David Popp's Publications and Working Papers

Working Papers

Description of data used in my energy patent papers (taken from chapter 2 of my dissertation).


Publications (when possible, links to journal web sites or working papers are included)

The Learning Process and Technological Change in Wind Power: Evidence from China’s CDM Wind ProjectsJournal of Policy Analysis and Management, 35(1), 195-222, Winter 2016 (with Tian Tang).


The Clean Development Mechanism (CDM) is a project-based carbon trade mechanism that subsidizes the users of climate-friendly technologies and encourages technology transfer. The CDM has provided financial support for a large share of Chinese wind projects since 2002. Using pooled cross-sectional data of 486 registered CDM wind projects in China from 2002 to 2009, we examine the determinants of technological change in wind power from a learning perspective. We use a spatial error model to estimate the effects of different channels of learning—learning through R&D in wind turbine manufacturing, learning from a firm's previous wind project experience, spillovers from industry-wide project experience, and learning through the network interaction between project developer and turbine manufacturer—on technological change, measured as reductions in projected costs or as increased capacity factor across CDM wind projects. While we find that a project developer's previous experience matters, interactions between a wind project developer and its partner foreign turbine manufacturer lead to the largest cost reductions and capacity factor improvement. We also find that spillovers from industry-wide experience only exist for wind farm installation. The evidence of industry-wide spillovers and the joint learning within partnerships between project developers and foreign turbine manufacturers supports the subsidies to users of wind technologies, and policy regimes that promote international collaboration and technology transfer.   

Climate-Friendly Technological Change for Developing Countries,” in Oxford Handbook of Macroeconomics of Global Warming, edited by Lucas Bernard and Willi Semmler, Oxford University Press, 2015, pp. 321-348. 


By reducing the costs of environmental protection, technological change is important for promoting green growth.  This entails both the creation of new technologies and more widespread deployment of existing green technologies.  This paper reviews the literature on environmentally friendly technological change, with a focus on lessons relevant to developing countries.  I begin with a discussion of data available for measuring the various steps of technological change.  I continue with a discussion of sources of environmental innovation.  Given that most innovation is concentrated in a few rich countries, this leads to a discussion of the remaining role for lower-income countries, followed by a discussion of technology transfer.  Because of the importance of market failures, I then discuss the role of both technology policy and environmental policy for promoting environmentally friendly technological change.  The review concludes with a discussion of what environmental economists can learn from other fields.


Introduction to the Special Issue on Climate Adaptation: Improving the connection between empirical research and integrated assessment models,” Energy Economics, November 2014, 46, 495-499 (with Karen Fisher-Vanden and Ian Sue Wing).

Necessity as the Mother of Invention: Innovative Responses to Natural Disasters Journal of Environmental Economics and Management, 68(2), 280-295, September 2014  (with Qing Miao).


How do innovators respond to the shock of a natural disaster? Do natural disasters spur technical innovations that can reduce the risk of future hazards? This paper examines the impact of three types of natural disasters including earthquakes, droughts and flooding on the innovation of their respective mitigation technologies. Using patent and disaster data, our study is the first to relate natural disasters to technology innovation, and also presents the first attempt to empirically examine adaptation responses to climate change across multiple sectors at the country level. Overall, we show that natural disasters lead to more risk-mitigating innovations, while the degree of influence varies across different types of disasters and technologies.


Technology Variation vs. R&D Uncertainty: What Matters Most for Energy Patent Success?Resource and Energy Economics, 35(4), November 2013, 505-533 (with Nidhi Santen, Karen Fisher-Vanden and Mort Webster).


R&D is an uncertain activity with highly skewed outcomes.  Nonetheless, most recent empirical studies and modeling estimates of the potential of technological change focus on the average returns to research and development (R&D) for a composite technology and contain little or no information about the distribution of returns to R&D—which could be important for capturing the range of costs associated with climate change mitigation policies—by individual technologies.  Through an empirical study of patent citation data, this paper adds to the literature on returns to energy R&D by focusing on the behavior of the most successful innovations for six energy technologies, allowing us to determine whether uncertainty or differences in technologies matter most for success.  We highlight two key results.  First, we compare the results from an aggregate analysis of six energy technologies to technology-by-technology results.  Our results show that existing work that assumes diminishing returns but assumes one generic technology is too simplistic and misses important differences between more successful and less successful technologies.  Second, we use quantile regression techniques to learn more about patents that have a high positive error term in our regressions – that is, patents that receive many more citations than predicted based on observable characteristics.  We find that differences across technologies, rather than differences across quantiles within technologies, are more important.  The value of successful technologies persists longer than those of less successful technologies, providing evidence that success is the culmination of several advances building upon one another, rather than resulting from one single breakthrough.  Diminishing returns to research efforts appear most problematic during rapid increases of research investment, such as experienced by solar energy in the 1970s.



