Facebook LinkedIn Instagram Twitter
Shop
Search
Begin New Search
Proceed to Checkout

Search Results for All:
(Showing results 1 to 8 of 8)



Chapter 8 - Applying Construction Lessons to Decommissioning Estimates

Robin Cantor

Year: 1991
Volume: Volume 12
Number: Special Issue
DOI: 10.5547/ISSN0195-6574-EJ-Vol12-NoSI-8
View Abstract

Abstract:
One of the standard practices in estimating costs for new procedures is to apply past experience. In this chapter, Robin Cantor uses prudency hearings and other data from power plant construction to illuminate some of the pitfalls likely to be encountered in preparing estimates for power plant decommissioning. Two of the most tempting pitfalls are scale and learning economies. She suggests that these presumed economies have had less impact on keeping construction costs down than expected, and that they also are unlikely to have much effect on decommissioning costs. Ignoring such evidence, she suggests, could result in decommissioning cost estimates that are too low and collection strategies that are inadequate. This finding has implications for future generations and future decommissioning options.



The Economics of Energy Market Transformation Programs

Richard Duke and Daniel M. Kammen

Year: 1999
Volume: Volume20
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol20-No4-2
View Abstract

Abstract:
This paper evaluates three energy-sector market transformation programs: the U.S. Environmental Protection Agency's Green Lights program to promote on-grid efficient lighting; the World Bank Group's new Photovoltaic Market Transformation Initiative; and the federal grain ethanol subsidy. We develop a benefit-cost model that uses experience curves to estimate unit cost reductions as a function of cumulative production. Accounting for dynamic feedback between the demand response and price reductions from production experience raises the benefit-cost ratio (BCR) of the first two programs substantially. The BCR of the ethanol program, however, is approximately zero, illustrating a technology for which subsidization was not justified. Our results support a broader role for market transformation programs to commercialize new environmentally attractive technologies, but the ethanol experience suggests moderately funding a broad portfolio composed of technologies that meet strict selection criteria.



The Curious Role of "Learning" in Climate Policy: Should We Wait for More Data?

Mort Webster

Year: 2002
Volume: Volume23
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol23-No2-4
View Abstract

Abstract:
Given the large uncertainties regarding potential damages from climate change and the significant but also uncertain costs of reducing greenhouse emissions, the debate over a policy response is often framed as a choice of acting now or waiting until the uncertainty is reduced. Implicit in the "wait to learn" argument is the notion that the ability to learn in the future necessarily implies that less restrictive policies should be chosen in the near term. I demonstrate in the general case that the ability to learn in the future can lead to either less restrictive or more restrictive policies today. I also show that the initial decision made under uncertainty will be affected by future learning only if the actions taken today change the marginal costs or marginal damages in the future. Results from an intermediate-scale integrated model of climate and economics indicate that the choice of current emissions restrictions is independent of whether or not uncertainty is resolved before future decisions, because, like most models, the cross-period interactions are minimal. With stronger interactions, the effect of learning on initial period decisions can be more important.



Technical Change Theory and Learning Curves: Patterns of Progress in Electricity Generation Technologies

Tooraj Jamasb

Year: 2007
Volume: Volume 28
Number: Number 3
DOI: 10.5547/ISSN0195-6574-EJ-Vol28-No3-4
View Abstract

Abstract:
Better understanding of the role of learning in technical progress is important for the development of innovation theory and technology policy. This paper presents a comparative analysis of the effect of learning and technical change in electricity generation technologies. We use simultaneous two-factor learning and diffusion models to estimate the effect of learning by doing and learning by research on technical progress for a range of technologies in four stages of development. We find learning patters broadly in line with the perceived view of technical progress. The results generally show higher learning by research than learning by doing rates. Moreover, we do not find any development stage where learning by doing is stronger than learning by research. We show that simple learning by doing curves overstate the effect of learning in particular for newer technologies. Finally, we find little substitution potential between learning by doing and research for most technologies.



