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Where does energy R&D come from? Examining crowding out from energy R&D

Open access
Popp, David, Newell, Richard·2012·Energy Economics

Abstract

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.

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Cites

  • Instrumental Variables Regression with Weak Instruments

    Staiger, D., & Stock, J. (1994) · doi:10.3386/t0151 · Cited by 5,302 · cited 3×

    “However, in columns 1 and 3, theWald F statistic based on the Kleibergen-Paap rk statistic is less than the “rule of thumb” of 10, suggestingweak instruments (Baumet al., 2007; Staiger and Stock, 1997).”
    BackgroundMethodInfluential

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Metadata

Authors
Popp, D., & Newell, R.
Venue
Energy Economics
Publisher
Elsevier BV
Published
2012-07
Volume
34
Issue
4
Pages
980-991
ISSN
0140-9883 (ISSN-L)
OpenAlex
W2052924199
Cited by
233
References
1
FWCI
21.74
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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CoChat. (2026). Citation check: Where does energy R&D come from? Examining crowding out from energy R&D. https://app.cochat.ai/papers/10.1016/j.eneco.2011.07.001
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Popp, D., & Newell, R. (2012). Where does energy R&D come from? Examining crowding out from energy R&D. Energy Economics. https://doi.org/10.1016/j.eneco.2011.07.001

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