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| Publications of Richard G. Newell :chronological alphabetical combined listing:
%% Books
@book{fds267080,
Author = {Henderson, RM and Newell, RG},
Title = {Accelerating Energy Innovation Insights from Multiple
Sectors},
Pages = {274 pages},
Publisher = {University of Chicago Press},
Year = {2011},
Month = {May},
ISBN = {0226326837},
Abstract = {2010. International energy outlook2010. No.
DOE/EIA-0484(2010). Washington, DC: Energy Information
Administration. Gallagher, Kelly Sims, John P. Holdren, and
Ambuj D. Sagar. 2006. Energy- technology innovation. Annual
Review of ...},
Key = {fds267080}
}
@book{fds267078,
Author = {Newell, RG and Henderson, RM},
Title = {Accelerating Energy Innovation: Insights from Multiple
Sectors},
Year = {2009},
Month = {December},
Abstract = {Accelerating the rate of innovation in energy is a critical
component of any effective response to the threat of climate
change. This book is designed to contribute to the debate as
to how this can best be done through a focus on the history
of four sectors of the US economy that have historically
seen very rapid increases in the rate of innovation:
agriculture, chemicals, life sciences, and information
technology. In a sequence of seven chapters leading experts
in the history of innovation in each sector explore the role
that public and private policy has played in enabling
accelerated innovation. Together they highlight the ways in
which effective public policy in highly innovative sectors
has been integrated (albeit rarely by design) into a complex
innovation system that includes three critical elements: (1)
substantial, differentiated, end-user demand that enables
private firms commercializing the technology to anticipate
healthy returns; (2) the sustained funding and effective
management of fundamental research; and (3) the development
of an institutional environment that includes robust
mechanisms to promote the widespread diffusion of both
knowledge and technology and that favors vigorous
private-sector competition.},
Key = {fds267078}
}
%% Book Chapters
@misc{fds171210,
Author = {Henderson, R.H and R.G. Newell},
Title = {Accelerating Innovation in Energy: Insights from Multiple
Sectors. Introduction and Summary},
Year = {2011},
Key = {fds171210}
}
@misc{fds171211,
Author = {R.G. Newell},
Title = {The Energy Innovation System: A Historical
Perspective},
Booktitle = {Accelerating Innovation in Energy: Insights from Multiple
Sectors (R.H. Henderson and R.G. Newell,
eds)},
Year = {2009},
Key = {fds171211}
}
@misc{fds152186,
Author = {Jaffe, A.B. and R.G. Newell and R.N. Stavins},
Title = {Technological change and the environment},
Volume = {1},
Series = {Handbooks in Economics series},
Pages = {461-516},
Booktitle = {Handbook of Environmental Economics},
Publisher = {Amsterdam: North-Holland/Elsevier},
Editor = {K.-G. Mäler and J. Vincent},
Year = {2003},
Key = {fds152186}
}
@misc{fds60875,
Author = {Newell, R.G. and A.B. Jaffe and R.N. Stavins},
Title = {The Induced Innovation Hypothesis and Energy-Saving
Technological Change},
Pages = {97-126},
Booktitle = {Technological Change and the Environment},
Publisher = {RFF Press, Washington, DC},
Editor = {A. Grubler and N. Nakicenovic and W.D. Nordhaus},
Year = {2002},
url = {http://www.nicholas.duke.edu/people/faculty/newell/RFFbookch05-newell.pdf},
Key = {fds60875}
}
%% Chapters in Books
@misc{fds332954,
Author = {Huang, B and Knox, M and Bradbury, K and Collins, LM and Newell,
RG},
Title = {Non-intrusive load monitoring system performance over a
range of low frequency sampling rates},
Journal = {2017 6th International Conference on Renewable Energy
Research and Applications, Icrera 2017},
Volume = {2017-January},
Pages = {505-509},
Publisher = {IEEE},
Year = {2017},
Month = {December},
ISBN = {9781538620953},
url = {http://dx.doi.org/10.1109/ICRERA.2017.8191111},
Abstract = {Non-intrusive load monitoring (NILM) systems estimate the
amount of energy each appliance consumes using as input the
aggregate building energy consumption. Typically, NILM
results are presented for a single sampling rate. To
evaluate tradeoffs between end-uses and sensor costs, it is
important to study the performance of NILM systems across
sampling rates. In this work, we examine the performance of
two NILM systems over a range of low frequency sampling
rates on two datasets. Our results empirically demonstrate
how NILM classification performance degrades nonlinearly as
the sampling rate decreases and how varied this degradation
is across appliance types. The results also suggest that
reporting algorithm accuracy for a single sampling rate may
not be sufficient for thorough algorithm performance
evaluation. These findings can assist policy and decision
makers in identifying the right smart meter hardware to meet
appliance-level energy efficiency and building automation
goals.},
Doi = {10.1109/ICRERA.2017.8191111},
Key = {fds332954}
}
@misc{fds330724,
Author = {Malof, JM and Bradbury, K and Collins, LM and Newell, RG and Serrano, A and Wu, H and Keene, S},
Title = {Image features for pixel-wise detection of solar
photovoltaic arrays in aerial imagery using a random forest
classifier},
Journal = {2016 Ieee International Conference on Renewable Energy
Research and Applications, Icrera 2016},
Pages = {799-803},
Publisher = {IEEE},
Year = {2017},
Month = {March},
ISBN = {9781509033881},
url = {http://dx.doi.org/10.1109/ICRERA.2016.7884446},
Abstract = {Power generation from distributed solar photovoltaic (PV)
arrays has grown rapidly in recent years. As a result, there
is interest in collecting information about the quantity,
power capacity, and energy generated by such arrays; and to
do so over small geo-spatial regions (e.g., counties,
cities, or even smaller regions). Unfortunately, existing
sources of such information are dispersed, limited in
geospatial resolution, and otherwise incomplete or
publically unavailable. As result, we recently proposed a
new approach for collecting such distributed PV information
that relies on computer algorithms to automatically detect
PV arrays in high resolution aerial imagery [1], Here, we
build on this work by investigating a detection algorithm
based on a Random Forest (RF) classifier, and we consider
its detection performance using several different sets of
image features. The proposed method is developed and tested
using a very large collection of publicly available [2]
aerial imagery, covering 112.5 km2 of surface area, with
2,328 manually annotated PV array locations. The results
indicate that a combination of local color and texture
(using the popular texton feature) features yield the best
detection performance.},
Doi = {10.1109/ICRERA.2016.7884446},
Key = {fds330724}
}
@misc{fds330726,
Author = {Czarnek, N and Morton, K and Collins, L and Newell, R and Bradbury,
K},
Title = {Performance comparison framework for energy disaggregation
systems},
Journal = {2015 Ieee International Conference on Smart Grid
Communications, Smartgridcomm 2015},
Pages = {446-452},
Publisher = {IEEE},
Year = {2016},
Month = {March},
ISBN = {9781467382892},
url = {http://dx.doi.org/10.1109/SmartGridComm.2015.7436341},
Abstract = {Energy disaggregation algorithms decompose building-level
energy data into device-level information. We conduct a
head-To-head comparison of energy disaggregation techniques
across multiple metrics and data sets. Our framework for
analyzing the performance of a complete energy
disaggregation system includes event detection,
classification, and power assignment. We use receiver
operating characteristics (ROCs) to evaluate event detection
performance, and we introduce a technique to evaluate
device-level event detection. We use confusion matrices to
compare classification performance across several
classifiers, and evaluate the resulting power assignments
using several assignment metrics that are commonly used in
the literature to demonstrate the varying strengths of the
techniques that were considered. We apply this framework to
several publicly available datasets and demonstrate how
system performance varies with sampling frequency and the
inclusion of reactive power. Our results suggest that (1)
disaggregation performance varies considerably across data
sets (2) increased data sampling rate improves
disaggregation performance, and (3) additional features such
as reactive power yields disaggregation performance
improvements.},
Doi = {10.1109/SmartGridComm.2015.7436341},
Key = {fds330726}
}
@misc{fds330727,
Author = {Malof, JM and Collins, LM and Bradbury, K and Newell,
RG},
Title = {A deep convolutional neural network and a random forest
classifier for solar photovoltaic array detection in aerial
imagery},
Journal = {2016 Ieee International Conference on Renewable Energy
Research and Applications, Icrera 2016},
Pages = {650-654},
Publisher = {IEEE},
Year = {2016},
Month = {January},
ISBN = {9781509033881},
url = {http://dx.doi.org/10.1109/ICRERA.2016.7884415},
Abstract = {Power generation from distributed solar photovoltaic PV
arrays has grown rapidly in recent years. As a result, there
is interest in collecting information about the quantity,
power capacity, and energy generated by such arrays; and to
do so over small geo-spatial regions (e.g., counties,
cities, or even smaller regions). Unfortunately, existing
sources of such information are dispersed, limited in
geospatial resolution, and otherwise incomplete or
publically unavailable. As result, we recently proposed a
new approach for collecting such distributed PV information
that relies on computer algorithms to automatically detect
PV arrays in high resolution aerial imagery [1], Here we
build on this work by investigating two machine learning
algorithms for PV array detection: a Random Forest
classifier (RF) [2] and a deep convolutional neural network
(CNN) [3]. We use the RF algorithm as a benchmark, or
baseline, for comparison with a CNN model. The two models
are developed and tested using a large collection of
publicly available [4] aerial imagery, covering 135 km2, and
including over 2,700 manually annotated distributed PV array
locations. The results indicate that the CNN substantially
improves over the RF. The CNN is capable of excellent
performance, detecting nearly 80% of true panels with a
precision measure of 72%.},
Doi = {10.1109/ICRERA.2016.7884415},
Key = {fds330727}
}
@misc{fds330339,
Author = {Malof, JM and Hou, R and Collins, LM and Bradbury, K and Newell,
R},
Title = {Automatic solar photovoltaic panel detection in satellite
imagery},
Journal = {2015 International Conference on Renewable Energy Research
and Applications, Icrera 2015},
Pages = {1428-1431},
Year = {2015},
Month = {January},
ISBN = {9781479999828},
url = {http://dx.doi.org/10.1109/ICRERA.2015.7418643},
Abstract = {The quantity of rooftop solar photovoltaic (PV)
installations has grown rapidly in the US in recent years.
