Forecasting The Path of U.S. CO_2 Emissions Using State-Level Information
AbstractWe 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.
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Bibliographic InfoArticle provided by MIT Press in its journal Review of Economics and Statistics.
Volume (Year): 94 (2012)
Issue (Month): 1 (February)
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Web page: http://mitpress.mit.edu/journals/
Other versions of this item:
- Maximillian Auffhammer & Ralf Steinhauser, 2010. "Forecasting the Path of USS CO2 Emissions Using State-Level Information," ANU Working Papers in Economics and Econometrics, Australian National University, College of Business and Economics, School of Economics 2010-526, Australian National University, College of Business and Economics, School of Economics.
- 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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