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Forecasting The Path of U.S. CO_2 Emissions Using State-Level Information

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  • Maximilian Auffhammer

    (University of California, Berkeley and NBER)

  • Ralf Steinhauser

    (Australian National University)

Abstract

We compare the most common reduced-form models used for emissions forecasting, point out shortcomings, and suggest improvements. Using a U.S. state-level panel data set of CO_2 emissions, we test the performance of existing models against a large universe of potential reduced-form models. We find that leading models in the literature, as well as models selected based on an emissions per capita loss measure or different in-sample selection criteria, perform significantly worse compared to the best model chosen based directly on the out-of-sample loss measure defined over aggregate emissions. © 2011 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Maximilian Auffhammer & Ralf Steinhauser, 2012. "Forecasting The Path of U.S. CO_2 Emissions Using State-Level Information," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 172-185, February.
    • Handle: RePEc:tpr:restat:v:94:y:2012:i:1:p:172-185
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    References listed on IDEAS

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    1. Holtz-Eakin, Douglas & Selden, Thomas M., 1995. "Stoking the fires? CO2 emissions and economic growth," Journal of Public Economics, Elsevier, vol. 57(1), pages 85-101, May.
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    More about this item

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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