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What If Energy Time Series Are Not Independent? Implications For Energy-GDP Causality Analysis

  • Stephan B. Bruns
  • , C Gross
  • Max Planck Institute of Economics

Research output: Contribution to journal › Article › peer-review

17   Link opens in a new tab Citations (SciVal)

Abstract

Time series of electricity, petroleum products, and renewables are found to be highly correlated with total energy consumption. Applying this insight to the huge literature on energy-GDP causality explains that the results of total energy-GDP causality tests frequently coincide with the results of energy type-GDP tests. Using the test by Toda-Yamamoto in combination with a cointegration-based testing approach, we detect such cases of concordance for 92% of the countries in our sample of 65 countries. We infer that drawing specific economic conclusions with regard to single types of energy from bivariate causality analysis is difficult.
Original languageEnglish
Pages (from-to)753-759
Number of pages7
JournalEnergy Economics
Volume40
DOIs
Publication statusPublished - Nov 2013

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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