There is a strong interest among decision makers in
obtaining high quality information about rooftop PV, such as
the locations, power capacity, and energy production of
existing rooftop PV installations. Solar PV installations
are typically connected directly to local power distribution
grids, and therefore it is important for the reliable
integration of solar energy to have information at high
geospatial resolutions: by county, zip code, or even by
neighborhood. Unfortunately, traditional means of obtaining
this information, such as surveys and utility
interconnection filings, are limited in availability and
geospatial resolution. In this work a new approach is
investigated where a computer vision algorithm is used to
detect rooftop PV installations in high resolution color
satellite imagery and aerial photography. It may then be
possible to use the identified PV images to estimate power
capacity and energy production for each array of panels,
yielding a fast, scalable, and inexpensive method to obtain
rooftop PV estimates for regions of any size. The aim of
this work is to investigate the feasibility of the first
step of the proposed approach: detecting rooftop PV in
satellite imagery. Towards this goal, a collection of
satellite rooftop images is used to develop and evaluate a
detection algorithm. The results show excellent detection
performance on the testing dataset and that, with further
development, the proposed approach may be an effective
solution for fast and scalable rooftop PV information
collection.},
Doi = {10.1109/ICRERA.2015.7418643},
Key = {fds330339}
}
%% Articles
@article{fds365722,
Author = {Rennert, K and Errickson, F and Prest, BC and Rennels, L and Newell, RG and Pizer, W and Kingdon, C and Wingenroth, J and Cooke, R and Parthum, B and Smith, D and Cromar, K and Diaz, D and Moore, FC and Müller, UK and Plevin, RJ and Raftery, AE and Ševčíková, H and Sheets, H and Stock,
JH and Tan, T and Watson, M and Wong, TE and Anthoff,
D},
Title = {Comprehensive evidence implies a higher social cost of
CO2.},
Journal = {Nature},
Volume = {610},
Number = {7933},
Pages = {687-692},
Publisher = {Springer Science and Business Media LLC},
Year = {2022},
Month = {October},
url = {http://dx.doi.org/10.1038/s41586-022-05224-9},
Abstract = {The social cost of carbon dioxide (SC-CO<sub>2</sub>)
measures the monetized value of the damages to society
caused by an incremental metric tonne of CO<sub>2</sub>
emissions and is a key metric informing climate policy. Used
by governments and other decision-makers in benefit-cost
analysis for over a decade, SC-CO<sub>2</sub> estimates draw
on climate science, economics, demography and other
disciplines. However, a 2017 report by the US National
Academies of Sciences, Engineering, and Medicine<sup>1</sup>
(NASEM) highlighted that current SC-CO<sub>2</sub> estimates
no longer reflect the latest research. The report provided a
series of recommendations for improving the scientific
basis, transparency and uncertainty characterization of
SC-CO<sub>2</sub> estimates. Here we show that improved
probabilistic socioeconomic projections, climate models,
damage functions, and discounting methods that collectively
reflect theoretically consistent valuation of risk,
substantially increase estimates of the SC-CO<sub>2</sub>.
Our preferred mean SC-CO<sub>2</sub> estimate is $185 per
tonne of CO<sub>2</sub> ($44-$413 per tCO<sub>2</sub>:
5%-95% range, 2020 US dollars) at a near-term risk-free
discount rate of 2%, a value 3.6 times higher than the US
government's current value of $51 per tCO<sub>2</sub>. Our
estimates incorporate updated scientific understanding
throughout all components of SC-CO<sub>2</sub> estimation in
the new open-source Greenhouse Gas Impact Value Estimator
(GIVE) model, in a manner fully responsive to the near-term
NASEM recommendations. Our higher SC-CO<sub>2</sub> values,
compared with estimates currently used in policy evaluation,
substantially increase the estimated benefits of greenhouse
gas mitigation and thereby increase the expected net
benefits of more stringent climate policies.},
Doi = {10.1038/s41586-022-05224-9},
Key = {fds365722}
}
@article{fds365158,
Author = {Newell, RG and Pizer, WA and Prest, BC},
Title = {A discounting rule for the social cost of
carbon},
Journal = {Journal of the Association of Environmental and Resource
Economists},
Volume = {9},
Number = {5},
Pages = {1017-1046},
Year = {2022},
Month = {September},
url = {http://dx.doi.org/10.1086/718145},
Abstract = {We develop a discounting rule for estimating the social cost
of carbon (SCC) given uncertain economic growth. Diminishing
marginal utility of income implies a relationship between
the discount rate term structure and economic growth
uncertainty. In the classic Ramsey framework, this
relationship is governed by parameters reflecting pure time
preference and the elasticity of the marginal utility of
consumption, yet disagreement remains about the values of
these parameters. We calibrate these parameters to match
empirical evidence on both the future interest rate term
structure and economic growth uncertainty, while also
maintaining consistency with discount rates used for
shorter-term benefit-cost analysis. Such an integrated
approach is crucial amid growth uncertainty, where growth is
also a key determinant of climate damages. This results in
an empirically driven, stochastic discounting rule to be
used in estimating the SCC that also accounts for the
correlation between climate damage estimates and discount
rates.},
Doi = {10.1086/718145},
Key = {fds365158}
}
@article{fds364287,
Author = {Rennert, K and Prest, BC and Pizer, WA and Newell, RG and Anthoff, D and Kingdon, C and Rennels, L and Cooke, R and Raftery, AE and Ševčíková, H and Errickson, F},
Title = {The Social Cost of Carbon: Advances in Long-Term
Probabilistic Projections of Population, GDP, Emissions, and
Discount Rates},
Journal = {Brookings Papers on Economic Activity},
Volume = {2021-Fall},
Pages = {223-305},
Year = {2021},
Month = {September},
url = {http://dx.doi.org/10.1353/eca.2022.0003},
Abstract = {The social cost of carbon (SCC) is a crucial metric for
inform-ing climate policy, most notably for guiding climate
regulations issued by the US government. Characterization of
uncertainty and transparency of assump-tions are critical
for supporting such an influential metric. Challenges
inherent to SCC estimation push the boundaries of typical
analytical techniques and require augmented approaches to
assess uncertainty, raising important considerations for
discounting. This paper addresses the challenges of
projecting very long-term economic growth, population, and
greenhouse gas emissions, as well as cali-bration of
discounting parameters for consistency with those
projections. Our work improves on alternative approaches,
such as nonprobabilistic scenarios and constant discounting,
that have been used by the government but do not fully
characterize the uncertainty distribution of fully
probabilistic model input data or corresponding SCC estimate
outputs. Incorporating the full range of economic
uncertainty in the social cost of carbon underscores the
importance of adopting a stochastic discounting approach to
account for uncertainty in an integrated
manner.},
Doi = {10.1353/eca.2022.0003},
Key = {fds364287}
}
@article{fds356873,
Author = {Newell, RG and Prest, BC and Sexton, SE},
Title = {The GDP-Temperature relationship: Implications for climate
change damages},
Journal = {Journal of Environmental Economics and Management},
Volume = {108},
Year = {2021},
Month = {July},
url = {http://dx.doi.org/10.1016/j.jeem.2021.102445},
Abstract = {Econometric models of temperature impacts on GDP are
increasingly used to inform global warming damage
assessments. But theory does not prescribe estimable forms
of this relationship. By estimating 800 plausible
specifications of the temperature-GDP relationship, we
demonstrate that a wide variety of models are statistically
indistinguishable in their out-of-sample performance,
including models that exclude any temperature effect. This
full set of models, however, implies a wide range of climate
change impacts by 2100, yielding considerable model
uncertainty. The uncertainty is greatest for models that
specify effects of temperature on GDP growth that accumulate
over time; the 95% confidence interval that accounts for
