A spatial panel data approach to estimating U.S. state-level energy emissions
We take advantage of a long panel data set to estimate the relationship between U.S. state-level carbon dioxide (CO2) emissions, economic activity, and other factors. We specify a reduced-form energy demand model to account for energy consumption activities that drive energy-related emissions. We contribute to the literature by exploring several spatial panel data models to account for spatial dependence between states. Estimation results and rigorous diagnostic analysis suggest that: (1) economic distance plays a role in intra- and inter-state CO2 emissions; and (2) there are statistically significant, positive economic spillovers and negative price spillovers to state-level emissions.
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- Auffhammer, Maximilian & Steinhauser, Ralf, 2006.
"The future trajectory of US CO2 emissions : the role of state vs. aggregate information,"
CUDARE Working Paper Series
1015, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
- Auffhammer, Maximilian & Steinhauser, Ralf, 2006. "The Future Trajectory of US CO2 Emissions: The Role of State vs. Aggregate Information," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt4878j5w0, Department of Agricultural & Resource Economics, UC Berkeley.
- Hausman, Jerry, 2015.
"Specification tests in econometrics,"
Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
- Won Kim, Chong & Phipps, Tim T. & Anselin, Luc, 2003.
"Measuring the benefits of air quality improvement: a spatial hedonic approach,"
Journal of Environmental Economics and Management,
Elsevier, vol. 45(1), pages 24-39, January.
- Kim, Chong Won & Phipps, Tim T. & Anselin, Luc, 1998. "Measuring The Benefits Of Air Quality Improvement: A Spatial Hedonic Approach," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20959, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Itkonen, Juha V.A., 2012. "Problems estimating the carbon Kuznets curve," Energy, Elsevier, vol. 39(1), pages 274-280.
- Auffhammer, Maximilian & Carson, Richard Taylor, 2004.
"Forecasting the path of China's CO2 emissions using province level information,"
CUDARE Working Paper Series
0971, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy, revised 2007.
- Auffhammer, Maximilian & Carson, Richard T., 2008. "Forecasting the path of China's CO2 emissions using province-level information," Journal of Environmental Economics and Management, Elsevier, vol. 55(3), pages 229-247, May.
- Auffhammer, Maximilian & Carson, Richard T., 2007. "Forecasting the Path of China's CO2 Emissions Using Province Level Information," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6d28j8rg, Department of Agricultural & Resource Economics, UC Berkeley.
- Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
- Debarsy, Nicolas & Ertur, Cem, 2010.
"Testing for spatial autocorrelation in a fixed effects panel data model,"
Regional Science and Urban Economics,
Elsevier, vol. 40(6), pages 453-470, November.
- Nicolas DEBARSY (CERPE De Namur) & Cem ERTUR, 2009. "Testing for Spatial Autocorrelation in a Fixed Effects Panel Data Model," LEO Working Papers / DR LEO 1546, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
- Nicolas Debarsy & Cem Ertur, 2009. "Testing for Spatial Autocorrelation in a Fixed Effects Panel Data Model," Post-Print halshs-00414133, HAL.
- Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
- P Burridge, 1981.
"Testing for a common factor in a spatial autoregression model,"
Environment and Planning A,
Pion Ltd, London, vol. 13(7), pages 795-800, July.
- P Burridge, 1981. "Testing for a Common Factor in a Spatial Autoregression Model," Environment and Planning A, SAGE Publishing, vol. 13(7), pages 795-800, July.
- Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-61, May.
- Richard T. Carson, 2010. "The Environmental Kuznets Curve: Seeking Empirical Regularity and Theoretical Structure," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 4(1), pages 3-23, Winter.
- Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2002. "Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption," Economics Letters, Elsevier, vol. 76(3), pages 375-382, August.
- Conley, Timothy G & Ligon, Ethan, 2002. "Economic Distance and Cross-Country Spillovers," Journal of Economic Growth, Springer, vol. 7(2), pages 157-87, June.
- Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
- J. Barkley Rosser, 2009. "Introduction," Chapters, in: Handbook of Research on Complexity, chapter 1 Edward Elgar Publishing.
- Maddala, G S, et al, 1997. "Estimation of Short-Run and Long-Run Elasticities of Energy Demand from Panel Data Using Shrinkage Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 90-100, January.
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