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Determinants of Prices of Agricultural and Mineral Commodities Jef fr ey Fr ankel, Har var d Univer sity, & Andr ew Rose, Univer sity of Califor nia, Ber keley First draft of a paper for the Reserve Bank of Australia To be presented at pre-conference, 16 June, 2009, Westfälische Wilhelms University Münster, Germany; Co-sponsored also by CAMA, Australia, & VERC, Wilfred Laurier University, Canada The determination of prices for oil and other mineral & agricultural commodities  falls predominantly in the province of microeconomics  But in periods when many commodity prices are moving far in the same direction at the same time, it becomes difficult to ignore the influence of macroeconomics  The decade of the 1970s  The decade of the 2000s ► A rise in the price of oil might be explained by “peak oil” fears, a risk premium on Gulf  instability, or political developments in Russia, Nigeria or Venezuela ► Some farm prices might be explained by drought in Australia, shortages in China, or ethanol subsidies in the US Commodity Price Index 100 150 200 Monthly data from Jan 2000 to Feb 2008 50 All commodity price index in US$ But it cannot be coincidence that almost all commodity prices rose together during much of the decade, and peaked abruptly in mid-2008 2000m1 Source: IMF 2002m1 2004m1 Time 2006m1 2008m1 Three theories competed to explain the ascent of commodity prices in 2003-08 Most standard: the global demand growth explanation, emphasizing especially growth in China, India, etc Also highly popular: destabilizing speculation Storability & homogeneity => asset-like speculation But destabilizing? Expansionary monetary policy low real interest rates expected inflation Counter-evidence to claims of destabilizing speculation Futures price of oil initially lagged behind spot price High volume of trading ≠ net short position Commodities that lack futures markets are as volatile as those that have them Historical efforts to ban speculative futures markets have failed to reduce volatility The real interest rate explanation Some argue that high prices for oil & other commodities in the 1970s were not exogenous, but rather a result of easy monetary policy [1] Conversely, a rise in US real interest rates in the early 1980s helped drive commodity prices down.[2] The Fed cut real interest rates sharply,2001-04, and again in 2008-09 My claim: it helped push up commodity prices.[3] [1] Barsky & Killian (2001) [2] Frankel (1985) [3] Frankel (2008) High interest rates Lower inventory demand; and encourage faster pumping of oil, mining of deposits, harvesting of crops, etc., because owners can invest the proceeds at interest rates higher than the return to saving the reserves Both channels – fall in demand & rise in supply – work to lower the commodity price A 3rd channel goes the same direction -trading in contracts (“the carry trade”): Low interest rates induce a “search for yield” among investors, who go long in commodities (just as FX, emerging markets., etc.) Inverse correlation between real interest rate and real commodity price index (DJ, 1950-2008) Counter-argument that applies to both the destabilizing-speculation & easymoney theories (Krugman, 2008, & Kohn, 2008):  Inventories of oil & other commodities were said to be low in 2008, contrary to the theory  Perhaps inventory numbers  not capture all inventories, or  are less relevant than (larger) reserves  King of Saudi Arabia (2008): “we might as well leave the reserves in the ground for our grandchildren.” 10 The same macro variables work to determine real oil price:             -Log real oil p | Coef Std Err t P>|t| + Log ind.prod | 3.445 239 14.44 0.00 log inventory | 455 119 3.82 0.00 Real int.rate | -.052 004 -13.24 0.00 Oil risk | 037 002 16.25 0.00 s-f spread | 026 002 15.94 0.00 counter | -.006 0002 -34.82 0.00 counter2 | 2.84e-06 6.23e-08 45.52 0.00 constant | -19.673 1.143 -17.21 0.00 21 Complete equation, from (5) and (8):  q = Q - (1/θ) r + (1/θ) γ(Y) + (1/θ)Ψ (σ) - (1/θ) Φ (INVENTORIES) (9)  We now test it on 12 commodities, with data from 1960s to 2008 22 -2.5 -3 -3.5 -4 1950 1975 2008 Corn 2008 1975 2008 1975 Platinum 2008 -.5 -1 1950 -3.5 -.5 -4 -1 1950 1975 2008 -3 1950 1975 1950 2008 -4.5 1950 1975 1975 Silver 2008 -1.5 -2 -2.5 -3 -3.5 1950 1975 2008 1975 2008 1975 2008 Gold -.5 -1 -1.5 -2 -2.5 1950 2008 Oats -2 1.5 -3 -1 Cotton Hogs 2.5 5 Cattle 1950 1975 Copper -.5 1950 1.5 -.5 1950 Oil 1975 -2 -2.5 -3 -3.5 -4 1950 2008 Soybeans Wheat Booms around 1974-75 and 2008 Log Real Spot Price 23 Table 3b Panel Results, for ln of real commodity prices, with risk included Annual data Ln(G-7 Volatility Risk Real GDP) Pooled 82* (.38) 57* 2.24 (1.57) 21 (.11) 1.75* -.06 (.58) (.04) SpotFutures Spread Inventories -.021** -.16** (.006) (.04) -.003* -.15** Real interest rate 02 (.04) 00 Commodity effects (.21) (.001) (.03) (.01) ** (*) => significantly different from zero at 01 (.05) significance level 24 Robust standard errors in parentheses; Intercept & trend included, not reported Other tests  Major commodity price indices  Unit root tests   Philips-Perron on individual commodities & panel  Co-integration tests    Johanson on individual commodities Panel Vector error correction 25 Overall conclusions (as of now)  The commodity-specific explanatory factors work surprisingly well:  Inventory holdings  Spot-futures spread  Volatility  In the latest results, the macroeconomic variables work surprisingly poorly:  Economic activity  Real interest rates 26 Possible extensions  Explore other measures of real interest rate and economic activity  Try survey data as a direct measure of expectations  Estimate simultaneous system  in inventories, expectations or spread, and commodity prices,  tied directly to the theory 27 Appendix  Graphs of data 28 1950 1975 2008 Corn 1975 2008 Cattle 1.5 5 1950 1975 2008 1975 Platinum 1950 1975 1950 2008 1.5 1950 1975 1950 2008 Cotton 2008 1.5 1950 Hogs 1950 Copper 1950 1.5 1975 2008 1950 Silver 1975 2008 1975 1950 2008 Soybeans Risk 2008 1950 1975 Oil 2008 2008 Gold Oats 1975 1975 Wheat 29 40 20 -20 -40 1950 1975 2008 Corn 20 -20 -40 -60 1950 100 50 -20 1975 2008 -50 1950 Cattle 1975 Platinum 2008 -50 1950 0 2008 2008 40 20 -20 -40 1950 1975 -20 1950 2008 Cotton 1975 Silver 1975 2008 1975 2008 1975 2008 Gold 100 50 1975 2008 -50 1950 2008 40 20 -20 -40 1950 Oats 0 20 40 20 -20 -40 1950 50 50 50 -50 1950 Hogs 100 -50 1950 1975 40 2008 Copper 20 -40 1950 1975 100 Oil 1975 Soybeans Wheat Future-Spot Spread 30 12.5 12 11.5 11 10.5 1950 1975 2008 Corn 11.6 11.4 1950 1975 2008 Cattle -2 1950 11 13 10.5 12 10 11 1950 1975 2008 Copper 11.8 11.2 14 1975 Platinum 11.1 11 10.9 10.8 10.7 1950 2008 1975 2008 Cotton 8.4 8.2 12 1975 2008 11 1950 1975 7.8 1950 2008 Oats 1975 Silver 2008 2008 1975 1950 Gold 13 Hogs 1950 9.5 1950 -.5 -1 11 10 1950 1975 2008 1975 2008 Oil 12.5 12 11.5 1975 11 1950 2008 Soybeans Wheat Log Inventory 31 .2 15 05 1950 1975 2008 Corn 15 05 1950 1975 2008 Copper 1975 2008 Cattle 1975 Platinum 15 05 1950 1975 2 1 1950 2008 1950 1975 1950 2008 Cotton 2008 1950 1975 1950 2008 Oats 1975 Silver 2008 2 1 1975 1950 2008 Soybeans Volatility 2008 1975 2008 1975 2008 Oil 1950 1975 Gold Hogs 1950 1950 Wheat 32 -5 1950 1975 2008 Real Interest Rate 33 31 30.5 30 29.5 29 1950 1975 2008 Log Real G-7 GDP 34 35