both sampling and model uncertainty across the
best-performing models ranges from 84% GDP losses to 359%
gains. Models of GDP levels effects yield a much narrower
distribution of GDP impacts centered around 1–3% losses,
consistent with damage functions of major integrated
assessment models. Further, models that incorporate lagged
temperature effects are indicative of impacts on GDP levels
rather than GDP growth. We identify statistically
significant marginal effects of temperature on poor country
GDP and agricultural production, but not rich country GDP,
non-agricultural production, or GDP growth.},
Doi = {10.1016/j.jeem.2021.102445},
Key = {fds356873}
}
@article{fds342154,
Author = {Newell, RG and Pizer, WA and Raimi, D},
Title = {U.S. federal government subsidies for clean energy: Design
choices and implications},
Journal = {Energy Economics},
Volume = {80},
Pages = {831-841},
Year = {2019},
Month = {May},
url = {http://dx.doi.org/10.1016/j.eneco.2019.02.018},
Abstract = {Subsidies for clean energy deployment have become a major
component of U.S. federal energy and climate policy. After a
surge in spending under the American Recovery and
Reinvestment Act of 2009, they are an even larger component
but now face increased scrutiny. Given their lasting
presence, how does one design these subsidies to be as
cost-effective as possible? Surprisingly, the conceptual
framework and empirical evidence available to help
policymakers identify which subsidies generate the most
“bang for the buck” are limited. To help answer this
question, we begin with an overview of the justifications
for, and the arguments against, subsidizing clean energy
technologies. Next, we briefly describe major subsidies.
Finally, we summarize key design choices, suggesting an
increased focus on upfront cash payments for physical
outcomes such as capacity. This contrasts with the
considerable focus on tax credits, loan guarantees,
production, and cost-based subsidies which have been more
prominent to date.},
Doi = {10.1016/j.eneco.2019.02.018},
Key = {fds342154}
}
@article{fds330725,
Author = {Cao, J and Ho, MS and Li, Y and Newell, RG and Pizer,
WA},
Title = {Chinese residential electricity consumption: Estimation and
forecast using micro-data},
Journal = {Resource and Energy Economics},
Volume = {56},
Pages = {6-27},
Publisher = {Elsevier BV},
Year = {2019},
Month = {May},
url = {http://dx.doi.org/10.1016/j.reseneeco.2017.10.003},
Abstract = {Based on econometric estimation using data from the Chinese
Urban Household Survey, we develop a preferred forecast
range of 85–143 percent growth in residential per capita
electricity demand over 2009–2025. Our analysis suggests
that per capita income growth drives a 43% increase, with
the remainder due to an unexplained time trend. Roughly
one-third of the income-driven demand comes from increases
in the stock of specific major appliances, particularly AC
units. The other two-thirds comes from non-specific sources
of income-driven growth and is based on an estimated income
elasticity that falls from 0.28 to 0.11 as income rises.
While the stock of refrigerators is not projected to
increase, we find that they contribute nearly 20 percent of
household electricity demand. Alternative plausible time
trend assumptions are responsible for the wide range of
85–143 percent. Meanwhile we estimate a price elasticity
of demand of −0.7. These estimates point to carbon pricing
and appliance efficiency policies that could substantially
reduce demand.},
Doi = {10.1016/j.reseneeco.2017.10.003},
Key = {fds330725}
}
@article{fds333902,
Author = {Newell, RG and Prest, BC},
Title = {The unconventional oil supply boom: Aggregate price response
from microdata},
Journal = {The Energy Journal},
Volume = {40},
Number = {3},
Pages = {1-30},
Publisher = {International Association for Energy Economics
(IAEE)},
Year = {2019},
Month = {January},
url = {http://dx.doi.org/10.5547/01956574.40.3.rnew},
Abstract = {We analyze the price responsiveness of U.S. conventional and
unconventional oil supply across three key stages of oil
production: Drilling, completion, and production. Drilling
is the most important margin, with price elasticities of 1.3
and 1.6 for conventional and unconventional drilling
respectively. Well productivity declines as prices rise,
implying smaller net supply elasticities of about 1.1 and
1.2. Despite similar supply elasticities, the price response
of unconventional supply is larger in terms of barrels
because of much higher production per well (∼10x
initially). Oil supply simulations show a 13-fold larger
supply response due to the shale revolution. The simulations
suggest that a price rise from $50 to $80 per barrel induces
incremental U.S. production of 0.6MM barrels per day in 6
months, 1.4MM in 1 year, 2.4MM in 2 years, and 4.2MM in 5
years. Nonetheless, the response takes much longer than the
30 to 90 days than typically associated with the role of
'swing producer'.},
Doi = {10.5547/01956574.40.3.rnew},
Key = {fds333902}
}
@article{fds333535,
Author = {Newell, RG and Raimi, D},
Title = {The fiscal impacts of increased U.S. oil and gas development
on local governments},
Journal = {Energy Policy},
Volume = {117},
Pages = {14-24},
Publisher = {Elsevier BV},
Year = {2018},
Month = {June},
url = {http://dx.doi.org/10.1016/j.enpol.2018.02.042},
Abstract = {Increased US oil and gas production has created
opportunities and challenges for local governments. Through
interviews with roughly 250 local officials, we evaluate the
fiscal effects of this development in 21 regions across
every major US oil and gas producing state during “boom”
and “bust” periods. Growing oil and gas production has
increased local government revenues through a variety of
mechanisms, including property taxes, sales taxes, severance
taxes, and more. Industry activity has also increased costs
and demand for local services led by road damage, water and
wastewater infrastructure, and a range of staff costs
including emergency services and law enforcement. Despite
volatility in revenues and service demands, our interview
results show that 74% of local governments have experienced
net fiscal benefits, 14% reported roughly neutral effects,
and 12% reported net fiscal costs. Local governments in
highly rural regions experiencing large-scale growth have
faced the greatest challenges. To further improve future
outcomes, local officials can plan for impacts, state
policymakers can re-examine revenue policies, and operators
can pursue collaboration with local governments.},
Doi = {10.1016/j.enpol.2018.02.042},
Key = {fds333535}
}
@article{fds333908,
Author = {Bielen, DA and Newell, RG and Pizer, WA},
Title = {Who did the ethanol tax credit benefit? An event analysis of
subsidy incidence},
Journal = {Journal of Public Economics},
Volume = {161},
Pages = {1-14},
Publisher = {Elsevier BV},
Year = {2018},
Month = {May},
url = {http://dx.doi.org/10.1016/j.jpubeco.2018.03.005},
Abstract = {At the end of 2011, the Volumetric Ethanol Excise Tax Credit
(VEETC), which had subsidized the blending of ethanol in
gasoline, was allowed to expire. During its tenure, the
subsidy was the subject of intense scrutiny concerning who
benefited from its existence. Using commodity price data, we
estimate the subsidy incidence accruing to corn farmers,
ethanol producers, gasoline blenders, and gasoline consumers
around the time of expiration. Our empirical approach
contributes methodologically to the event studies literature
by analyzing futures contract prices (as opposed to spot
prices) when possible. Ultimately, we find compelling
evidence that, at the date of VEETC expiration, ethanol
producers captured about 25¢ of the 45¢ subsidy per gallon
of ethanol blended. We find suggestive, albeit inconclusive,
evidence that a portion of this benefit (about 5¢ per
gallon) was passed further upstream from ethanol producers
to corn farmers. Most of the remainder seems most likely to
have been captured by the blenders themselves. On the
petroleum side, we find no evidence that oil refiners
captured any part of the subsidy. We also find no evidence
that the subsidy was passed downstream to gasoline consumers
in the form of lower gasoline prices.},
Doi = {10.1016/j.jpubeco.2018.03.005},
Key = {fds333908}
}
@article{fds267050,
Author = {Kerr, S and Newell, RG},
Title = {Policy-induced technology adoption: Evidence from the U.S.
