This paper utilizes instrumental variables and joint estimation to construct efficiently identified estimates of supply and demand equations for the world iron ore market under the assumption of perfect competition

With annual data spanning 1960-2010, I found an upward sloping supply curve and a downward sloping demand curve. Both of the supply and demand curves are efficiently identified using a 3SLS model. The instruments chosen are strong and credible. Point estimation of the long-run price elasticities of supply and demand are 0.45 and -0.24 respectively, indicating inelastic supply and demand market dynamics

Back-tests and forecasts were done with Monte Carlo simulations. The results indicate that 1) the predicted prices are consistent with the historical prices, 2) world GDP growth rate is the determining factor in the forecasting of iron ore prices

GLOBAL IRON ORE INDUSTRY GLOBAL IRON ORE INDUSTRY

ABSTRACT ABSTRACT

Identifying Supply and Demand Elasticities of Identifying Supply and Demand Elasticities of Iron OreIron Ore

Author: Zhirui Zhu, Faculty Advisor: Professor Gale A Boyd

Annual Supply and Demand using Iron Ore Production for Quantity

OLS 2SLS 3SLSWd Ore Pd Wd Ore Pd Wd Ore Pd

Demand FunctionOre Price (t) -0.0693 -0.463 -0.928***

(-0.61) (-1.71) (-4.33)

Scrap Price 0.0612 0.0811 0.0910**

(1.57) (1.77) (2.66)

Demand Shock05 0.464*** 0.608*** 0.744***

(6.21) (5.01) (7.65)

Wd GDP 0.435*** 0.419*** 0.404***

(12.62) (10.42) (11.69)

Ore Price (t-1) 0.0917 0.353 0.688***

(0.99) (1.86) (4.45)

Constant 9.039*** 9.894*** 10.76***

(8.54) (7.56) (9.77)R2 0.95 0.93 0.88

Supply Function Ore Price (t) 0.322** 0.601*** 0.900***

(3.22) (3.88) (6.84)

Interest Rate -0.0418* -0.0410 -0.0122(-2.02) (-1.81) (-0.82)

Time 0.0261*** 0.0247*** 0.0231***

(16.81) (13.77) (15.11)

Supply Shock -0.175*** -0.148* -0.138**

(-3.36) (-2.56) (-2.99)

Ore Price (t-1) 0.0680 -0.190 -0.450***

(0.67) (-1.26) (-3.48)

Constant 18.76*** 18.69*** 18.48***

(93.55) (84.84) (97.84)R2 0.94 0.93 0.89

Durbin–Watson 1.04 1.54 1.94

N 47 47 47

Effect of instruments on annual iron ore price

OLS OLS-Demand

OLS-Supply

Ore Price (t)

Ore Price (t)

Ore Price (t)

Ore Price (t-1) 0.479*** 0.653*** 0.923***

(5.06) (6.85) (8.13)

Demand ShiftersScrap Price 0.0572 0.0609

(1.15) (1.21)

Wd GDP 0.206 -0.0504(1.24) (-1.30)

Demand Shock05 0.600*** 0.366***

(6.24) (3.80)

P-value for all demand shifters

0.000***

Supply Shifters

Time -0.0171** 0.00523

(-2.90) (1.60)

Interest Rate -0.00538 -0.00295(-0.32) (-0.16)

Supply Shock 0.172* -0.0959(2.18) (-1.45)

P-value for all supply shifters 0.0034**

Constant -3.240 2.492 0.231(-0.76) (1.96) (0.51)

N 47 48 47P-value from joint test of all coefficients (Prob > F)

0.00*** 0.00*** 0.00***

adj. R2 0.90 0.82 0.81

Fig 2 Iron Ore Imports by CountryFig 1 Iron Ore Pricing Diagram

The current iron ore trade market is dominated by the Big Three - Vale, Rio Tinto and BHP Billiton. Three companies control about 70% of the seaborne market in 2010

In 1970’s, European steelmakers determined the market demand with the Japanese buyers taking over in the 80’s and 90’s. In the 2000’s, Chinese steelmakers started to play a dominant role in the buyer’s market

Since post-World War II, iron ore prices had been decided behind closed doors in negotiations between mining companies and steelmakers

In 2004, Chinese steelmakers obtained the right to negotiate the ironstone benchmark price for the first time. However the benchmark price was mainly settled between the Big Three and the Japanese steelmakers. Meanwhile, the global ore import price from 2004 to 2008 had increased 18%, 71%, 20%, 9% and 96% respectively

The iron ore annual pricing system officially ended in 2010 and moved to a spot market system

METHODS & DATAMETHODS & DATA

Supply and Demand Structural Equations 

Demand: ln (QtD) = β0 + β1 ln(Pt) + β2 ln (Pt-1) +β3 ln (Scrap Pricet) + β4 Demand Shockt + β5 ln (GDPt) + μ

Supply: ln (QtS ) = γ0 + γ1 ln (Pt) + γ2 ln (Pt-1) + γ3 ln (Interest Ratet) + γ4 Timet + γ5 Supply Shockt + ν

Market Clearing: QtD = QtS

Instruments SelectionFig 3 World iron ore price and production, U.S. scrap price, world GDP, China iron ore imports and U.S. real interest rate plots (1962 – 20010)

RESULTS - BACK TESTING (1962-RESULTS - BACK TESTING (1962-2010)2010)

RESULTS – OLS, 2SLS, 3SLSRESULTS – OLS, 2SLS, 3SLS

Price elasticities of supply and demand

Coef. S.D. Z

Demand β1+β2 -0.241** 0.090 -2.68

Supply γ1+γ2 0.450*** 0.045 9.93

CONCLUSTIONCONCLUSTION

RESULTS – FORECASTS (2011-RESULTS – FORECASTS (2011-2020)2020)

Covariates Sensitivity Tests

Fig 4 Iron ore price and predicted prices, quantities and predicted quantities (1962-2010)

Fig 5 Covariates sensitivity tests (1962-2010) 3SLS yields efficient and consistent coefficient estimatorsThe annual model indicates that the long-run iron ore supply curve appears to be upward sloping while the long-run demand curve for iron ore appears to be downward slopingThe simulation results indicate that the annual model captures most of the historical price fluctuations