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Mục lục

  • Determinants of Prices of Agricultural and Mineral Commodities Jeffrey Frankel, Harvard University, & Andrew Rose, University of California, Berkeley

  • The determination of prices for oil and other mineral & agricultural commodities

  • ► A rise in the price of oil might be explained by “peak oil” fears, a risk premium on Gulf instability, or political developments in Russia, Nigeria or Venezuela. ► Some farm prices might be explained by drought in Australia, shortages in China, or ethanol subsidies in the US.

  • But it cannot be coincidence that almost all commodity prices rose together during much of the decade, and peaked abruptly in mid-2008.

  • Three theories competed to explain the ascent of commodity prices in 2003-08.

  • Counter-evidence to claims of destabilizing speculation

  • The real interest rate explanation

  • High interest rates

  • Inverse correlation between real interest rate and real commodity price index (DJ, 1950-2008)

  • Counter-argument that applies to both the destabilizing-speculation & easy-money theories (Krugman, 2008, & Kohn, 2008):

  • But in 2008, enthusiasm for theories (2) & (3), the speculation & interest rate theories, rose, at the expense of theory (1), the global boom.

  • Definitions

  • Derive the relationship between q & r from two equations:

  • Combining (2) & (3) gives the relationship:

  • Inverse correlation between real interest rate and real commodity price index (Moody’s, 1950-2008)

  • Translate convenience yield, storage costs, & risk premium from equation (6) into empirically usable form, with 4 or 5 measurable factors:

  • Two more measurable determinants

  • The last two are uncertainy measures

  • Slide 19

  • The equation works for oil inventories: INVENTORIES = Φ -1 (cy - i– (s-f))

  • The same macro variables work to determine real oil price:

  • Complete equation, from (5) and (8):

  • Slide 23

  • Table 3b -- Panel Results, for ln of real commodity prices, with risk included. Annual data.

  • Other tests

  • Overall conclusions (as of now)

  • Possible extensions

  • Appendix

  • Slide 29

  • Slide 30

  • Slide 31

  • Slide 32

  • Slide 33

  • Slide 34

  • Slide 35

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