lead phasedown},
Pages = {193-219},
Year = {2018},
Month = {January},
ISBN = {9780815388227},
url = {http://dx.doi.org/10.4324/9781351161084-11},
Abstract = {Theory suggests that economic instruments, such as pollution
taxes or tradable permits, can provide more efficient
technology adoption incentives than conventional regulatory
standards. We explore this issue for an important industry
undergoing dramatic decreases in allowed pollution - the
U.S. petroleum industry’s phasedown of lead in gasoline.
Using a duration model applied to a panel of refineries from
1971-1995, we find that the pattern of technology adoption
is consistent with an economic response to market
incentives, plant characteristics, and alternative policies.
Importantly, evidence suggests that the tradable permit
system used during the phasedown provided incentives for
more efficient technology adoption decisions.},
Doi = {10.4324/9781351161084-11},
Key = {fds267050}
}
@article{fds330723,
Author = {Newell, RG and Raimi, D},
Title = {US state and local oil and gas revenue sources and
uses},
Journal = {Energy Policy},
Volume = {112},
Pages = {12-18},
Publisher = {Elsevier BV},
Year = {2018},
Month = {January},
url = {http://dx.doi.org/10.1016/j.enpol.2017.10.002},
Abstract = {US state and local governments generate revenues from oil
and gas production through a variety of mechanisms. In this
paper, we quantify four leading sources: (1) state taxes
levied on the value or volume of oil and gas produced; (2)
local property taxes levied on the value of oil and gas
property; (3) oil and gas lease revenues from state lands;
and (4) oil and gas lease revenues from federal lands. We
measure these revenues against the total value of oil and
gas produced in the top 16 oil- and gas-producing states
using fiscal year 2013 as a benchmark. On average, state and
local governments collect roughly 10% of oil and gas
revenue, ranging from a low of roughly 1% to a high of
nearly 40% (not including income taxes). We also assess the
use of these revenues, finding that there is substantial
variation among states. The largest shares of revenue flow
to state governments’ current expenditures and education,
followed by local governments. Some states also allocate a
portion of oil and gas revenues to trust funds endowing
future government operations and/or education
expenditures.},
Doi = {10.1016/j.enpol.2017.10.002},
Key = {fds330723}
}
@article{fds267085,
Author = {Gerarden, TD and Newell, RG and Stavins, RN},
Title = {Assessing the energy-efficiency gap},
Journal = {Journal of Economic Literature},
Volume = {55},
Number = {4},
Pages = {1486-1525},
Publisher = {American Economic Association},
Year = {2017},
Month = {December},
url = {http://dx.doi.org/10.1257/jel.20161360},
Abstract = {Energy-efficient technologies offer considerable promise for
reducing the financial costs and environmental damages
associated with energy use, but it has long been observed
that these technologies may not be adopted by individuals
and firms to the degree that might be justified, even on a
purely financial basis. We survey the relevant literature on
this "energy-efficiency gap" by presenting two complementary
frameworks. First, we divide potential explanations for the
energy-efficiency gap into three categories: market
failures, behavioral explanations, and model and measurement
errors. Second, we organize previous research in terms of
the fundamental elements of cost-minimizing
energy-efficiency decisions. This provides a decomposition
that organizes thinking around four questions. First, are
product offerings and pricing economically efficient?
Second, are energy operating costs inefficiently priced
and/or understood? Third, are product choices cost
minimizing in present value terms? Fourth, do other costs
inhibit more energy-efficient decisions? We synthesize
academic research on these questions, with an emphasis on
recent empirical findings, and offer suggestions for future
research. ( JEL D24, D82, L94, L98, O33, Q41,
Q48).},
Doi = {10.1257/jel.20161360},
Key = {fds267085}
}
@article{fds347655,
Author = {Fischer, C and Preonas, L and Newell, RG},
Title = {Environmental and technology policy options in the
electricity sector: Are we deploying too
many?},
Journal = {Journal of the Association of Environmental and Resource
Economists},
Volume = {4},
Number = {4},
Pages = {959-984},
Year = {2017},
Month = {December},
url = {http://dx.doi.org/10.1086/692507},
Abstract = {Myriad policy measures aim to reduce greenhouse gas
emissions from the electricity sector, promote generation
from renewable sources, and encourage energy efficiency
(EE). Prior literature has argued that overlapping policies
reduce the efficiency of emissions markets, absent other
market failures. We extend the model of Fischer and Newell
to incorporate knowledge spillovers for both advanced and
conventional renewable energy technologies, as well as
imperfections in demand for EE investments. EE
undervaluation can justify interventions and raises the
importance of fully pricing the social costs of electricity,
making policies (like renewable subsidies) that lower
electricity prices less desirable. Innovation market
failures justify some technology policies, particularly
correcting R&D incentives, but aggressive deployment
policies seem unlikely to enhance welfare when placed
alongside sufficient emissions pricing. Even with multiple
market failures, emissions pricing remains the most
cost-effective option for reducing emissions. However,
technology-oriented policies can involve less redistribution
of surplus.},
Doi = {10.1086/692507},
Key = {fds347655}
}
@article{fds333900,
Author = {Newell, RG and Prest, B},
Title = {Informing SPR Policy Through Oil Futures and Inventory
Dynamics},
Year = {2017},
Month = {November},
Key = {fds333900}
}
@article{fds333901,
Author = {Newell, RG and Prest, B},
Title = {Informing SPR Policy Through Oil Futures and Inventory
Dynamics},
Journal = {Ssrn Electronic Journal},
Publisher = {Elsevier BV},
Year = {2017},
Month = {October},
url = {http://dx.doi.org/10.2139/ssrn.3094419},
Doi = {10.2139/ssrn.3094419},
Key = {fds333901}
}
@article{fds333903,
Author = {Newell, RG and Prest, B},
Title = {Is the US the New Swing Producer? The Price Responsiveness
of Tight Oil},
Journal = {Ssrn Electronic Journal},
Number = {17},
Publisher = {Elsevier BV},
Year = {2017},
Month = {June},
url = {http://dx.doi.org/10.2139/ssrn.3093968},
Doi = {10.2139/ssrn.3093968},
Key = {fds333903}
}
@article{fds330013,
Author = {Bradbury, K and Saboo, R and Johnson, TL and Malof, JM and Devarajan, A and Zhang, W and Collins, LM and Newell, RG},
Title = {Distributed solar photovoltaic array location and extent
dataset for remote sensing object identification},
Journal = {Scientific Data},
Volume = {3},
Pages = {160106},
Year = {2016},
Month = {December},
url = {http://dx.doi.org/10.1038/sdata.2016.106},
Abstract = {Earth-observing remote sensing data, including aerial
photography and satellite imagery, offer a snapshot of the
world from which we can learn about the state of natural
resources and the built environment. The components of
energy systems that are visible from above can be
automatically assessed with these remote sensing data when
processed with machine learning methods. Here, we focus on
the information gap in distributed solar photovoltaic (PV)
arrays, of which there is limited public data on solar PV
deployments at small geographic scales. We created a dataset
of solar PV arrays to initiate and develop the process of
automatically identifying solar PV locations using remote
sensing imagery. This dataset contains the geospatial
coordinates and border vertices for over 19,000 solar panels
across 601 high-resolution images from four cities in
California. Dataset applications include training object
detection and other machine learning algorithms that use
remote sensing imagery, developing specific algorithms for
predictive detection of distributed PV systems, estimating
installed PV capacity, and analysis of the socioeconomic
correlates of PV deployment.},
Doi = {10.1038/sdata.2016.106},
Key = {fds330013}
}
@article{fds330014,
Author = {Malof, JM and Bradbury, K and Collins, LM and Newell,
RG},
Title = {Automatic detection of solar photovoltaic arrays in high
resolution aerial imagery},
Journal = {Applied Energy},
Volume = {183},
Pages = {229-240},
Publisher = {Elsevier BV},
Year = {2016},
Month = {December},
url = {http://dx.doi.org/10.1016/j.apenergy.2016.08.191},
Abstract = {The quantity of small scale solar photovoltaic (PV) arrays
in the United States has grown rapidly in recent years. As a
result, there is substantial interest in high quality
information about the quantity, power capacity, and energy
generated by such arrays, including at a high spatial
resolution (e.g., cities, counties, or other small regions).
