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Innovation without magic bullets: Stock pollution and R&D sequences

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  • Goeschl, Timo
  • Perino, Grischa

Abstract

We study the optimal R&D trajectory in a setting where new technologies are never perfect backstops in the sense that there is no perfectly clean technology that eventually solves the pollution problem once and for all. New technologies have stings attached, i.e. each emits a specific stock pollutant. Damages are convex in individual pollution stocks but additive across stocks, creating gains from diversification. The research and pollution policies are tightly linked in such a setting. We derive the optimal pollution path and R&D program. Pollution stocks overshoot and in the long run all available technologies produce. Research is sequential and the optimal portfolio of technologies is finite.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Environmental Economics and Management.

Volume (Year): 54 (2007)
Issue (Month): 2 (September)
Pages: 146-161

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Handle: RePEc:eee:jeeman:v:54:y:2007:i:2:p:146-161

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Web page: http://www.elsevier.com/locate/inca/622870

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References

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  1. Marc Baudry, 2000. "Joint Management of Emission Abatement and Technological Innovation for Stock Externalities," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 16(2), pages 161-183, June.
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Cited by:
  1. Mads Greaker & Lise-Lotte Pade, 2008. "Optimal CO2 abatement and technological change. Should emission taxes start high in order to spur R&D?," Discussion Papers 548, Research Department of Statistics Norway.
  2. Grischa Perino, 2008. "The merits of new pollutants and how to get them when patents are granted," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 40(3), pages 313-327, July.
  3. Goeschl, Timo & Heyen, Daniel & Moreno-Cruz, Juan, 2013. "The Intergenerational Transfer of Solar Radiation Management Capabilities and Atmospheric Carbon Stocks," Working Papers 0540, University of Heidelberg, Department of Economics.
  4. Rob Hart, 2009. "Bad Eggs, Learning-by-doing, and the Choice of Technology," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 42(4), pages 429-450, April.
  5. Ralph Winkler, 2008. "Optimal control of pollutants with delayed stock accumulation," CER-ETH Economics working paper series 08/91, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
  6. Gerlagh, Reyer & Kverndokk, Snorre & Rosendahl, Knut Einar, 2014. "The optimal time path of clean energy R&D policy when patents have finite lifetime," Journal of Environmental Economics and Management, Elsevier, vol. 67(1), pages 2-19.
  7. Färnstrand Damsgaard, Erika, 2012. "Exhaustible resources, technology choice and industrialization of developing countries," Resource and Energy Economics, Elsevier, vol. 34(3), pages 271-294.
  8. Krysiak, Frank C., 2011. "Environmental regulation, technological diversity, and the dynamics of technological change," Journal of Economic Dynamics and Control, Elsevier, vol. 35(4), pages 528-544, April.

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