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Transcript of This paper utilizes instrumental variables and joint estimation to construct efficiently identified...
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 3SLS
Wd Ore Pd Wd Ore Pd Wd Ore PdDemand 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 0.88Supply 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 0.89Durbin–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