Is Better Global Governance of the Food System the Answer to Improve Resilience?


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May 16 in Parallel Session 3D "Food Price Spikes & Financial Crises: Dealing with Regional and International Market Shocks". Presented by Maximo Torero, IFPRI.

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Is Better Global Governance of the Food System the Answer to Improve Resilience?

  1. 1. Maximo Torero Is better global governance of the food system the answer to improve resilience? BUILDING RESILIENCE FOR FOOD & NUTRITION SECURITY 15-17 MAY 2014, ADDIS ABABA, ETHIOPIA
  2. 2. Effects on world prices of trade policy reactions for selected countries 0% 10% 20% Exogenous demand increase [initial perturbation] Effects of increases in export taxes to mitigate the shock on domestic prices Effects of decrease in import duties to mitigate the shock on domestic prices Interaction effects between import and export restrictions Policy Effects “Natural” Shock Source: Bouet and Laborde, 2009. MIRAGE simulations
  3. 3. Import tariffs on food products: a heavy burden for the poor 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% Bermuda CentralAfricanRep. Chad Congo Cyprus EquatorialGuinea Iceland India Ireland Israel Japan Kenya Malta Morocco Nigeria Norway Pakistan Portugal Rep.ofKorea Romania SaintKittsandNevis SerbiaandMontenegro Seychelles SolomonIsds Switzerland Thailand Tunisia Turkmenistan Ukraine UnitedKingdom Average Tariff on Calories Average Tariff on Proteins Source: Deason and Laborde (2010)
  4. 4. Periods of Excessive Volatility Note: This figure shows the results of a model of the dynamic evolution of daily returns based on historical data going back to 1954 (known as the Nonparametric Extreme Quantile (NEXQ) Model). This model is then combined with extreme value theory to estimate higher-order quantiles of the return series, allowing for classification of any particular realized return (that is, effective return in the futures market) as extremely high or not. 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 taken to be a high order (95%) conditional quantile, (i.e. a value of return that is exceeded with low probability: 5 %). One or two such returns do not necessarily indicate a period of excessive volatility. Periods of excessive volatility are identified based a statistical test applied to the number of times the extreme value occurs in a window of consecutive 60 days. Source: Martins-Filho, Torero, and Yao 2010. See details at 2014 Please note Days of Excessive volatility for 2014 are through March 2014
  5. 5. What is happening today
  6. 6. In summary
  7. 7. Global Stock to use ratios
  8. 8. High concentration of exports
  9. 9. Increase in the number of extreme events Source: Year Numberofextremeevents