Unfortunately, existing methods for obtaining this
information, such as surveys and utility interconnection
filings, are limited in their completeness and spatial
resolution. This work presents a computer algorithm that
automatically detects PV panels using very high resolution
color satellite imagery. The approach potentially offers a
fast, scalable method for obtaining accurate information on
PV array location and size, and at much higher spatial
resolutions than are currently available. The method is
validated using a very large (135 km2) collection of
publicly available (Bradbury et al., 2016) aerial imagery,
with over 2700 human annotated PV array locations. The
results demonstrate the algorithm is highly effective on a
per-pixel basis. It is likewise effective at object-level PV
array detection, but with significant potential for
improvement in estimating the precise shape/size of the PV
arrays. These results are the first of their kind for the
detection of solar PV in aerial imagery, demonstrating the
feasibility of the approach and establishing a baseline
performance for future investigations.},
Doi = {10.1016/j.apenergy.2016.08.191},
Key = {fds330014}
}
@article{fds333904,
Author = {Raimi, D and Newell, RG},
Title = {US State and Local Oil and Gas Revenues},
Year = {2016},
Month = {November},
Key = {fds333904}
}
@article{fds333907,
Author = {Newell, RG and Prest, B and Vissing, A},
Title = {Trophy Hunting vs. Manufacturing Energy: The
Price-Responsiveness of Shale Gas},
Year = {2016},
Month = {August},
Key = {fds333907}
}
@article{fds361696,
Author = {Newell, RG and Raimi, D},
Title = {Local government revenue from oil and gas
production},
Year = {2016},
Month = {June},
Abstract = {Oil and gas production generates substantial revenue for
state and local governments. This report examines revenue
from oil and gas production flowing to local governments
through four mechanisms: (i) state taxes or fees on oil and
gas production; (ii) local property taxes on oil and gas
property; (iii) leasing of state-owned land; and (iv)
leasing of federally owned land. We examine every major oil-
and gas-producing state and find that the share of oil and
gas production value allocated to and collected by local
governments ranges widely, from 0.5 percent to more than 9
percent due to numerous policy differences among states.
School districts and trust funds endowing future school
operations tend to see the highest share of revenue,
followed by counties. Municipalities and other local
governments with more limited geographic boundaries tend to
receive smaller shares of oil and gas driven revenue. Some
states utilize grant programs to allocate revenue to where
impacts from the industry are greatest. Others send most
revenue to state operating or trust funds, with little
revenue earmarked specifically for local
governments.},
Key = {fds361696}
}
@article{fds361697,
Author = {Newell, RG and Raimi, D},
Title = {Local fiscal effects of oil and gas development in eight
states},
Year = {2016},
Month = {June},
Abstract = {Oil and gas production in the United States has increased
dramatically in the past 10 years. This growth has important
implications for local governments, which often see new
revenues from a variety of sources: property taxes on oil
and gas property, sales taxes driven by the oil and gas
workforce, allocations of state revenues from severance
taxes or state and federal leases, leases on local
government land, and contributions from oil and gas
companies to support local services. At the same time, local
governments tend to experience a range of new costs such as
road damage caused by heavy industry truck traffic,
increased demand for emergency services and law enforcement,
and challenges with workforce retention. This report
examines county and municipal fiscal effects in 14 oil- and
gas-producing regions of eight states: AK, CA, KS, OH, OK,
NM, UT, and WV. We find that for most local governments, oil
and gas development—whether new or longstanding—has a
positive effect on local public finances. However, effects
can vary substantially due to a variety of local factors and
policy issues. For some local governments, particularly
those in rural regions experiencing large increases in
development, revenues have not kept pace with rapidly
increased costs and demand for services, particularly on
road repair. Duke University Energy Initiative working
paper; May 2016.},
Key = {fds361697}
}
@article{fds361699,
Author = {Newell, RG and Raimi, D},
Title = {Dunn County and Watford City, North Dakota: A case study of
the fiscal effects of Bakken shale development},
Publisher = {Duke University Energy Initiative},
Year = {2016},
Month = {May},
Abstract = {The Bakken region of North Dakota and Montana has
experienced perhaps the greatest effects of increased oil
and gas development in the United States, with major
implications for local governments. Though development of
the Bakken began in the early 2000s, large-scale drilling
and population growth dramatically affected the region from
roughly 2008 through today. This case study examines the
local government fiscal benefits and challenges experienced
by Dunn County and Watford City, which lie near the heart of
the producing region. For both local governments, the
initial growth phase presented major fiscal challenges due
to rapidly expanding service demands and insufficient
revenue. In the following years, these challenges eased as
demand for services slowed due to declining industry
activity and state tax policies redirected more funds to
localities. Looking forward, both local governments describe
their fiscal health as stronger because of the Bakken boom,
though higher debt loads and an economy heavily dependent on
the volatile oil and gas industry each pose challenges for
future fiscal stability.},
Key = {fds361699}
}
@article{fds361698,
Author = {Newell, RG and Raimi, D},
Title = {Colorado's Piceance Basin: Variation in the local public
finance effects of oil and gas development},
Publisher = {Duke University Energy Initiative},
Year = {2016},
Month = {May},
Abstract = {A large increase in natural gas production occurred in
western Colorado’s Piceance basin in the mid- to
late-2000s, generating a surge in population, economic
activity, and heavy truck traffic in this rural region. We
describe the fiscal effects related to this development for
two county governments: Garfield and Rio Blanco, and two
city governments: Grand Junction and Rifle. Counties
maintain rural road networks in Colorado, and Garfield
County’s ability to fashion agreements with operators to
repair roads damaged during operations helped prevent the
types of large new costs seen in Rio Blanco County, a
neighboring county with less government capacity and where
such agreements were not made. Rifle and Grand Junction
experienced substantial oil- and gas-driven population
growth, with greater challenges in the smaller, more
isolated, and less economically diverse city of Rifle.