The Clean Development Mechanism and Neglected Environmental Technologies,” Energy Policy, April 2013, 55, 165-179 (with Jung Eun Kim and Andrew Prag).  



The Clean Development Mechanism (CDM) provides an institutional framework for developed countries to support projects that reduce greenhouse gas emissions in developing countries.  Many of these projects result in the transfer of technologies to host countries.  Are the technologies transferred those most needed by the recipient countries?  We address this question by first reviewing Technology Needs Assessments prepared by developing countries, and then comparing the stated needs to the technologies most frequently transferred via CDM.  While there appears to be a good match between requested technologies and those used in CDM, desired technologies such as solar energy for remote locations, biofuels, improved cooking stoves, and efficient lighting appear “neglected” by CDM.  Nonetheless, a review of costs for these technologies suggests that they could be cost effective for developing countries.  For projects requiring wide dispersal of household items, such as cooking stoves or lighting, the administrative burdens of CDM provide a hurdle.  In other cases, mismatches between developing country needs and developed country technology capabilities appear to be a problem.  We conclude with possible explanations for why these technologies are neglected and suggestions for future research.



Modeling Climate Change Feedbacks and Adaptation Responses: Recent Approaches and Shortcomings,” Climatic Change, April 2013, 117(3), 481-495 (with Karen Fisher-Vanden, Ian Sue Wing and Elisa Lanzi).  



This paper offers a critical review of modeling practice in the field of integrated assessment of climate change and ways forward. Past efforts in integrated assessment have concentrated on developing baseline trajectories of emissions and mitigation scenario analyses. A key missing component in Integrated Assessment Models (IAMs) is the representation of climate impacts and adaptation responses. In this paper, we identify key biases that are introduced when climate impacts and adaptation responses are omitted from the analysis and review the state of modeling studies that attempt to capture these feedbacks. A common problem in these IAM studies is the lack of connection with empirical studies. We therefore also review the state of the empirical work on climate impacts and identify ways that this connection could be improved.



Where Does Energy R&D Come From?  Examining Crowding out from energy R&D," Energy Economics, July 2012, 34(4), 980-991 (with Richard Newell).


Recent efforts to endogenize technological change in climate policy models demonstrate the importance of accounting for the opportunity cost of climate R&D investments.  Because the social returns to R&D investments are typically higher than the social returns to other types of investment, any new climate mitigation R&D that comes at the expense of other R&D investment may dampen the overall gains from induced technological change. Unfortunately, there has been little empirical work to guide modelers as to the potential magnitude of such crowding out effects.  This paper considers both the private and social opportunity costs of climate R&D.  Addressing private costs, we ask whether an increase in climate R&D represents new R&D spending, or whether some (or all) of the additional climate R&D comes at the expense of other R&D.  Addressing social costs, we use patent citations to compare the social value of alternative energy research to other types of R&D that may be crowded out.  Beginning at the industry level, we find no evidence of crowding out across sectors – that is, increases in energy R&D do not draw R&D resources away from sectors that do not perform R&D.  Given this, we proceed with a detailed look at alternative energy R&D.  Linking patent data and financial data by firm, we ask whether an increase in alternative energy patents leads to a decrease in other types of patenting activity.  While we find that increases in alternative energy patents do result in fewer patents of other types, the evidence suggests that this is due to profit-maximizing changes in research effort, rather than financial constraints that limit the total amount of R&D possible.  Finally, we use patent citation data to compare the social value of alternative energy patents to other patents by these firms.  Alternative energy patents are cited more frequently, and by a wider range of other technologies, than other patents by these firms, suggesting that their social value is higher.

