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Causality Between Energy and Output in the Long-Run

Author

Listed:
  • Stern, David

    (Crawford School of Public Policy, Australian National University, Canberra)

  • Enflo, Kerstin

    (Department of Economic History, Lund University)

Abstract

Though there is a very large literature examining whether energy use Granger causes economic output or vice versa this literature is fairly inconclusive. Almost all existing studies use relatively short time series or panels with a relatively small time dimension. Additionally, many recent papers continue to use what seem to be misspecified models. We apply Granger causality and cointegration techniques to a Swedish time series data set on energy and economic growth spanning 150 years to test whether increases in energy use and energy quality have driven economic growth. We show that these techniques are very sensitive to variable definition, choice of additional variables in the model, and sample periods. All of the following appear to make a finding that energy causes growth more likely: using multivariate models, defining variables to better reflect their theoretical definition, using larger samples, and including appropriate structural breaks. However, it is also possible that the relationship between energy and growth has changed over time and that results from recent smaller samples reflect this. Energy prices have a significant causal impact on both energy use and output.

Suggested Citation

  • Stern, David & Enflo, Kerstin, 2013. "Causality Between Energy and Output in the Long-Run," Lund Papers in Economic History 126, Lund University, Department of Economic History.
  • Handle: RePEc:hhs:luekhi:0126
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Energy; macroeconomics; Granger causality; cointegration; causality; time series;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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