1. TRAINING ON FERTILIZER DEMAND FORECASTING Patrick Heffer, IFA 19 April 2013 Moscow, Russia

2. What Is IFA?

3. IFA in Brief Non-governmental organization representing the world fertilizer industry About 540 members in 85 countries( including Uralkali and many other Russian fertilizer producers) Based in Paris Organized around three standing committees: o Technical o Production and International Trade o Agriculture Main activities: market analysis, issue management/ advocacy, conference organization

4. IFA Agriculture Committee Four objectives: Address issues facing fertilizer demand Promote the efficient, balanced and responsible use of fertilizers Improve the public image of fertilizers Develop reliable and authoritative fertilizer demand forecasts

5. Reports on demand forecasts twice a year  Annual Conference (May/June) medium-term (5-year) forecasts  Enlarged Council Meeting (Nov/Dec) short-term (1-year) forecasts Improving the forecasts  Develop network of correspondents  Guidelines for a crop-based approach  Regional training programmes IFA Agriculture Committee Develop reliable and authoritative fertilizer demand forecasts

6. IFA’s Fertilizer Demand Forecasts

7. Current strategy Rely on information provided by a network of correspondents in ~50 countries Heterogeneous inputs essentially due to different methodologies used depending on the countries  Trend forecasts  Government objectives  Recommended application rates  Econometric model (e.g. India, Brazil)  Crop-based / expert-based model (e.g. EU, USA) Methodology and Information Used by IFA

8. Correspondents are not enough Use additional sources of info (reports, articles…) on:  Economic context, weather, policy factors  Global agricultural situation Check consistency between national forecasts and the global scenario Forecasts provided by the correspondents are revised in more than half of the countries ! They are almost always revised down. And checks are needed Fertilizer demand forecasts are cross-checked with forecasts on the supply side  To ensure consistency between the two sets  To issue forecasts on the supply/demand balances Methodology and Information Used by IFA

9. National forecasts are the starting point: They provide the foundation for developing regional and global forecasts High margin of error Mostly over-estimation Small margin of error Balanced fluctuations around actual demand Objective Importance of Good National Forecasts

10. Objective - Improve national forecasts, which should result in turn in better regional and global projections Developed guidelines for a crop-based, expert-based forecast On-the-ground training programmes IFA Training Programme on Fertilizer Demand Forecasts

11. Crop-Based, Expert-Based Forecast Why Is It the Preferred Methodology?

12. What is a Good Forecast? ….. the most likely scenario Independent from:  Commercial pressures  Governmental objectives  Fertilizer recommendations As realistic as possible  Not too optimistic  over-investments  Not too pessimistic  would endanger food security Often more conservative than governmental targets

13. Types of Forecast Methodologies Trend analysis Growth rate models Production/trade models Econometric models Crop-based, expert-based models

14. Why Does IFA Recommend Using a Crop-Based, Expert-Based Approach? Can be used on a consistent basis across all the countries and regions Yields much more accurate forecasts than the trend analysis, growth rate models and production/trade models Does not require large databases and knowledge in econometrics as econometric models. Also, more accurate than econometric models Explains where changes in demand are anticipated to come from

15. The Four Stages of a Crop-Based, Expert-Based Forecast

16. The Four Stages Our Goal: “To Arrive at a Realistic, Objective, and Defensible Forecast” Main Steps: I.Create a Historical Database or ‘Base Year’ II.Develop a Qualitative Scenario: Outlook Conditions III. Prepare the Quantitative Forecast IV. Validate the Forecast

17. I. The Historical Database Overview Consists of Data for 3 Forecast Components: 1.Area Planted to Major Crops 2.Percent of Planted Area Fertilized by Nutrient and Crop Type 3.Average Application Rates of Nutrients by Crop Type

18. I. The Historical Database Data Collection 1.Area Planted to Major Crops Identify the Major Nutrient Consuming Crops Develop a Database: Major Crops Other Crops Potential Problems Only Harvested Area Data is Available Data Only Available for Some/Few Crops

19. Nutrient Use – Major U.S. Crops 68% 76% 73%

20. Acres Planted – Major U.S. Crops

21. Share of Total Fertilizer Consumption by Crop Type in 2010 in Russia wheat + barley + maize + sunflower + sugar beet = 75-80% Source: IFA

22. I. The Historical Database Data Collection 2. Percent of Planted Area Fertilized Identify Area Fertilized for Each Major Crop Express as Percent of Planted Area 3. Average Application Rates Determine Amount of Each Nutrient Applied to Crop Express in kg/ha Potential Problems Only Some Data Exists