Lessons from this case study include the value of crafting
road maintenance agreements, fiscal risks for small and
geographically isolated communities experiencing rapid
population growth, challenges associated with limited
infrastructure, and the desirability of flexibility in the
allocation of oil- and gas-related revenue.},
Key = {fds361698}
}
@article{fds267074,
Author = {Gerarden, T and Newell, RG and Stavins, RN},
Title = {Deconstructing the energy efficiency gap: Conceptual
frameworks and evidence},
Journal = {American Economic Review},
Volume = {105},
Number = {5},
Pages = {183-186},
Publisher = {American Economic Association},
Year = {2015},
Month = {May},
ISSN = {0002-8282},
url = {http://hdl.handle.net/10161/10273 Duke open
access},
Doi = {10.1257/aer.p20151012},
Key = {fds267074}
}
@article{fds267083,
Author = {Newell, RG and Siikamki, J},
Title = {Individual time preferences and energy efficiency},
Journal = {American Economic Review},
Volume = {105},
Number = {5},
Pages = {196-200},
Publisher = {American Economic Association},
Year = {2015},
Month = {May},
ISSN = {0002-8282},
url = {http://hdl.handle.net/10161/10274 Duke open
access},
Doi = {10.1257/aer.p20151010},
Key = {fds267083}
}
@article{fds267045,
Author = {Gerarden, T and Newell, RG and Stavins, RN},
Title = {Assessing the Energy-Efficiency Gap},
Journal = {Feem Working Paper},
Number = {035},
Year = {2015},
Month = {April},
Abstract = {Energy-efficient technologies offer considerable promise for
reducing the financial costs and environmental damages
associated with energy use, but these technologies appear
not to be adopted by consumers and businesses to the degree
that would apparently be justified, even on a purely
financial basis. We present two complementary frameworks for
understanding this so-called “energy paradox” or
“energy-efficiency gap.” First, we build on the previous
literature by dividing potential explanations for the
energy-efficiency gap into three categories: market
failures, behavioral anomalies, and model and measurement
errors. Second, we posit that it is useful to think in terms
of the fundamental elements of cost-minimizing
energy-efficiency decisions. This provides a decomposition
that organizes thinking around four questions. First, are
product offerings and pricing economically efficient?
Second, are energy operating costs inefficiently priced
and/or understood? Third, are product choices
cost-minimizing in present value terms? Fourth, do other
costs inhibit more energy-efficient decisions? We review
empirical evidence on these questions, with an emphasis on
recent advances, and offer suggestions for future
research.},
Key = {fds267045}
}
@article{fds267076,
Author = {Gerarden, T and Newell, RG and Stavins, RN and Stowe,
R},
Title = {An Assessment of the Energy-Efficiency Gap and Its
Implications for Climate Change Policy},
Year = {2015},
Month = {April},
Abstract = {Improving end-use energy efficiency — that is, the
energy-efficiency of individuals, households, and firms as
they consume energy — is often cited as an important
element in efforts to reduce greenhouse-gas (GHG) emissions.
Arguments for improving energy efficiency usually rely on
the idea that energy-efficient technologies will save end
users money over time and thereby provide low-cost or
no-cost options for reducing GHG emissions. However, some
research suggests that energy-efficient technologies appear
not to be adopted by consumers and businesses to the degree
that would seem justified, even on a purely financial basis.
We review in this paper the evidence for a range of
explanations for this apparent “energy-efficiency gap.”
We find most explanations are grounded in sound economic
theory, but the strength of empirical support for these
explanations varies widely. Retrospective program
evaluations suggest the cost of GHG abatement varies
considerably across different energy-efficiency investments
and can diverge substantially from the predictions of
prospective models. Findings from research on the
energy-efficiency gap could help policy makers generate
social and private benefits from accelerating the diffusion
of energy-efficient technologies — including reduction of
GHG emissions.},
Key = {fds267076}
}
@article{fds267075,
Author = {Gerarden, T and Newell, RG and Stavins, RN},
Title = {Assessing the Energy-Efficiency Gap},
Year = {2015},
Month = {January},
Abstract = {Energy-efficient technologies offer considerable promise for
reducing the financial costs and environmental damages
associated with energy use, but these technologies appear
not to be adopted by consumers and businesses to the degree
that would apparently be justified, even on a purely
financial basis. We present two complementary frameworks for
understanding this so-called “energy paradox” or
“energy-efficiency gap.” First, we build on the previous
literature by dividing potential explanations for the
energy-efficiency gap into three categories: market
failures, behavioral anomalies, and model and measurement
errors. Second, we posit that it is useful to think in terms
of the fundamental elements of cost-minimizing
energy-efficiency decisions. This provides a decomposition
that organizes thinking around four questions. First, are
product offerings and pricing economically efficient?
Second, are energy operating costs inefficiently priced
and/or understood? Third, are product choices
cost-minimizing in present value terms? Fourth, do other
costs inhibit more energy-efficient decisions? We review
empirical evidence on these questions, with an emphasis on
recent advances, and offer suggestions for future
research.},
Key = {fds267075}
}
@article{fds267086,
Author = {Gerarden, T and Newell, RG and Stavins, RN and Stowe,
R},
Title = {An Assessment of the Energy-Efficiency Gap and its
Implications for Climate-Change Policy},
Year = {2015},
Month = {January},
Abstract = {Improving end-use energy efficiency—that is, the
energy-efficiency of individuals, households, and firms as
they consume energy—is often cited as an important element
in efforts to reduce greenhouse-gas (GHG) emissions.
Arguments for improving energy efficiency usually rely on
the idea that energy-efficient technologies will save end
users money over time and thereby provide low-cost or
no-cost options for reducing GHG emissions. However, some
research suggests that energy-efficient technologies appear
not to be adopted by consumers and businesses to the degree
that would seem justified, even on a purely financial basis.
We review in this paper the evidence for a range of
explanations for this apparent “energy-efficiency gap.”
We find most explanations are grounded in sound economic
theory, but the strength of empirical support for these
explanations varies widely. Retrospective program
evaluations suggest the cost of GHG abatement varies
considerably across different energy-efficiency investments
and can diverge substantially from the predictions of
prospective models. Findings from research on the
energy-efficiency gap could help policy makers generate
social and private benefits from accelerating the diffusion
of energy-efficient technologies—including reduction of
GHG emissions.<br><br>Institutional subscribers to the NBER
working paper series, and residents of developing countries
may download this paper without additional charge at <a
href="http://www.nber.org/papers/w??20905"
TARGET="_blank">www.nber.org</a>.<br>},
Key = {fds267086}
}
@article{fds267089,
Author = {Pizer, W and Adler, M and Aldy, J and Anthoff, D and Cropper, M and Gillingham, K and Greenstone, M and Murray, B and Newell, R and Richels,
R and Rowell, A and Waldhoff, S and Wiener, J},
Title = {Using and improving the social cost of carbon},
Journal = {Science (New York, N.Y.)},
Volume = {346},
Number = {6214},
Pages = {1189-1190},
Year = {2014},
Month = {December},
ISSN = {0036-8075},
url = {http://hdl.handle.net/10161/10259 Duke open
access},
Doi = {10.1126/science.1259774},
Key = {fds267089}
}
@article{fds267082,
Author = {Newell, RG and Siikamäki, J},
Title = {Nudging Energy Efficiency Behavior: The Role of Information
Labels},
Pages = {555-598},
Publisher = {University of Chicago Press},
Year = {2014},
Month = {December},
url = {http://dx.doi.org/10.1086/679281},
Abstract = {This report evaluates the effectiveness of energy efficiency
labels in guiding household decisions. Using a choice
experiment with alternative labels, the authors find that
simple information on the economic value of saving energy is
the most important element guiding more cost-efficient
investments in appliance energy efficiency; information on
physical energy use and carbon emissions has no significant
additional value. They also find that the degree to which
the current EnergyGuide label guides cost-efficient
decisions depends on the assumed discount rate. These
results reinforce the importance of intertemporal choice and
discounting for understanding individual behavior and
guiding policy.},
Doi = {10.1086/679281},
Key = {fds267082}
}
@article{fds267046,
Author = {Gerarden, T and Newell, RG and Stavins, RN and Stowe,
R},
Title = {An Assessment of the Energy-Efficiency Gap and Its
Implications for Climate-Change Policy},
Year = {2014},
Month = {November},
Abstract = {Improving end-use energy efficiency — that is, the
energy-efficiency of individuals, households, and firms as
they consume energy — is often cited as an important
element in efforts to reduce greenhouse-gas (GHG) emissions.
Arguments for improving energy efficiency usually rely on
the idea that energy-efficient technologies will save end
users money over time and thereby provide low-cost or
no-cost options for reducing GHG emissions. However, some
research suggests that energy-efficient technologies appear
not to be adopted by consumers and businesses to the degree
that would seem justified, even on a purely financial basis.
