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Energy use, international trade and economic growth nexus in Australia: New evidence from an extended growth model

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  • Rahman, Mohammad Mafizur
  • Mamun, Shamsul Arifeen Khan

Abstract

This study investigates the existence of either energy-led growth hypothesis or trade-led growth in Australia for a 53-year period (1960–2012) using a multivariate extended growth model. The econometric techniques used in this study are Autoregressive Distributed Lag (ARDL) bounds testing approach of cointegration, the Granger Causality Test and Impulse Response Functions. The study finds the evidence of no long-run cointegration between the variables of interest. Granger causality test confirms bidirectional causal relationship between international trade and per capita GDP growth, but does not find any Granger causal relationship between energy use and per capita GDP growth. Thus, this study provides an evidence of the trade-led growth hypothesis over the energy-led growth hypothesis for the Australian macroeconomy.

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  • Rahman, Mohammad Mafizur & Mamun, Shamsul Arifeen Khan, 2016. "Energy use, international trade and economic growth nexus in Australia: New evidence from an extended growth model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 806-816.
    • Handle: RePEc:eee:rensus:v:64:y:2016:i:c:p:806-816
    DOI: 10.1016/j.rser.2016.06.039
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    More about this item

    Keywords

    Q4; F1; F64; O4; C32; Energy use; International trade; Economic growth; Australia;
    All these keywords.

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • F1 - International Economics - - Trade
    • F64 - International Economics - - Economic Impacts of Globalization - - - Environment
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • 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

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