Modeling Energy and Climate Change Policies:

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Modeling Energy and Climate Change Policies
Characterizing New Policies, Changing Behaviors,
and Technology Returns

• John A. Skip Laitner
• Economic Analysis Director
• American Council for an Energy-Efficient Economy
  (ACEEE)
• NREL Energy Collaborative Analysis Initiative
• Web Forum Modeling Impacts of Policy Options
• May 15, 2008

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Following the Key Modeling Workshop Outcomes,

Would this be true. . . .
Where the Masked Spider standard economic
policy models. . .
and
Bob policymakers
who have just learned that such models reflect
only limited behavioral and technological
responses in their assessments?
Hey, Bob. . . did I scare you or what?
See, http//www.aceee.org/conf/06modeling/
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The Good News About Energy Efficiency Investments
and Climate Change Policies

• It is does not have to be about ratcheting down
  our economy
• Rather, it can be all about
• using innovation and our technological
  leadership
• investing in more productive technologies
  (including both existing and new technologies)
  and
• developing new ways to make things, and new ways
  to get where we want to go, where we want to
  work, and where we want to play.
• But again, most economic models
  appear to assume the former.

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Economics Science Has Not Solved. . . .

• Its first problem namely, what determines the
  price of a commodity? (Robinson 1947)
• Among things that can influence commodity
  prices
• Belief
• Value
• Habit
• Alternatives
• Necessity
• Income
• All of which can be shaped by changed
  perceptions, clear and persistent policy signals,
  as well as new or expanding programs (Brown 2001).

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An Admittedly Simple Heuristic Policy Modeling
Exercise

• Starting from todays prices of 4.00 per gallon
  of gasoline equivalent, suppose we need to reduce
  energy by 25 percent.
• Let us further assume in our policy model that
  there is a price elasticity of -0.25. So if. . .
  .
• Then the new energy price will need to be just
  over 13.26 per gallon equivalent, or 3.2 times
  higher than today.
• Clearly this is not good for the economy and
  most economic policy models indicate exactly that
  kind of bad news to the detriment of smart
  energy and climate policy.
• And while prices matter, they are not all that
  matter!

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A very small difference in assumptions can have a
huge impact in the eventual outcome.
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Comparing Hardware and Energy Costs with Soft
Search and Transaction Costs
Preferences, Perceived Risk Transaction Costs
Impacted by policies, programs, awareness, and by
shifting preferences all roughly approximated
by the hurdle rate or the implicit discount
rate
Information Costs
Search Costs
All areas that can benefit from policy development
Cost or Cost Equivalent
Fuel
Fuel
Impacted by policies, RD programs, experience,
growing expectations, and new innovations
Capital
Capital
Standard Technology
Efficiency Technology
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Suppose, Now, We Have an Integrated
Technology-Behavior Policy Model

• That instead of a simple (probably invariant)
  price elasticity, we employ a substitution
  elasticity which allows a more productive use of
  capital to displace the inefficient use of
  energy and
• That combines shifts in awareness, preferences,
  and norms as they motivate the production and the
  adoption of improved technology all in response
  to some changed circumstance, or some combination
  of prices and other policy signals.

Where productive capital implies a greater than
average return on investment
See, http//www.aceee.org/conf/06modeling/
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The Maryland Example for Electricity
Collectively, a 29 reduction
. . . .a 29 reduction in conventional resources
driven by 3.4 billion in program spending, a
9.3 billion efficiency investment, displacing
the need for 3.9 billion in MD utility
investments, and all of which saves consumers
21 billion in avoided energy bills over the
period 2008 through 2025
And, oh yes, generates a small but net positive
gain in GSP as well as 12,000 net new jobs by
2025
Source "Energy Efficiency the First Fuel for a
Clean Energy Future Resources for Meeting
Marylands Electricity Needs," ACEEE 2008
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With Now Three Critical Differences Integrated
into Our Policy Model