We review in this paper the evidence for a range of
explanations for this apparent “energy-efficiency gap.”
We find most explanations are grounded in sound economic
theory, but the strength of empirical support for these
explanations varies widely. Retrospective program
evaluations suggest the cost of GHG abatement varies
considerably across different energy-efficiency investments
and can diverge substantially from the predictions of
prospective models. Findings from research on the
energy-efficiency gap could help policy makers generate
social and private benefits from accelerating the diffusion
of energy-efficient technologies — including reduction of
GHG emissions.},
Key = {fds267046}
}
@article{fds267090,
Author = {Newell, RG and Pizer, WA and Raimi, D},
Title = {Carbon markets: Past, present, and future},
Journal = {Annual Review of Resource Economics},
Volume = {6},
Number = {1},
Pages = {191-215},
Publisher = {ANNUAL REVIEWS},
Year = {2014},
Month = {October},
ISSN = {1941-1340},
url = {http://hdl.handle.net/10161/10262 Duke open
access},
Abstract = {Carbon markets are substantial and expanding. There are many
lessons from experience over the past 9 years: fewer free
allowances, careful moderation of low and high prices, and a
recognition that trading systems require adjustments that
have consequences for market participants and market
confidence. Moreover, the emerging international
architecture features separate emissions trading systems
serving distinct jurisdictions. These programs are
complemented by a variety of other types of policies
alongside the carbon markets. This architecture sits in
sharp contrast to the integrated global trading architecture
envisioned 15 years ago by the designers of the Kyoto
Protocol and raises a suite of new questions. In this new
architecture, jurisdictions with emissions trading have to
decide how, whether, and when to link with one another, and
policy makers must confront how to measure both the
comparability of efforts among markets and the comparability
between markets and a variety of other policy
approaches.},
Doi = {10.1146/annurev-resource-100913-012655},
Key = {fds267090}
}
@article{fds267096,
Author = {Newell, RG and Raimi, D},
Title = {Implications of shale gas development for climate
change},
Journal = {Environmental Science & Technology},
Volume = {48},
Number = {15},
Pages = {8360-8368},
Year = {2014},
Month = {August},
ISSN = {0013-936X},
url = {http://hdl.handle.net/10161/10263 Duke open
access},
Abstract = {Advances in technologies for extracting oil and gas from
shale formations have dramatically increased U.S. production
of natural gas. As production expands domestically and
abroad, natural gas prices will be lower than without shale
gas. Lower prices have two main effects: increasing overall
energy consumption, and encouraging substitution away from
sources such as coal, nuclear, renewables, and electricity.
We examine the evidence and analyze modeling projections to
understand how these two dynamics affect greenhouse gas
emissions. Most evidence indicates that natural gas as a
substitute for coal in electricity production, gasoline in
transport, and electricity in buildings decreases greenhouse
gases, although as an electricity substitute this depends on
the electricity mix displaced. Modeling suggests that absent
substantial policy changes, increased natural gas production
slightly increases overall energy use, more substantially
encourages fuel-switching, and that the combined effect
slightly alters economy wide GHG emissions; whether the net
effect is a slight decrease or increase depends on modeling
assumptions including upstream methane emissions. Our main
conclusions are that natural gas can help reduce GHG
emissions, but in the absence of targeted climate policy
measures, it will not substantially change the course of
global GHG concentrations. Abundant natural gas can,
however, help reduce the costs of achieving GHG reduction
goals. © 2014 American Chemical Society.},
Doi = {10.1021/es4046154},
Key = {fds267096}
}
@article{fds267079,
Author = {Fischer, C and Newell, RG and Preonas, L},
Title = {Environmental and Technology Policy Options in the
Electricity Sector: Interactions and Outcomes},
Year = {2014},
Month = {July},
Abstract = {Myriad policy measures aim to reduce greenhouse gas
emissions from the electricity sector, promote generation
from renewable sources, and encourage energy conservation.
To what extent do innovation and energy efficiency (EE)
market failures justify additional interventions when a
carbon price is in place? We extend the model of Fischer and
Newell (2008) with advanced and conventional renewable
energy technologies and short and long-run EE investments.
We incorporate both knowledge spillovers and imperfections
in the demand for energy efficiency. We conclude that some
technology policies, particularly correcting R&D market
failures, can be useful complements to emissions pricing,
but ambitious renewable targets or subsidies seem unlikely
to enhance welfare when placed alongside sufficient
emissions pricing. The desirability of stringent EE policies
is highly sensitive to the degree of undervaluation of EE by
consumers, which also has implications for policies that
tend to lower electricity prices Even with multiple market
failures, emissions pricing remains the single most
cost-effective option for reducing emissions.},
Key = {fds267079}
}
@article{fds267069,
Author = {Fischer, C and Newell, RG and Preonas, L},
Title = {Environmental and Technology Policy Options in the
Electricity Sector: Interactions and Outcomes},
Year = {2014},
Month = {April},
url = {http://hdl.handle.net/10161/10753 Duke open
access},
Abstract = {Myriad policy measures aim to reduce greenhouse gas
emissions from the electricity sector, promote generation
from renewable sources, and encourage energy conservation.
To what extent do innovation and energy efficiency (EE)
market failures justify additional interventions when a
carbon price is in place? We extend the model of Fischer and
Newell (2008) with advanced and conventional renewable
energy technologies and short and long-run EE investments.
We incorporate both knowledge spillovers and imperfections
in the demand for energy efficiency. We conclude that some
technology policies, particularly correcting R&D market
failures, can be useful complements to emissions pricing,
but ambitious renewable targets or subsidies seem unlikely
to enhance welfare when placed alongside sufficient
emissions pricing. The desirability of stringent EE policies
is highly sensitive to the degree of undervaluation of EE by
consumers, which also has implications for policies that
tend to lower electricity prices. Even with multiple market
failures, emissions pricing remains the single most
cost-effective option for reducing emissions.},
Key = {fds267069}
}
@article{fds267094,
Author = {Arrow, KJ and Cropper, ML and Gollier, C and Groom, B and Heal, GM and Newell, RG and Nordhaus, WD and Pindyck, RS and Pizer, WA and Portney,
PR and Sterner, T and Tol, RSJ and Weitzman, ML},
Title = {Should governments use a declining discount rate in project
analysis?},
Journal = {Review of Environmental Economics and Policy},
Volume = {8},
Number = {2},
Pages = {145-163},
Publisher = {Oxford University Press (OUP)},
Year = {2014},
Month = {January},
ISSN = {1750-6816},
url = {http://hdl.handle.net/10161/10268 Duke open
access},
Abstract = {At a workshop held at Resources for the Future in September
2011, twelve of the authors were asked by the US
Environmental Protection Agency (EPA) to provide advice on
the principles to be used in discounting the benefits and
costs of projects that affect future generations. Maureen L.