Environmental Policy vs. Public Pressure: Innovation and Diffusion of Alternative Bleaching Technologies in the Pulp Industry,” Research Policy, November 2011, 40(9), 1253-1268 (with Tamara Hafner and Nick Johnstone).


In the late 1980s and early 1990s, concern over dioxin in both paper products and wastewater led to the development of techniques that reduced the use of chlorine in the pulp industry. Both regulatory and consumer pressure motivated this change. Unlike previous studies, we use patent data to examine the evolution of two competing bleaching technologies in five major paper-producing countries, both of which reduce the use of chlorine in the pulping process. The use of patent data allows us to focus on the invention stage. However, adoption data are also presented, and by the end of the 1990s, nearly all pulp production in these countries used one of these technologies. While previous studies emphasize the importance of regulation for inducing innovation, here we find substantial innovation occurring before regulations were in place. Instead, pressure from consumers and the public at large to reduce the chlorine content of paper drove invention, prior to the introduction of environmental policies in any of the countries concerned.

Technology and the Diffusion of Renewable Energy,” Energy Economics, July 2011, 33(4), 648-662 (with Ivan Hascic and Neelakshi Medhi).


We consider investment in wind, solar photovoltaic, geothermal, and electricity from biomass & waste across 26 OECD countries from 1991-2004.  Using the PATSTAT database, we obtain a comprehensive list of patents for each of these technologies throughout the world, which we use to assess the impact of technological change on investment in renewable energy capacity.  We consider four alternative methods for counting patents, considering two possible filters: weighting patents by family size and including only patent applications filed in multiple countries.  For each patent count, we create knowledge stocks representing the global technological frontier.  Technological advances do lead to greater investment, but the effect is small.  Environmental policy appears more important, as countries that have ratified the Kyoto Protocol invest in more renewable capacity.  Investment in other carbon-free energy sources, such as hydro and nuclear power, serve as substitutes for renewable energy.  Comparing the effectiveness of our four patent counts, both using only patents filed in multiple countries and weighting by family size improve the fit of the model. 

International Technology Transfer for Climate Policy,” Review of Environmental Economics and Policy, Winter 2011, 5(1), 131-152.


As the developed world begins efforts to limit its emissions of greenhouse gases, economic growth in developing countries is causing increased emissions from the developing world.  Reducing these emissions while still enabling developing countries to grow requires the use of climate-friendly technologies in these countries.   In most cases, these technologies are first created in high-income countries.  Thus, the challenge for climate policy is to encourage the transfer of these climate-friendly technologies to the developing world. This article reviews the economic literature on environmental technology transfer and discusses the implications of this literature for climate policy, focusing on the Clean Development Mechanism (CDM).  A key point is that technology diffusion is gradual.  Early adoption of policy by developed countries leads to the development of new technologies that make it easier for developing countries to reduce pollution as well.  Since clean technologies are first developed in the world’s leading economies, international trade and foreign investments provide access to these technologies.  Moreover, evidence suggests that some technologies, such as those enhancing energy efficiency, will diffuse to developing countries even without the aid of policy prescriptions such as the CDM.  This is important for assessing the potential emissions reductions of proposed CDM projects.

Trade, Technology, and the Environment: Does Access to Technology Promote Environmental Regulation,” Journal of Environmental Economics and Management, January 2011, 61(1), 16-35 , (with Mary Lovely).


Focusing specifically on regulation of coal-fired power plants, we examine how technological innovation by early adopters influences the timing of new environmental regulation in non-innovating countries.  We build a general equilibrium model of an open economy to identify the political-economy determinants of regulation.  With a newly-created data set of SO2 and NOX regulations for coal-fired power plants and a patent-based measure of the technology frontier, we estimate the determinants of environmental regulation diffusion.  Our findings support the hypothesis that international economic integration eases access to environmentally friendly technologies and leads to earlier adoption, ceteris paribus, of regulation in non-innovating countries.  However, we also find evidence that domestic trade protection promotes earlier adoption by allowing shifts of regulatory costs to domestic consumers.  Furthermore, international market power permits large countries to shift costs to foreign consumers.  Other political economy factors, such as the quality of domestic coal, are also important determinants.

Meaningful Technology Transfer for Climate Disruption,” Journal of International Affairs, 64(1), Fall/Winter 2010, 1-15 (with David M. Driesen).  


