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The Energy Crisis and Macroeconomic Policy

William D. Nordhaus

Year: 1980
Volume: Volume 1
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol1-No1-2
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Abstract:
It is hard to find an issue more confusing than energy policy. Is there a shortage of oil? Why? How long will the shortages last? Who's to blame? What will be the supply and demand response to price decontrol? What are the appropriate policy responses today? Can the president or the secretary of energy or the Congress be trusted to find the answers? And so on.



The Cost of Slowing Climate Change: a Survey

William D. Nordhaus

Year: 1991
Volume: Volume 12
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol12-No1-4
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Abstract:
Policies to deal effectively and efficiently with the threat of greenhouse warming must balance the costs of slowing climate change against the potential damages. This survey discusses one half of this question, the costs of slowing climate change by reducing greenhouse gas (GHG) emissions. The analysis provides estimates of the cost of reducing chlorofluorocarbon and CO2 emissions, and inquires into the costs of using forestry options to remove CO2 from the atmosphere. A promising new approach, the use ofgeoengineering, is discussed qualitatively.



What is the Value of Scientific Knowledge? An Application to Global Warming Using the PRICE Model

William D. Nordhaus and David Popp

Year: 1997
Volume: Volume18
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol18-No1-1
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Abstract:
Governments must cope with the enormous uncertainties about both future climate change as well as the costs and benefits of slowing climate change. This study analyses the value of improved information about a variety of geophysical and economic processes. The value of information is estimated using the "PRICE model" which is a probabilistic extension of earlier models of the economics of global warming. The study uses five different approaches to estimating the value of information about all uncertain parameters and about individual parameters. It is estimated that the value of early information is between $1 and $2 billion for each year that resolution of uncertainty is moved toward the present. We estimate that the most important uncertain variables are the damages of climate change and the costs of reducing greenhouse gas emissions. Resolving the uncertainties about these two parameters would contribute 75 percent of the value of improved knowledge.



Requiem for Kyoto: An Economic Analysis of the Kyoto Protocol

William D. Nordhaus and Joseph G. Boyer

Year: 1999
Volume: Volume 20
Number: Special Issue - The Cost of the Kyoto Protocol: A Multi-Model Evaluation
DOI: 10.5547/ISSN0195-6574-EJ-Vol20-NoSI-5
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Abstract:
This paper uses the newly developed RICE-98 model to analyze the economics of the Kyoto Protocol. It analyzes versions of the Kyoto Protocol that have different approaches to trading emissions rights and compares these with efficient approaches. The major conclusions are: (a) the net global cost of the Kyoto Protocol is $716 billion in present value, (b) the United States bears almost two thirds of the global cost; and (c) the benefit-cost ratio of the Kyoto Protocol is 1/7. Additionally, the emissions strategy is highly cost-ineffective, with the global temperature reduction achieved at a cost almost 8 times the cost of a strategy which is cost-effective in terms of "where" and "when" efficiency. These conclusions assume that trading in carbon permits is allowed among the Annex I countries.



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
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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





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