23. Percent of Corn Acres Treated by Nutrient

24. Application Rate per Treated Corn Acre

25. Average Nutrient Application Rate - Corn

26. II. The Qualitative Scenario “What Will the Future Look Like?” Develop Assumptions About Conditions That Will Impact Crop Acreage and Nutrient Application Consider Domestic and World Economies Crop Market Conditions Fertilizer Market Conditions The Regulatory Environment Infrastructure Investments or Limitations Avoid Government/Industry Targets

27. III. The Quantitative Forecast Applying Your Qualitative Conditions “For Each Crop, Consider Impact of Stage II Assumptions on Each Forecast Component”: Area Planted Impacted by: Crop Prices Weather Government Policies Changes to Demand Infrastructure

28. “For Each Crop, Consider Impact of Stage II Assumptions on Each Forecast Component”: Percent of Area Fertilized and Application Rates Impacted by: Crop Prices and Yields Fertilizer Prices and Availability Soil Type, Moisture, and Weather Policy Changes III. The Quantitative Forecast Applying Your Qualitative Conditions

29. IV. Forecast Validation Recall Our Goal: “To Arrive at a Realistic, Objective, and Defensible Forecast” The Final Step: Verify That the Forecast Meets These Criteria 1.Cross Check Results 2.Seek Out Supporting Data 3.Compare to Other Methodologies Trend Forecast Econometric Model if Available Once Comfortable With the Forecast, Explain Results

30. Concluding Remarks Maintaining Your Forecast 1.Update Your Stage II Assumptions Regularly 2.Anticipate/Explain Structural Changes Historical Data Forecast 3.Compare Results With Others 4.Rely On and Trust Your Own Expertise Your Forecast Will Improve Over Time Progressive Increase of Crop Coverage Progressive Improvement of Data Quality

31. Crop-Based, Expert-Based Forecast in Summary Our goal: “to arrive at a realistic, objective, and defensible forecast” Main steps: I.Create a historical database or ‘base year’ II.Develop a qualitative scenario: outlook conditions III.Prepare the quantitative forecast IV.Validate the forecast 3 variables 1.Area planted to major crops 2.Percent of planted area fertilized by nutrient and crop type 3.Average application rates of nutrients by crop type

32. Outlook for World and Regional Fertilizer Demand Note regarding data presented: Short-term outlook of December 2012 Medium-term Outlook of June 2012

33. World Cereal Production and Utilization (Mt) Source: FAO Balance forecast at the end of the 2012/13 campaign:  FAO: -30 Mt  USDA: -45 Mt  IGC: -45 Mt Balance forecast at the end of the 2012/13 campaign:  FAO: -30 Mt  USDA: -45 Mt  IGC: -45 Mt

34. World Cereal Stock-to-Use Ratio Source: FAO Anticipated ending stock evolution in 2012/13: Wheat:  -23 Mt (-12%)  Lowest S/U ratio since 2007/08; 2 nd lowest since 1980  Major exporters stock-to- disappearance: 13.9% Coarse grains:  -13 Mt (-8%)  Lowest S/U ratio since 1980  Major exporters stock-to- disappearance: 8.9%; below 6% in the US Rice:  Increase for 6 th consecutive year Anticipated ending stock evolution in 2012/13: Wheat:  -23 Mt (-12%)  Lowest S/U ratio since 2007/08; 2 nd lowest since 1980  Major exporters stock-to- disappearance: 13.9% Coarse grains:  -13 Mt (-8%)  Lowest S/U ratio since 1980  Major exporters stock-to- disappearance: 8.9%; below 6% in the US Rice:  Increase for 6 th consecutive year

35. Relative Evolution of Agricultural Commodity Prices Sources: Financial Times and IMF Relative Price Evolution from January 2006 to October 2012 Rice Maize Soybean Wheat

36. Global Fertilizer Demand Short-term Forecasts (Mt nutrients) Source: IFA Agriculture Reminder on reference years: ~1/2 of the world market: January X  December X ~1/6 of the world market: April X  March X+1 ~2/6 of the world market: July X  June X+1

37. Global Fertilizer Demand Short-term Forecasts (Mt nutrients) Source: IFA Agriculture

38. Regional N Fertilizer Demand Short-term Forecast (Mt N)

39. Source: IFA Agriculture Regional P Fertilizer Demand Short-term Forecast (Mt P 2 O 5 )

40. Source: IFA Agriculture Regional K Fertilizer Demand Short-term Forecast (Mt K 2 O)

41. Source: IFA Agriculture 2013/14 vs. 2007/08 (Mt nutrients) 49% of global net increase

42. Medium-Term Outlook for Agricultural Commodity Prices World Nominal Prices (US$/t) Source: OECD-FAO

43. Global Fertilizer Demand Medium-term Outlook (Mt nutrients) Source: IFA Agriculture Base year

44. Regional Fertilizer Consumption Medium-term Outlook (Mt nutrients) Source: IFA Agriculture 30% 21% 24% 6%

45. for more information: www.fertilizer.org