Any serious effort to address global climate disruption will require effective technology transfer. Developing countries with growing emissions must somehow make emission reductions without curtailing the economic development needed to alleviate poverty. This must be done in order to permit global abatement on the scale required to avoid dangerous climate disruption. Given the limited financial and technical capabilities of developing countries, this task seems impossible without technology transfer. As policymakers continue to embrace and enhance technology transfer options, it is critical to understand the relationship between technology transfer and policy development in order to formulate more effective policies. Whether through market mechanisms, such as the Clean Development Mechanism (CDM), or direct aid programs, such as the Green Climate Fund, we argue that technology transfer programs must support the elaboration of policies in developing countries by addressing three key issues: adilitionality, appropriate scale and the promotion of knowledge spillovers. We use these three principles to provide a framework for assessing the potential of both the CDM and direct financial aid to foster meaningful technology transfer, which we define as technology transfer that not only lowers the overall short-run costs of carbon reductions, but also enhances the capacity of these countries to address climate change more thoroughly in the future. 

Innovation and Climate Policy,” Annual Review of Resource Economics, vol. 2, 2010, Gordon C. Rausser, V. Kerry Smith and David Zilberman eds., Annual Reviews, Palo Alto, CA, pp. 275-298. 


Within the field of environmental economics, the role of technological change has received much attention. The long-term nature of many environmental problems, such as climate change, makes understanding the evolution of technology an important part of projecting future impacts. Moreover, in many cases environmental problems cannot be addressed, or can only be addressed at great cost, using existing technologies. Providing incentives to develop new environmentally-friendly technologies then becomes a focus of environmental policy. This chapter reviews the literature on technological change and the environment. Our goals are to introduce technological change economists to how the lessons of the economics of technological change have been applied in the field of environmental economics, and suggest ways in which scholars of technological change could contribute to the field of environmental economics.

Energy, the Environment, and Technological Change,” Handbook of the Economics of Innovation: vol. 2, Bronwyn Hall and Nathan Rosenberg, eds., Academic Press/Elsevier, 2010, 873-937  (with Richard Newell and Adam Jaffe).


Within the field of environmental economics, the role of technological change has received much attention. The long-term nature of many environmental problems, such as climate change, makes understanding the evolution of technology an important part of projecting future impacts. Moreover, in many cases environmental problems cannot be addressed, or can only be addressed at great cost, using existing technologies. Providing incentives to develop new environmentally-friendly technologies then becomes a focus of environmental policy. This chapter reviews the literature on technological change and the environment. Our goals are to introduce technological change economists to how the lessons of the economics of technological change have been applied in the field of environmental economics, and suggest ways in which scholars of technological change could contribute to the field of environmental economics. 

Exploring Links Between Innovation and Diffusion: Adoption of NOX Control Technologies at U.S. Coal-fired Power Plants,” Environmental and Resource Economics, March 2010, 45(3), 319-352. .


While many studies have looked at innovation and adoption of technologies separately, the two processes are linked. Advances (and expected advances) in a single technology should affect both its adoption rate and the adoption of alternative technologies. This paper combines plant-level data on US coal-fired electric power plants with patent data pertaining to NOX pollution control techniques to study this link. As in other studies of environmental technologies, the effect of other explanatory variables is dominated by the effect of environmental regulations, demonstrating that the mere presence of environmental technologies is not enough to encourage its usage. Nonetheless, I do find that technological advances are important for the adoption of existing combustion modification technologies. However, these advances are less important for the adoption of newer post-combustion control techniques, which are adopted only when needed to comply with the strictest emission limits.

Renewable Energy Policies and Technological Innovation: Evidence Based on Patent Counts,” Environmental and Resource Economics, January 2010, 45(1), 133-155  (with Nick Johnstone and Ivan Hascic).


This paper examines the effect of environmental policies on technological innovation in the specific case of renewable energy. The analysis is conducted using patent data on a panel of 25 countries over the period 1978–2003. We find that public policy plays a significant role in determining patent applications. Different types of policy instruments are effective for different renewable energy sources. Broad-based policies, such as tradable energy certificates, are more likely to induce innovation on technologies that are close to competitive with fossil fuels. More targeted subsidies, such as feed-in tariffs, are needed to induce innovation on more costly energy technologies, such as solar power.

