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Lessons from Patents: Using Patents To Measure Technological Change in Environmental Models

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  • David Popp

Abstract

When studying solutions to long-term environmental problems such as climate change, it is important to consider the role that technological change may play. Nonetheless, to date few economic models of climate change explicitly model the link between policy and technological change. There is a growing body of evidence that the incentives offered by prices and environmental regulations have a strong influence on both the creation and adoption of new technologies. In several recent papers, I have used patent data to examine the links between environmental policy and technological change. In addition, I have used the results of this research to calibrate the ENTICE model (for Endogenous Technological change) of climate change, which links energy-related R&D to changes in the price of carbon. Drawing on my experiences from empirical studies on innovation and from modeling the climate change problem, in this paper I review some of the key lessons from recent empirical work using patents to study environmental innovation and diffusion, and discuss its implications for modeling climate change policy. I conclude by offering suggestions for future research.

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  • David Popp, 2003. "Lessons from Patents: Using Patents To Measure Technological Change in Environmental Models," NBER Working Papers 9978, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:9978
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    Cited by:

    1. Nadia Ayari & Szabolcs Blazsek & Pedro Mendi, 2012. "Renewable energy innovations in Europe: a dynamic panel data approach," Applied Economics, Taylor & Francis Journals, vol. 44(24), pages 3135-3147, August.
    2. Bu, Maoliang & Qiao, Zhenzi & Liu, Beibei, 2020. "Voluntary environmental regulation and firm innovation in China," Economic Modelling, Elsevier, vol. 89(C), pages 10-18.
    3. Gillingham, Kenneth & Newell, Richard G. & Pizer, William A., 2008. "Modeling endogenous technological change for climate policy analysis," Energy Economics, Elsevier, vol. 30(6), pages 2734-2753, November.
    4. Brutschin, Elina & Fleig, Andreas, 2016. "Innovation in the energy sector – The role of fossil fuels and developing economies," Energy Policy, Elsevier, vol. 97(C), pages 27-38.
    5. David Popp, 2004. "R&D Subsidies and Climate Policy: Is There a "Free Lunch"?," NBER Working Papers 10880, National Bureau of Economic Research, Inc.
    6. Clark, Matthew, 2005. "Corporate environmental behavior research: informing environmental policy," Structural Change and Economic Dynamics, Elsevier, vol. 16(3), pages 422-431, September.
    7. Otto, Vincent M. & Kuosmanen, Timo & van Ierland, Ekko C., 2006. "Estimating Feedback Effect in Technical Change: A Frontier Approach," Knowledge, Technology, Human Capital Working Papers 12086, Fondazione Eni Enrico Mattei (FEEM).

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    JEL classification:

    • Q33 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Resource Booms (Dutch Disease)
    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General

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