Rare Earth Substitutability in Clean Energy Technology: Using Expert Elicitation to Estimate Elasticities

The Case of Permanent Magnets

Braeton J. Smith and Roderick EggertDivision of Economics and Business

Colorado School of Mines

33rd USAEE/IAEE North American ConferencePittsburgh, PA

October 25-28, 2015

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Clean Energy and Rare Earth Elements

Clean energy technology• Wind• Solar• EVs• Fluorescent

lighting/LEDs

High efficiency technology• Direct drive

motors in wind and EVs

Direct drive motors• Permanent

magnets

Permanent magnets (PMs)• NdFeB• SmCo

Rare earth elements (REEs)• Neodymium• Dysprosium• Praseodymium• Samarium

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Rare Earth Price Spike

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Purpose

• Survey of magnet producer and user responses to rare earth price changes

• Two Purposes:1. Historical - Document and quantify responses during and

following the rare earth (RE) price shock of 2010/20112. Forward Looking - Assess possible future substitution and price

responsiveness

• Estimate price elasticities of demand and substitution of REEs in PMs

• Apply expert elicitation methods to estimate forward-looking elasticities

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Motivation

• Substitutability is a key indicator of material criticality

• Need to know what to expect if price shock happens again – not necessarily the same (non-constant elasticity)– Estimate elasticities not based on historical data

• Substitutability is an important consideration in simulation modeling

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Substitution Taxonomy1. No substitution - “do nothing” (low cost share, technically difficult)

a) Cost pass-through

b) Cost absorption

2. Material Substitution – general characteristics of end product are maintaineda) Element for Element

• Substitute or reduce material content (e.g., reduce Dy content of NdFeB magnet)

b) Alloy for Alloy • Use different, but comparable, grade (e.g., N42SH instead of N45SH)

3. System Substitution – requires reengineering of overall systema) Magnet for Magnet

•Use different magnet type altogether (e.g., SmCo instead of NdFeB)

b) System for System• Use different system altogether (e.g., gearbox vs. direct drive)

4. Increased Manufacturing Efficiency – use materials more efficiently

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• Price elasticity of demand:

• Elasticity of substitution:– Expenditure on good 2 relative to good 1:

– When E21 < 1, c2/c1 falls by less than p2/p1 increases– When E21 > 1, c2/c1 falls by more than p2/p1 increases– When E21 = 1, c2/c1 is independent of relative prices

Price Responsiveness Quantification

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Variables

• Target Variables– Price elasticity of demand (of Dy in a NdFeB

magnet)– Elasticity of substitution (between Dy and Nd in a

NdFeB magnet)• Query Variables– Price and quantity (% composition) combinations– Composition and cost share for given price

changes

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Survey Structure

• Survey divided into 2 parts– Part 1: Historical Substitutability and Price

Responsiveness• Historical questions focus on events during and post RE

price shock– Part 2: Future Substitutability and Price

Responsiveness• Probability elicitation of potential future responses

• Four categories provide framework for survey

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Historical Questions Approach

1. No Substitution:– Sales price change during and after price shock– Cost shares before, during, and after price shock

2. Material Substitution (element for element):– Material composition of magnet before and after price shock

3. Material Substitution (alloy for alloy):– Change in sales and production shares of different grades of

NdFeB magnets during and after price shock4. Increased Mfg. Efficiency: – Reduction in material purchase requirement during and after

price shock

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Historical Anecdotes• No substitution

– Some evidence of cost pass-through in short run, but difficult for non-Chinese producers

– Some evidence of cost absorption• Material substitution

– Evidence of element for element subst. over time for Dy, less so for Nd– Japanese companies reduced Dy content 6-8% (Roskill, 2015)

• System Substitution– No evidence of magnet for magnet substitution for wind technology,

although much research into alternatives to NdFeB– Evidence of System for System subst. in wind technology

• Increased Mfg. Efficiency– Some evidence of recovery and reuse (Roskill, 2015)

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Quantifying Uncertainty• Probability Encoding and Sources of Bias

– “Process of extracting and quantifying individual judgment about uncertain quantities” - Spetzler and Von Holstein (1975)

• Fixed probability (FP) vs. fixed value (FV) (Abbas et al., 2008)• Many applications in natural sciences, risk analysis, and

decision analysis• Applications in economics mainly focus on R&D and

technical breakthrough:– Baker et al. (2009), Baker and Keisler (2011), Anadon et al. (2012), Abdulla et al.

(2013), Catenacci et al. (2013), Nemet et al. (2013), many others

• Quantifying uncertainty around future substitutability is new application

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• Define prototype magnet and market conditions now

• Elicit probabilities using mix of FV and FP methods for each potential response

• Generate probability distribution for each expert and response

Forward Looking Questions Approach

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Example - PrototypeConsider a sintered N45SH neo magnet that is used in a generator for a 2.5 MW wind turbine.

Material Nd (%) Dy (%) Pr (%)N45SH 23% 7% 3.3%

Properties Br HcB HcJ (BH)max TW

Material Typical mT

Typical Gauss

Min kA/m

Min Oersteds

Min kA/m

Min Oersteds

Typical kJ/m3

Typical MGOe Max oC

N45SH 1,350 13,500 979 12,300 1,592 20,000 354 44.0 150

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FV Example – Material Substitution

• If the price of the element in Column 1 were to change by the amount in Column 2, what is the probability that the material composition of the element in Column 5 would change by the amount in Column 6?

• E.g.: If the Dy price were to increase by 50 percent, what is the probability that the Dy content of the N45SH magnet would remain the same?

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Element Price Change

Current Price ($/kg)

Future Price ($/kg)

Change Element

Content Change

Current Content

Future Content

Probability Estimate

Dy +50% $500 $750 Dy 0% 7% 7.00% Dy +50% $500 $750 Dy -5% 7% 6.65% Dy +50% $500 $750 Dy -10% 7% 6.30% Dy +50% $500 $750 Dy -25% 7% 5.25% Dy +50% $500 $750 Dy -50% 7% 3.50%

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FP Example – Material Substitution

• Please give your 10th, 25th, 50th, 75th, and 90th percentile estimates for the amount that the material content of the material in Column 1 would change for the price change indicated in Column 2.

Material Price Change 10th 25th 50th 75th 90th

Dy +50%

Dy +100%

Dy +500%

Dy +1000%

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Thanks!

Questions?

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Hypothetical Result

25 30 35 40 45 50 55 60 65 70 75-0.2

-1.66533453693773E-16

0.2

0.4

0.6

0.8

1

1.2

CDF

25 30 35 40 45 50 55 60 65 70 75-0.004999999999999982.34187669256869E-170.00500000000000002

0.010.015

0.020.025

0.030.035

0.04

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