Information Disclosure Policy: Do States’ Data Processing Efforts Help More than the Information Disclosure Itself?Journal of Policy Analysis and Management, Winter 2010, 29(1), 163-182, (with Hyunhoe Bae and Peter Wilcoxen).


The Toxics Release Inventory (TRI) was expected to reduce health risks stemming from emissions of hazardous chemicals by increasing public pressure on polluters invoked by disclosed toxic release information. However, the raw TRI data fails to transmit accurate information fitted to the public’s interest. TRI is a massive and complex dataset, published in the pounds of toxics released in its raw form, not a health risk indicator which is the true quantity of interest. Consequently, the raw TRI data needs to be refined and interpreted in terms of health risks by the users/public but those processing data procedures often overwhelms their capability. State governments have attempted to increase of the usefulness of the TRI’s information via two types of policies: (1) selection and dissemination of raw TRI data for plants within the state, and (2) data processing activities producing more refined reports and further data analysis. This study assesses the effectiveness of those two types of policies with the hypothesis that the latter might increase the accuracy of the TRI information contributing to the true policy outcome (reducing health risk), more than the former. Our results show that state-level data dissemination efforts lowered the total number of pounds of chemicals released, but had little effect on health risks. State-level data processing efforts, in contrast, did lead to significant reductions in health risks. We conclude that simple dissemination of the data was ineffective (and even counterproductive in some instances), and that the states’ data processing efforts have played a critical role in achieving the TRI’s intended policy goal by providing accurate information with which users can find the right signal of interest.

Does Regulation Stimulate Technical Productive Efficiency?  The Effect of Air Quality Policies on the Efficiency of U.S. Power Plants,”  Energy Policy, November 2009, 37(11), 4574-4582 (with Rachel Fleishman, Rob Alexander, and Stuart Bretschneider ).


This research examines the effect of air quality regulations on the productivity of U.S. power plants based on both economic and environmental outputs.  Using Data Envelopment Analysis (DEA) to estimate an efficiency measure incorporating both economic and environmental outcomes, we look at changes in efficiency in U.S. power plants over an eleven-year time period (1994-2004) during which several different regulations were implemented for the control of nitrogen oxides (NOx) and sulfur dioxide (SO2).  The paper then models how estimated efficiency behaves over time as a function of regulatory changes. Findings suggest mixed effects of regulations on power plant efficiency when pollution abatement and electricity generation are both included as outputs. 

Endogenizing Technological Change: Matching Empirical Evidence to Modeling Needs,” Energy Economics, November 2008, 30(6), 2754-2770 (with William A. Pizer).


Given that technologies to significantly reduce fossil fuel emissions are currently unavailable or only available at high cost, technological change will be a key component of any long-term strategy to reduce greenhouse gas emissions. In light of this, the amount of research on the pace, direction, and benefits of environmentally-friendly technological change has grown dramatically in recent years. This research includes empirical work estimating the magnitude of these effects, and modeling exercises designed to simulate the importance of endogenous technological change in response to climate policy. Unfortunately, few attempts have been made to connect these two streams of research. This paper attempts to bridge that gap. We review both the empirical and modeling literature on technological change. Our focus includes the research and development process, learning by doing, the role of public versus private research, and technology diffusion. Our goal is to provide an agenda for how both empirical and modeling research in these areas can move forward in a complementary fashion. In doing so, we discuss both how models used for policy evaluation can better capture empirical phenomena, and how empirical research can better address the needs of models used for policy evaluation. 

"The Effects of Innovation Policies on Private R&D Investment: A Cross-national Empirical Study,” Economics of Innovation and New Technology, June 2007, 16(4), 237–253 (with Yonghong Wu and Stuart Bretschneider).


This paper examines the effect of three major national innovation policies (patent protection, research and development (R&D) tax incentives, and government funding of business R&D) on business R&D spending. Unlike previous work, we also consider the effect of openness to international trade. We use data from nine OECD countries (Australia, Canada, France, Germany, Italy, Japan, Spain, UK, and USA) in 1985-1995. Our results show that all three innovation policies play a significant role in stimulating business R&D. Enforcement of patent right matters most to business R&D spending. In addition, R&D performed by the government has a positive effect on business R&D, whereas R&D by the higher education sector has a negative impact on business R&D. We also find modest empirical support to the positive role of openness to international trade in business R&D investment.