Learning-by-Doing and the Optimal Solar Policy in California

Arthur van Benthem, Kenneth Gillingham and James Sweeney

Year: 2008
Volume: Volume 29
Number: Number 3
DOI: 10.5547/ISSN0195-6574-EJ-Vol29-No3-7
View Abstract

Abstract:
Much policy attention has been given to promote fledgling energy technologies that promise to reduce our reliance on fossil fuels. These policies often aim to correct market failures, such as environmental externalities and learning�by-doing (LBD). We examine the implications of the assumption that LBD exists, quantifying the market failure due to LBD. We develop a model of technological advancement based on LBD and environmental market failures to examine the economically efficient level of subsidies in California�s solar photovoltaic market. Under central-case parameter estimates, including nonappropriable LBD, we find that maximizing net social benefits implies a solar subsidy schedule similar in magnitude to the recently implemented California Solar Initiative. This result holds for a wide range of LBD parameters. However, with no LBD, the subsidies cannot be justified by the environmental externality alone.



Willingness to Pay for a Climate Backstop: Liquid Fuel Producers and Direct CO2 Air Capture

Gregory F. Nemet and Adam R. Brandt

Year: 2012
Volume: Volume 33
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol33-No1-3
View Abstract

Abstract:
We conduct a sensitivity analysis to describe conditions under which liquid fuel producers would fund the development of a climate backstop. We estimate (1) the cost to develop competitively priced direct CO2 air capture technology, a possible climate backstop and (2) the effect of this technology on the value of liquid fuel reserves by country and fuel. Under most assumptions, development costs exceed individual benefits. A particularly robust result is that carbon prices generate large benefits for conventional oil producers--making a climate backstop unappealing for them. Unilateral investment does become more likely under: stringent carbon policy, social discount rates, improved technical outcomes, and high price elasticity of demand for liquid fuels. Early stage investment is inexpensive and could provide a hedge against such developments, particularly for fuels on the margin, such as tar sands and gas-to-liquids. Since only a few entities benefit, free riding is not an important disincentive to investment, although uncertainty about who benefits probably is.

Keywords: Air capture, Backstop technology, Climate policy, Learning by doing, R&D, Unconventional oil



Learning by Doing with Constrained Growth Rates:An Application to Energy Technology Policy

Karsten Neuhoff

Year: 2008
Volume: Volume 29
Number: Special Issue #2
DOI: 10.5547/ISSN0195-6574-EJ-Vol29-NoSI2-9
View Abstract

Abstract:
Learning by doing methodology attributes cost reductions of a technology to cumulative investment and experience. This paper argues that in addition market growth rates must also be considered. Historically growth rates have been limited in most sectors, thus allowing for feedback in the learning process. When market growth is below the optimal rate, the marginal value of additional investment could be a multiple of the direct learning benefit. Analytic and numeric models quantify this impact emphasizing the need for tailored technology policy in addition to carbon pricing. Implications for the modeling of endogenous technological change are discussed.



The Perils of the Learning Model for Modeling Endogenous Technological Change

William D. Nordhaus

Year: 2014
Volume: Volume 35
Number: Number 1
DOI: 10.5547/01956574.35.1.1
View Abstract

Abstract:
Modeling of technological change has been a major empirical and analytical obstacle for many years. One approach to modeling technology is learning or experience curves, which originated in techniques used to estimate cost functions in manufacturing. These have recently been introduced in policy models of energy and climate-change economics to make the process of technological change endogenous - that is, allow technologies to vary with economic conditions. It is not widely appreciated that using learning in modeling raises major potential problems. The present note has three points. First, it shows that there is a fundamental statistical identification problem in trying to separate learning from exogenous technological change and that the estimated learning coefficient will generally be biased upwards. Second, we present two empirical tests that illustrate the potential bias in practice and show that learning parameters are not robust to alternative specifications. Finally, we show that an overestimate of the learning coefficient will provide incorrect estimates of the total marginal cost of output and will therefore bias optimization models to tilt toward technologies that are incorrectly specified as having high learning coefficients. Keywords: Learning by doing, Climate change, Technological change





Begin New Search
Proceed to Checkout

 





function toggleAbstract(id) { alert(id); }