Transcript Introduction on Energy Policy

Economics of exhaustible resources
Economics 331b
Spring 2011
1
Agenda
Monday: Energy primer
Wednesday: Hubbert curve and Hotelling theories
Thursday pm: Lint will show you how to use spreadsheets and Solver
Friday: snow day
Monday: Hotelling v. Hubbert
Sometime next week: A pset on using spreadsheets and numerical
optimization.
2
Questions about exhaustible resources
1. What is the optimal (efficient) price of the resource?
2. Is it an “essential” resource?
- Question of elasticity of substitution between resource and other
inputs. Is there a backstop technology? At what price?
3. Is the use of the resources “sustainable”?
- This refers to whether net investment in the economy is positive.
- E.g., investment in capital greater than disinvestment in value of
resources
3
McKelvey diagram on resources
4
Two important approaches
Hubbert concerns the Q
Hotelling concerns the P
Can they be married into a happy P-Q couple?
5
Hubbert theory
The Hubbert peak-oil theory posits that for any given
geographical area, from an individual oil-producing
region to the planet as a whole, the rate of petroleum
production tends to follow a bell-shaped (normal) curve.
There is no explicit economics in this approach.
6
Hubbert theory
Qmax = Maximum producible resources
P(t) = production
7
Hubbert curve for US
3,600
US crude oil production
Hubbert curve
Production (barrels/year)
3,200
2,800
2,400
2,000
1,600
1,200
800
(peak 1976; total = 222; cum to date = 197)
400
0
00
10
20
30
40
50
60
70
80
90
Data source: Oil production for EIA. Hubbert curve fit by Nordhaus.
00
10
8
Hotelling theory: Derives the price of an
exhaustible resource
Let’s work through an example
Assume demand = 10 per year (zero price elasticity)
Resources:
100 units of costless oil
unlimited amount of “backstop oil” at $100 per unit
Discount rate = 5 % per year
Questions:
1. What is the efficient allocation over time? Q and P?
2. What would be the market pricing in a competitive market?
3. How do (1) and (2) compare?
9
Solution quantities
12
10
Quantity/year
8
Low cost
Backstop
6
4
2
0
0
5
10
15
Year
20
25
30
10
Solution prices
200
180
160
Price/unit
140
120
100
80
60
Supply price low cost
40
Market price
20
0
0
5
10
15
Year
20
25
30
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Hotelling theory
• Let rt = net price of oil in ground = pt – et
= price of oilt – extraction costt
• Oil is developed and produced to meet the arbitrage
condition for assets:
rt* = market rate of return on assets = ri,j,t = return on oil in the
ground for grade i, location j, time t.
• Note that arbitrage condition holds only when
production is positive (price-quantity duality condition)
12
Real crude oil prices (2010 $ per barrel)
200
100
80
60
50
40
30
20
10
50
55
60
65
70
75
80
85
90
95
00
05
10
Data source: Oil price data from EIA and BLS. Price deflation by CPI from BLS.
13
200
Real oil price
100
80
60
50
40
30
20
10
Hotelling growth at
r = 3% per year
1975
1980
1985
1990
Hotelling line
1995
2000
2005
2010
Real oil price
14
Next step
We next will build a little economic model of the world oil
industry using geological data, demand data, and
solving using numerical optimization.
This will give you a chance to learn numerical
optimization.
15
Why we will learn numerical optimization
1. You will use to build a little economy-climate change
model and optimize your policy.
2. You have learned the theory (Lagrangeans etc.), so let’s
see how it is applied
3. Optimization is extremely widely used in modern
analysis:
- statistics, finance, profit maximization, engineering design,
sustainable systems, marketing, sports, just everywhere!
4. It is fun!
16
Standard Tools for Numerical Optimization in
Economics and Environment
1.
Some kind of Newton’s method.
- Start with system z = g(x). Use trial values until converges (if
you are lucky and live long enough). [For picture, see
http://en.wikipedia.org/wiki/File:NewtonIteration_Ani.gif]
2.
EXCEL “Solver,” which is convenient but has relatively low power.
- I will use this for the Hotelling model. [proprietary version is
better but pricey.]
3.
GAMS software (LP and other) . Has own language, proprietary
software, but very powerful.
- This is used in many economic integrated assessment models of climate
change. GAMS software. Has own language, proprietary software, but
very powerful.
4.
MATLAB and similar.
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