"They Don't Invent Them Like They Used To: An Examination of Energy Patent Citations Over Time," Economics of Innovation and New Technology, 15(8), November 2006, 753-776.

This paper uses patent citation data to study flows of knowledge across time and across institutions in the field of energy research. Popp (2002) finds the level of energy-saving R&D depends not only on energy prices, but also on the quality of the accumulated knowledge available to inventors. Patent citations are used to represent this quality. This paper explores the pattern of citations in these fields more carefully. I find evidence for diminishing returns to research inputs, both across time and within a given year. To check whether government R&D can help alleviate potential diminishing returns, I pay special attention to citations to government patents. Government patents filed in or after 1981 are more likely to be cited. More importantly, descendants of these government patents are 30 percent more likely to be cited by subsequent patents. Earlier government research was more applied in nature and is not cited more frequently.

Appendix: Patent classifications used in this paper

"Innovation in Climate Policy Models: Implementing Lessons from the Economics of R&D," Energy Economics, 28(5-6), November 2006, 596-609.


Only recently have economists considered the effect of induced innovation in climate policy models.  One reason is that, until recently, empirical evidence of the magnitude of such effects was unavailable.  Drawing on my experiences with empirical studies on innovation and from modeling the climate change problem, in this paper I present key lessons from the empirical literature on innovation and environmental policy, and discuss how much of the variation in results found in the modeling literature can be explained by differences in implementing (or failing to implement) these lessons into climate models.  The paper concludes with a discussion of future research needs, focusing on a framework for improving the modeling of technology diffusion in climate change models.

"R&D Subsidies and Climate Policy: Is There a 'Free Lunch'?", Climatic Change, 77(3-4), August 2006, 311-341.


Because of the long-term nature of the climate problem, technological advances are often seen as an important component of any solution. However, when considering the potential for technology to help solve the climate problem, two market failures exist which lead to underinvestment in climate-friendly R&D: environmental externalities and the public goods nature of new knowledge. As a result, government subsidies to climate-friendly R&D projects are often proposed as part of a policy solution. Using the ENTICE model, I analyze the effectiveness of such subsidies, both with and without other climate policies, such as a carbon tax. While R&D subsidies do lead to significant increases in climate-friendly R&D, this R&D has little impact on the climate itself. Subsidies address the problem of knowledge as a public good, but they do not address the environmental externality, and thus offer no additional incentive to adopt new technologies. Moreover, high opportunity costs to R&D limit the potential role that subsidies can play. While R&D subsidies can improve efficiency, policies that directly affect the environmental externality have a much larger impact on both atmospheric temperature and economic welfare.


Appendix: Equations and calibration of the ENTICE-BR model

"Comparison of Climate Policies in the ENTICE-BR Model", Energy Journal, Special Issue: Endogenous Technological Change and the Economics of Atmospheric Stablilisation, 2006, 163-174.


This paper uses the ENTICE-BR model to study the effects of various climate stabilization policies. Because the ENTICE-BR model includes benefits from reduced climate damages, it is possible to calculate the net economic impact of each policy. In general, only the least restrictive concentration limit is welfare enhancing. While the policies are welfare enhancing in simulations using optimistic assumptions about the potential of the backstop energy technology, such assumptions mean that the backstop is also used in the no-policy base case, so that climate change itself is less of a problem. Finally, assumptions about the nature of R&D markets are important. Removing the assumption of partial crowding out from energy R&D nearly doubles the gains from policy-induced energy R&D.

"The Transition to Endogenous Technical Change in Climate-Economy Models: A Technical Overview to the Innovation Modeling Comparison Project," Energy Journal, Special Issue: Endogenous Technological Change and the Economics of Atmospheric Stablilisation, 2006, 17-55 (with Jonathan Köhler, Michael Grubb, and Ottmar Edenhofer).


This paper assesses endogenous technical change (ETC) in climate-economy models, using the models in the Innovation Modeling Comparison Project as a representative cross-section. ETC is now a feature of most leading models. Following the new endogenous growth literature and the application of learning curves to the energy sector, there are two main concepts employed: knowledge capital and learning curves. The common insight is that technical change is driven by the development of knowledge capital and its characteristics of being partly non-rival and partly non-excludable. There are various different implementations of ETC. Recursive CGE models face particular difficulties in incorporating ETC and increasing returns. The main limitations of current models are: the lack of uncertainty analysis, the limited representation of the diffusion of technology and the homogeneous nature of agents in the models, including the lack of representation of institutional structures in the innovation process.

