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Assessing Investment in Future Landsat Instruments: The Example of Forest Carbon Offsets

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  • Macauley, Molly K.

    (Resources for the Future)

  • Shih, Jhih-Shyang

    (Resources for the Future)

Abstract

We extend the theory of quality-adjusted expenditure indices to estimate benefits from public investment. In particular, we model the selection of new instruments (in the form of remote-sensing devices) to enhance the longest-operating U.S. satellite-based land-observing program, Landsat. We then apply the model to the use of Landsat in measuring global forest carbon sequestration. Improving measurement of the role of forests in storing carbon has become a prominent concern in climate policy. By characterizing the value of Landsat data in forest measurement, the expenditure function allows us to help inform public investment decisions in the satellite system. The expenditure function also makes explicit the sensitivity of the selection of instruments for the satellites to the value of Landsat information, thus linking instrument choice explicitly to policy design.

Suggested Citation

  • Macauley, Molly K. & Shih, Jhih-Shyang, 2010. "Assessing Investment in Future Landsat Instruments: The Example of Forest Carbon Offsets," RFF Working Paper Series dp-10-14, Resources for the Future.
    • Handle: RePEc:rff:dpaper:dp-10-14
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    File URL: http://www.rff.org/RFF/documents/RFF-DP-10-14.pdf
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    References listed on IDEAS

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    1. Anger, Niels & Dixon, Alistair & Livengood, Erich, 2009. "Interactions of Reduced Deforestation and the Carbon Market: The Role of Market Regulations and Future Commitments," ZEW Discussion Papers 09-001, ZEW - Leibniz Centre for European Economic Research.
    2. Brian C. Murray & Bruce A. McCarl & Heng-Chi Lee, 2004. "Estimating Leakage from Forest Carbon Sequestration Programs," Land Economics, University of Wisconsin Press, vol. 80(1), pages 109-124.
    3. Kim, Man-Keun & McCarl, Bruce A. & Murray, Brian C., 2008. "Permanence discounting for land-based carbon sequestration," Ecological Economics, Elsevier, vol. 64(4), pages 763-769, February.
    4. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    5. MacAuley, Molly K. & Shih, Jhih-Shyang & Aronow, Emily & Austin, David H. & Bath, Tom & Darmstadter, Joel, 2002. "Measuring the Contribution to the Economy of Investments in Renewable Energy: Estimates of Future Consumer Gains," Discussion Papers 10588, Resources for the Future.
    6. Bresnahan, Timothy F, 1986. "Measuring the Spillovers from Technical Advance: Mainframe Computers inFinancial Services," American Economic Review, American Economic Association, vol. 76(4), pages 742-755, September.
    7. Macauley, Molly K., 2009. "Earth Observations in Social Science Research for Management of Natural Resources and the Environment: Identifying the Contribution of the U.S. Land Remote Sensing (Landsat) Program," RFF Working Paper Series dp-09-01, Resources for the Future.
    8. Pfaff, Alexander S. P. & Kerr, Suzi & Hughes, R. Flint & Liu, Shuguang & Sanchez-Azofeifa, G. Arturo & Schimel, David & Tosi, Joseph & Watson, Vicente, 2000. "The Kyoto protocol and payments for tropical forest:: An interdisciplinary method for estimating carbon-offset supply and increasing the feasibility of a carbon market under the CDM," Ecological Economics, Elsevier, vol. 35(2), pages 203-221, November.
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    Cited by:

    1. Molly Macauley & Roger Sedjo, 2011. "Forests in climate policy: technical, institutional and economic issues in measurement and monitoring," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 16(5), pages 499-513, June.
    2. Nathan Richardson & Molly Macauley, 2012. "Forest Carbon Economics: What We Know, What We Do Not And Whether It Matters," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 1-18.

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    More about this item

    Keywords

    value of information; satellite data; forests; carbon; sequestration; Landsat;
    All these keywords.

    JEL classification:

    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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