, be negatively affected as their food might be exported to the region in need. This, in turn, acts as a risk sharing mechanism between regions. This also implies that 'problems can be imported', meaning that high prices elsewhere can cause high local prices. The degree to which prices are transmitted indicates to what extent markets are integrated and risks are shared.
The price transmission indicator reflects the influence of global prices on domestic prices for the individual countries. Since global prices are subject to global demand and supply, market integration is a crucial determinant. The higher the domestic market is integrated with the global market, in other words the more the country engages in international trade for commodities, the stronger the influence is that global prices have on domestic prices.
The impact of international price shocks on domestic prices is captured by the transmission coefficients estimated in Kalkuhl (2014) using a time series model while exploiting an extensive price database with global and local prices. These coefficients are used to calculate the expected price changes within a country solely depending on the global price changes. For this indicator, we use daily global prices from the CME Group, one of the world’s largest options and futures exchange, the South African Futures Exchanges (SAFEX), and the International Grains Council (IGC) Commodity Index.
Combining these transmission elasticities with price changes, the partial impact of international prices on domestic prices is computed and successively compared to the realized historical domestic volatility. The results are then matched with predetermined thresholds based on which we assign different risk levels: low risk, moderate exposure to international price spike, high exposure to international price spike.
However, it is important to note that this indicator only captures the effects of global price movements on domestic markets. Local effects on domestic prices are not reflected unless they do significantly affect the global prices.
For more detailed information on price transmission and price volatility, please click here.
If food is scarce in a specific region, the local as well as international press is usually reporting about this. In some cases, there are limitations about what the local press is allowed to report. This may influence the coverage and the way the situation is presented. However, the international press usually also covers situations which may not be fully covered locally. The idea of the Food Security News Hotspot indicator is that the media coverage of a food security crisis often scales with the intensity of the crisis. In a situation with no or little problems, there is typically little news coverage whereas many warnings are issued if huge local problems occur that affect many people. However, the media coverage is a weak indicator for the intensity of a crisis as the coverage also depends on many other factors such as: Are there currently other big problems or events which distract media attention? Is the local government allowing reports about the situation? Are many people affected or only some small groups? Is the situation of food insecurity occurring while many social systems are breaking down (e.g. during war) or social systems working fine apart from the food scarcity? The map is therefore an indicator of the magnitude of the news coverage and only a weak and indirect indicator of the intensity of food insecurity.
The map of news hotspots reflects the latest news which are related to global and regional food security. Google news feeds are used to daily collect all relevant news, which are then aggregated on a weekly basis. Collected news articles are automatically included, but regular checks for relevance of the articles and reliability of the algorithm are performed. Only news in English are collected. This limits the usefulness of the indicators in countries where no English is spoken. Nevertheless, there is always a certain coverage by the international press. The individual news articles which are collected can be seen and reviewed on the Food Security Portal. This collection of news provides a times series of the number of news articles per week for all covered countries.
To deal with countries of different sizes and a different coverage within the English speaking press, the indicators are calibrated based on the number of warnings for each country in the past. Hence, a "medium risk" is assigned if there are substantially more news than in the past for a particular country. More precisely, the threshold between "low risk" and medium risk" is set to one standard deviation above the historic mean number of news per week. A "high risk" is assigned if the number of news stories is extremely high and exceeds twice the standard deviation above the historic mean. This only occurs roughly 2.1% of the time. As a result, countries which consistently suffer from food insecurity may not appear as quickly on the map of news hotspots whereas countries which are usually mostly food secure may quickly appear on the map if there are local food scarcities which are reported about. As this is a relative threshold, all countries will at some point appear as in "high risk". More precisely, for each country, the times with the highest news coverage will appear as "high risk" even though there may not necessarily be large problems at these times. This is another limitation of the food security news hotspots indicator.
The Excessive Price Volatility tool provides a visual representation of historical periods of excessive global price volatility from 2000-present, as well as a daily volatility status. This status can alert policymakers when world markets are experiencing a period of excessive food price volatility; this information can then be used to determine appropriate country-level food security responses, such as the release of physical food stocks.
Based on sophisticated statistical modelling, the tool provides daily price variability ratings for four major crops: hard wheat, soft wheat, maize and soybeans. Data for the model is obtained from closing prices of future contracts traded on the Chicago Board of Trade and in the case of hard wheat, obtained from the Kansas Board of Trade.
A period of time characterized by extreme price variation (volatility) is a period of time in which we observe a large number of extreme positive returns. An extreme positive return is defined to be a return that exceeds a certain pre-established threshold. This threshold is normally taken to be a high order (95 or 99%) conditional quantile, (i.e. a value of return that is exceeded with low probability: 5 or 1%). In this model we are using the 95% quantile.
Days in volatilityreflects the number of continuous days in the current level of volatility. Script taken from the Food Security Portal.
A technical documentation of this tool can be downloaded here.
The global supply risk indicator serves as a non-price assessment of the classical agricultural market fundamentals. Its economic foundation is on the competitive storage model such that equilibrium prices are a function of current and expected supply and demand.
The supply risk indicator is calculated using monthly updated forecasts on changes in total supply per capita and in total GDP per capita. This is then normalized by a scaling factor that measures historical food price fluctuations.
The price elasticity of expected supply change and that of expected income per capita (demand) change, which are used in the risk calculation, are estimated using simple regression models. We use data on production forecasts and stocks from the United States Department of Agriculture (USDA) supply and demand estimates, mid-year global population growth rates from the US Census, and GDP projections from the International Monetary Fund (IMF).