"ENTICE-BR: The Effects of Backstop Technology R&D on Climate Policy Models", Energy Economics, March 2006, 28(2), 188-222.

"International Innovation and Diffusion of Air Pollution Control Technologies: The Effects of NOX and SO2 Regulation in the US, Japan, and Germany", Journal of Environmental Economics and Management, 51(1), 46-71, January 2006.

"Lessons From Patents: Using Patents to Measure Technological Change: in Environmental Models", Ecological Economics, 54(2-3), 209-226, August 2005.

"Uncertain R&D and the Porter Hypothesis",  Contributions to Economic Analysis & Policy, 4(1), Article 6, 2005.

Ever since Michael Porter proposed that environmental regulations can improve competitiveness, much economic research has examined the potential for such outcomes. Attempts to model Porter hypothesis outcomes in a way consistent with neoclassical economics have focused on things such as strategic relationships between firms, moral hazard problems, and economies of scale. In this paper, I offer a simpler alternative. The results of any R&D project are uncertain. Calibrating a simple model of induced R&D with uncertainty so that the expected value of research is only positive with environmental policy, I find that between 8 and 24 percent of simulations result in cases where post-regulation profits are higher than pre-regulation profits. This result is consistent both with Porter finding specific cases with complete innovation offsets and with macro-level findings that environmental policy is not costless. I conclude by discussing the implication of these results for environmental policy and future research.

"Institutions and Intellectual Property: The Influence of Institutional Forces on University Patenting", (with Yixin Dai and Stuart Bretschneider), Journal of Policy Analysis and Management, 24(3), Summer 2005, 579-598.

Over the past 20 years, the number of patents assigned to universities has increased dramatically. This increase coincided with several policy initiatives, such as the Bayh-Dole Act of 1980, designed to foster technology transfer between universities and the private sector. This paper examines the effect of such policies using an institutional framework, designed to illustrate how factors both from inside and outside of academia influence the decision to patent university research. We find passage of the Bayh-Dole Act spurred university patenting, but did not induce additional applied research funding. Thus, Bayh-Dole fostered technology transfer, but did not result in more applied research at universities.

"Time In Purgatory: Examining the Grant Lag for U.S. Patent Applications", (with Ted Juhl and Daniel K.N. Johnson), Topics in Economic Analysis & Policy, 4(1), Article 29, 2004.


"ENTICE: Endogenous Technological Change in the DICE Model of Global Warming", Journal of Environmental Economics and Management, 48(1), July 2004, 742-768.

"Pollution Control Innovations and the Clean Air Act of 1990", Journal of Policy Analysis and Management, 22(4), Fall 2003, 641-660.

"Forced Out of the Closet: The Impact of the American Inventors Protection Act on the Timing of Patent Disclosure," (with Daniel Johnson), RAND Journal of Economics, 34(1), Spring 2003, pp. 96-112.

"Induced Innovation and Energy Prices," American Economic Review, 92(1), March 2002, pp. 160-180.

"Altruism and the Demand for Environmental Quality," Land Economics, 77(3), August 2001, pp. 339-349.
This paper asks whether individuals consider the value future generations will receive from environmental quality when deciding what level of environmental protection to provide.  Using data on life expectancy, I develop two tests for altruism towards future generations.  One, a test for strong altruism, asks whether individual motives are purely altruistic when deciding to provide environmental quality.  The second, a test for weak altruism, combines an individual’s concern for both self-interest and the interest of future generations.  Using data from a Washington Post survey on environmental attitudes to implement the test, I find evidence of weak altruism.

Data appendix to "Altruism and the Demand for Environmental Quality"

"The Effect of New Technology on Energy Consumption," Resource and Energy Economics, 23(3), July 2001, pp. 215-239.

"What is the Value of Scientific Knowledge? An Application to Global Warming Using the PRICE Model," with William Nordhaus, The Energy Journal, 18(1), January 1997, pp. 1-45.

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.


Last modified January 14, 2015