Cropper chaired the workshop. Much of the discussion in this
article is based on the authors' recommendations and advice
presented at the workshop. © The Author
2014.},
Doi = {10.1093/reep/reu008},
Key = {fds267094}
}
@article{fds267095,
Author = {Newell, RG and Pizer, WA and Raimi, D},
Title = {Carbon markets: Effective policy? - Response},
Journal = {Science (New York, N.Y.)},
Volume = {344},
Number = {6191},
Pages = {1460-1461},
Year = {2014},
Month = {January},
ISSN = {0036-8075},
url = {http://hdl.handle.net/10161/10261 Duke open
access},
Doi = {10.1126/science.344.6191.1460-c},
Key = {fds267095}
}
@article{fds267097,
Author = {Newell, RG and Pizer, WA and Raimi, D},
Title = {Carbon market lessons and global policy outlook},
Journal = {Science (New York, N.Y.)},
Volume = {343},
Number = {6177},
Pages = {1316-1317},
Year = {2014},
Month = {January},
ISSN = {0036-8075},
url = {http://hdl.handle.net/10161/10260 Duke open
access},
Abstract = {Ongoing work on linking markets and mixing policies builds
on successes and failures in pricing and trading
carbon.},
Doi = {10.1126/science.1246907},
Key = {fds267097}
}
@article{fds267072,
Author = {Arrow, KJ and Cropper, M and Gollier, C and Groom, B and Heal, GM and Newell, RG and Nordhaus, WD and Pindyck, RS and Pizer, WA and Portney,
P and Sterner, T and Tol, RSJ and Weitzman, M},
Title = {How Should Benefits and Costs Be Discounted in an
Intergenerational Context? The Views of an Expert
Panel},
Year = {2013},
Month = {December},
Abstract = {In September 2011, the US Environmental Protection Agency
asked 12 economists how the benefits and costs of
regulations should be discounted for projects that affect
future generations. This paper summarizes the views of the
panel on three topics: the use of the Ramsey formula as an
organizing principle for determining discount rates over
long horizons, whether the discount rate should decline over
time, and how intra- and intergenerational discounting
practices can be made compatible. The panel members agree
that the Ramsey formula provides a useful framework for
thinking about intergenerational discounting. We also agree
that theory provides compelling arguments for a declining
certainty-equivalent discount rate. In the Ramsey formula,
uncertainty about the future rate of growth in per capita
consumption can lead to a declining consumption rate of
discount, assuming that shocks to consumption are positively
correlated. This uncertainty in future consumption growth
rates may be estimated econometrically based on historic
observations, or it can be derived from subjective
uncertainty about the mean rate of growth in mean
consumption or its volatility. Determining the remaining
parameters of the Ramsey formula is, however,
challenging.},
Key = {fds267072}
}
@article{fds267113,
Author = {Newell, RG and Pizer, WA and Raimi, D},
Title = {Carbon markets 15 years after Kyoto: Lessons learned, new
challenges},
Journal = {The Journal of Economic Perspectives : a Journal of the
American Economic Association},
Volume = {27},
Number = {1},
Pages = {123-146},
Publisher = {American Economic Association},
Year = {2013},
Month = {December},
url = {http://hdl.handle.net/10161/10264 Duke open
access},
Doi = {10.1257/jep.27.1.123},
Key = {fds267113}
}
@article{fds267059,
Author = {Newell, RG and Siikamäki, J},
Title = {Nudging Energy Efficiency Behavior: The Role of Information
Labels},
Journal = {Resources for the Future Discussion Paper},
Number = {13},
Year = {2013},
Month = {July},
Abstract = {We evaluate the effectiveness of energy efficiency labeling
in guiding household appliance choice decisions. Using a
carefully designed choice experiment with several
alternative labeling treatments, we disentangle the relative
importance of different types of information and
intertemporal behavior (i.e., discounting) in guiding energy
efficiency behavior. We find that simple information on the
economic value of saving energy was the most important
element guiding more cost-efficient investments in appliance
energy efficiency, with information on physical energy use
and carbon dioxide emissions having additional but lesser
importance. The degree to which the current EnergyGuide
label guided cost-efficient decisions depends importantly on
the discount rate assumed appropriate for the analysis.
Using individual discount rates separately elicited in our
study, we find that the current EnergyGuide label came very
close to guiding cost-efficient decisions, on average.
However, using a uniform five percent rate for discounting
— which was much lower than the average individual
elicited rate — the EnergyGuide label led to choices that
result in a one-third undervaluation of energy efficiency.
We find that labels that not only nudged people with
dispassionate monetary or physical information, but also
endorsed a model (with Energy Star) or gave a suggestive
grade to a model (as with the EU-style label), had a
substantial impact in encouraging the choice of appliances
with higher energy efficiency. Our results reinforce the
centrality of views on intertemporal choice and discounting,
both in terms of understanding individual behavior and in
guiding public policy decisions.},
Key = {fds267059}
}
@article{fds267071,
Author = {Newell, RG and Siikamäki, J},
Title = {Nudging Energy Efficiency Behavior: The Role of Information
Labels},
Year = {2013},
Month = {July},
Abstract = {We evaluate the effectiveness of energy efficiency labeling
in guiding household decisions. Using a carefully designed
choice experiment with alternative labels, we disentangle
the relative importance of different types of information
and intertemporal behavior (i.e., discounting) in guiding
energy efficiency behavior. We find that simple information
on the economic value of saving energy was the most
important element guiding more cost-efficient investments in
energy efficiency, with information on physical energy use
and carbon emissions having additional but lesser
importance. The degree to which the current EnergyGuide
label guided cost-efficient decisions depends importantly on
the discount rate assumed. Using individual discount rates
separately elicited in our study, we find that the current
EnergyGuide label came very close to guiding cost-efficient
decisions, on average. However, using a uniform five percent
discount rate--which was much lower than the average
elicited rate--the EnergyGuide label led to choices that
result in a one-third undervaluation of energy efficiency.
We find that labels that also endorsed a model (with Energy
Star) or gave a suggestive grade to a model (EU-style
label), encouraged substantially higher energy efficiency.
Our results reinforce the centrality of views on
intertemporal choice and discounting, both in terms of
understanding individual behavior and in guiding
policy.<br><br>Institutional subscribers to the NBER working
paper series, and residents of developing countries may
download this paper without additional charge at <a
href="http://www.nber.org/papers/w??19224"
TARGET="_blank">www.nber.org</a>.<br>},
Key = {fds267071}
}
@article{fds267081,
Author = {Newell, RG and Iler, S},
Title = {The Global Energy Outlook},
Year = {2013},
Month = {April},
Abstract = {We explore the principal trends that are shaping the future
landscape of energy supply, demand, and trade. We take a
long-term view, assessing trends on the time scale of a
generation by looking 25 years into the past, taking stock
of the current situation, and projecting 25 years into the
future. We view these market, technology, and policy trends
at a global scale, as well as assess the key regional
dynamics that are substantially altering the energy scene.
The shift from West to East in the locus of energy growth
and the turnaround of North American gas and oil production
are the most pronounced of these currents. Key uncertainties
include the strength of economic and population growth in
emerging economies, the stringency of future actions to
reduce carbon emissions, the magnitude of unconventional
natural gas and oil development in non-OPEC countries, and
the stability of OPEC oil supplies.<br><br>Institutional
subscribers to the NBER working paper series, and residents
of developing countries may download this paper without
additional charge at <a href="http://www.nber.org/papers/w??18967"
TARGET="_blank">www.nber.org</a>.<br>},
Key = {fds267081}
}
@article{fds267098,
Author = {Arrow, K and Cropper, M and Gollier, C and Groom, B and Heal, G and Newell,
R and Nordhaus, W and Pindyck, R and Pizer, W and Portney, P and Sterner,
T and Tol, RSJ and Weitzman, M},
Title = {Determining benefits and costs for future
generations},
Journal = {Science (New York, N.Y.)},
Volume = {341},
Number = {6144},
Pages = {349-350},
Year = {2013},
Month = {January},
ISSN = {0036-8075},
url = {http://hdl.handle.net/10161/10265 Duke open
access},
Abstract = {The United States and others should consider adopting a
different approach to estimating costs and benefits in light
of uncertainty.},
Doi = {10.1126/science.1235665},
Key = {fds267098}
}
@article{fds267055,
Author = {Newell, RG and Pizer, WA and Raimi, D},
Title = {Carbon Markets: Past, Present, and Future},
Year = {2012},
Month = {December},
Abstract = {Carbon markets are substantial and they are expanding. There
are many lessons from experiences over the past eight years:
fewer free allowances, better management of market-sensitive
information, and a recognition that trading systems require
adjustments that have consequences for market participants
and market confidence. Moreover, the emerging international
architecture features separate emissions trading systems
serving distinct jurisdictions. These programs are
complemented by a variety of other types of policies
alongside the carbon markets. This sits in sharp contrast to
the integrated global trading architecture envisioned 15
years ago by the designers of the Kyoto Protocol and raises
a suite of new questions. In this new architecture,
jurisdictions with emissions trading have to decide how,
whether, and when to link with one another, and policymakers
overseeing carbon markets must confront how to measure the
comparability of efforts among markets and relative to a
variety of other policy approaches.},
Key = {fds267055}
}
@article{fds267121,
Author = {Eccles, JK and Pratson, L and Newell, RG and Jackson,
RB},
Title = {The impact of geologic variability on capacity and cost
estimates for storing CO
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