Modeling and forecasting the CO2 emissions, energy consumption, and economic growth in Brazil

Hsiao-Tien Pao*, Chung Ming Tsai

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

310 Scopus citations

Abstract

This paper examines the dynamic relationships between pollutant emissions, energy consumption, and the output for Brazil during 1980-2007. The Grey prediction model (GM) is applied to predict three variables during 2008-2013. In the long-run equilibrium emissions appear to be both energy consumption and output inelastic, but energy is a more important determinant of emissions than output. This may be because Brazilian unsustainable land use and forestry contribute most to the country's greenhouse gas emissions. The findings of the inverted U-shaped relationships of both emissions-income and energy consumption-income imply that both environmental damage and energy consumption firstly increase with income, then stabilize, and eventually decline. The causality results indicate that there is a bidirectional strong causality running between income, energy consumption and emissions. In order to reduce emissions and to avoid a negative effect on the economic growth, Brazil should adopt the dual strategy of increasing investment in energy infrastructure and stepping up energy conservation policies to increase energy efficiency and reduce wastage of energy. The forecasting ability of GM is compared with the autoregressive integrated moving average (ARIMA) model over the out-of-sample period between 2002 and 2007. All of the optimal GMs and ARIMAs have a strong forecasting performance with MAPEs of less than 3%.

Original languageEnglish
Pages (from-to)2450-2458
Number of pages9
JournalEnergy
Volume36
Issue number5
DOIs
StatePublished - 1 Jan 2011

Keywords

  • Brazil
  • Dynamic causal relationship
  • Grey prediction model

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