Price Volatility, Reserves and Public Policy

1. Price Volatility, Reserves and Public Policy Brian Wright Chair, Agricultural and Resource Economics UC Berkeley ICABR Ravello Italy June 19, 2013

2. Post- “Inside Job” I perceive a need for disclosure: Recent or current grant support: • AMIS initiative of G20 • Energy Biosciences Initiative (UC Berkeley, UIUC, LBL, BP, funded by BP) – researches cellulosic biofuels • USDA • NIH • NSF • USPTO • Giannini Foundation

3. Disclosure (contd.) • Current consulting relationships: • World Bank • FAO • No recent positions in commodity markets • No investments in agricultural input or service providers, or significant commodity market or energy market participants. • In past 2 years, I was a consultant/expert witness engaged by an entity that produces and exports agricultural products. I was recently an expert witness in a case involving generic drug entry in pharmaceuticals • I recently made a presentation at a major agricultural bank • Last month I was compensated by a leading investment firm for a presentation at their head office • I am happy to identify any of the firms involved in the above activities, should any audience member request that I do so.

4. Global Grain Markets: Assumptions for a simple model • Production is seasonal, most often with one grain harvest ht per year. • positive trend due to productivity increases. • There is an inevitable one-year lag between the investment in planting an area At and the harvest. • within-year planned supply can be approximated as pre-determined. • Expected harvest at planting, Et-1ht, is roughly proportional to planted area. • The realized harvest is subject to random shocks proportional to expected harvest, due to variation in the weather, the prevalence of pests, and other shocks. • Grain consumption is a negative function of price. • Positive trend due mainly to (exogenous) population increase. • Other demand shifters such as income and tastes and tend to be slow-acting, not “shocks” • So we can write the inverse consumption demand as pt = F(ct).

5. Simplest S-D model is consistent with long run increasing production trend • Obvious (linear?) uptrend in production • Obvious downtrend in price in long view

6. Index of World Detrended Price vs. Index of Detrended Production for Rice (1961-2012)

7. After detrending, simplest S-D model cannot explain rice price volatility • No consistent relation even before 2005 • Simplest Marshallian S-D model fails if applied to rice alone

8. Try Adding Storage to the Marshallian Market Model Assume stylized facts of major grain markets: • Grains can be stored from period to period without cost, waste, or “shrinkage” • Grain stocks cannot be negative. • Consumption cannot be negative.

9. Available supply is used in two ways: • for consumption in year t, ct and for carryout stocks, which become carryin stocks xt for the next year. • for carryout stocks, which become carryin stocks xt for the next year.

10. Available supply at time t, at, for a given year comes from the current harvest htand from stocks xt-1carried in from the previous harvest: • at= ht + xt-1

11. Available supply is used in 2 ways: • Consumption • Carryout stocks ct= at – xt.

12. Sources of available supply • Available supply atfor a given year comes from the current harvest htand from stocks xt-1carried in from the previous harvest. • at= ht + xt-1

13. If storers are competitive and aim to maximize expected profits, and the only cost of storing is the (constant) opportunity cost of capital r, then their behavior will result in the following complementary conditions for equilibrium intertemporal arbitrage:

14. Nonlinearity of Inverse Total Demand Function and Price Dynamics

15. Does Storage Dynamics Explain Prices?

16. Rice: Index of Detrended Price versus Observed Stock-to-Use Ratio • No consistent relation even before 2005 • Adding storage to the rice market model does not make it fit

17. Try Aggregation of Rice, Maize, and WheatCalories price and grain prices

18. Index of World Detrended Price vs. Index of World Detrended Production for Calories • Simple S-D model fails even for aggregate grains

19. Was there a perfect supply storm?

20. Weather and Global Warming?Really?

21. US Corn Harvest

22. Cost push?

23. Consumption Surge in India and China?Consider their net exports:

24. Let’s try: Aggregation Plus Storage

25. Calories of 3 major grains:Index of Detrended Price versus Observed Stock-to-Use Ratio - maize, wheat and rice: Now it works!

26. But are stocks consistent with the naïve model?

27. DetrendedPrice-implied Stocks Data vs. Detrended Observed Price Index for Calories

28. Calories: Actual Stocks vs. Stocks implied by Price Data and commodity model

29. Actual SUR vs. price-estimates-implied SUR for Calories(why good fit only through 2004?)

30. Calories: Index of Detrended Price versus Observed Stock-to-Use Ratio

33. Transfer to Farmer Wealth:Financial crisis plus biofuels

34. Permanent Mandate Anticipated and Imposed

35. Shifts due to a Temporary Mandate versus Permanent Mandate

36. Implication of Storage Model • Relation highly nonlinear due to influence of stocks levels • Cannot calculate “percentages of blame” • Marginal effect is the key: Relevant for policy • Linear SR time series irrelevant

37. Policy Options • Self sufficiency: • Strategic reserves • Virtual reserves (IFPRI 2008) • Subsidize storage • Ban Export Bans (if you can) • Limit biofuels use of grains and sugar • Farmer risk management • Acquire foreign farmland and grow the national staple • Biofuels diversion contracts • GM crops?

38. Policy Options: Tools for Execution? • Strategic reserves • Subject to political interference - almost always against security and in favor of pressing political interests • Acquisition and disposal rules contentious (see e.g. commodity fund rules)

39. Policy Options: Tools for Execution? • Strategic reserves • US strategic petroleum reserve as example • But substitution reduces effectiveness inevitably • Speculative attacks look bad, but actually can increase efficiency • US silver reserve as cautionary tale (among others)

40. Public and Private Stocks: Interactions

41. Policy Options: Tools for Execution? • Strategic reserves • US silver reserve as cautionary tale (among others)

42. Policy Options: Tools for Execution? • Virtual Reserves (IFPRI 2008) • Naked short positions where necessary to convince markets that their price expectations will not be fulfilled? • What would have happened if adopted in 2007/08?

43. Ban Export Bans? • Prisoner’s dilemma • Export bans can prevent hunger in weak regimes • Fundamental trade problem: Biofuels as classic (but huge) price discrimination Divert grain from inelastic (food) to elastic energy) demand market

44. Acquire foreign farmland and grow the national staple • Acquire foreign farmland and grow the national staple • Good deal for all? Capital or oil for land output and supply security? • Sovereign risk? • Political commitment durability?

45. Policy Options: Tools for Execution? • Acquire foreign farmland and grow the national staple • Buy-in from private sector? • Buy-in from resident peasants? • “terra nullius??”

46. Policy Options: Tools for Execution? • Subsidize storage? • Advantage: depoliticize buy-sell decisions

47. Policy Options: Tools for Prevention/Amelioration? • Political alliances, naturally • Reduce incentive to use biofuels by moderating oil prices? • Support transparency in grain markets • AMIS initiative • Reduce ignorance that generates panic

48. Policy Options: Tools for Execution?Impact of Biofuels: Limit biofuels use of grains and sugar • Not just in EU and US • Huge transfer to landowners and farmers • Huge transfer from poor consumers

49. Transfer to Farmer Wealth:Financial crisis plus biofuels

50. Relevance of GM for poor? • Depends on biofuels policy • Increase RFS continually? • If so GM can do nothing for poor • Not North/South issue but Landowner/Consumer