• First, we enable a more productive technology to
  substitute for inefficient use of energy
• Second, we allow for a shift in preferences and
  behavior which motivate the development,
  production, and adoption of that technology
• Finally, rather than an assumed inflationary cost
  we now have a return on investment
• All of which provides for a more satisfying
  modeling result that, in turn, might encourage
  the adoption of a smart energy and/or climate
  change policy

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A Selected Modeling and Technology
Characterization Bibliography

• Elliott, R. Neal, Therese Langer, and Steven
  Nadel. 2006. Reducing Oil Use through Energy
  Efficiency Opportunities Beyond Cars and Light
  Trucks, Washington, DC American Council for an
  Energy Efficient Economy, January.
• Elliott, R. Neal and Shipley, Anna Monis.
  "Impacts of Energy Efficiency and Renewable
  Energy on Natural Gas Markets Updated and
  Expanded Analysis," Washington, DC American
  Council for an Energy Efficient Economy, 2005.
• Geller, Howard, Philip Harrington, Arthur H.
  Rosenfeld, Satoshi Tanishima, and Fridtjof
  Unander. Polices for increasing energy
  efficiency Thirty years of experience in OECD
  countries, Energy Policy, 34 (2006) 556573.
• Koomey, Jonathan G., Paul Craig, Ashok Gadgil,
  and David Lorenzetti. 2003. Improving long-range
  energy modeling A plea for historical
  retrospectives. The Energy Journal, vol. 24, no.
  4. October. pp. 75-92.
• Laitner, John A. "Skip and Donald A. Hanson.
  2006. Modeling Detailed Energy-Efficiency
  Technologies and Technology Policies within a CGE
  Framework, Energy Journal, Hybrid Modelling New
  Answers to Old Challenges.
• Laitner, John A. "Skip" and Alan H. Sanstad.
  2004. "Learning by Doing on Both the Demand and
  the Supply Sides Implications for Electric
  Utility Investments in a Heuristic Model."
  International Journal of Energy Technology and
  Policy, 2004, 2(1/2), pp. 142-152.
• Laitner, John A. "Skip. 2004. How Far Energy
  Efficiency? Proceedings of the 2004 ACEEE Summer
  Study on Energy Efficiency in Buildings.
  Washington, DC American Council for an Energy
  Efficient Economy.
• Laitner, John A. "Skip", Donald A. Hanson, Irving
  Mintzer, and Amber J. Leonard. 2005. Adapting
  in Uncertain Times A Scenario Analysis of U.S.
  Energy and Technology Futures. Energy Studies
  Review, Vol. 14, No.1, 2005 pp120-135.
• Laitner, John A., Stephen J. DeCanio, Jonathan G.
  Koomey, and Alan H. Sanstad. 2003. Room for
  Improvement Increasing the Value of Energy
  Modeling for Policy Analysis. Utilities Policy,
  11, pp. 87-94.
• Martin, Nathan, et al. 2000. "Emerging
  Energy-Efficient Industrial Technologies,"
  Washington, DC American Council for an Energy
  Efficient Economy, 2000.
• Sachs, Harvey et al. 2004. Emerging
  Energy-Saving Technologies and Practices for the
  Buildings Sector, Washington,
  DC American Council for an Energy Efficient
  Economy, 2004.
• Shipley, Anna Monis and R. Neal Elliott. 2006.
  Ripe for the Picking Have We Exhausted
  the Low-Hanging Fruit in
  the Industrial Sector? Washington, DC American
  Council for an
  Energy-Efficient Economy, April.

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The difficulty lies not with the new ideas, but
in escaping the old ones
John Maynard Keynes
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Contact Information
John A. Skip Laitner Director of Economic
Analysis American Council for an Energy-Efficient
Economy (ACEEE) 4372 Shooting Star Drive Island
Lake, IL 60042 [phone] jslaitner_at_aceee.org
For more information and updates
visit http//www.aceee.org