Forecasting Carbon Dioxide Emission and Sustainable Economy: Evidence and Policy Responses

Phatchapa Boontome, Apichit Therdyothin, Jaruwan Chontanawat

Abstract


Forecasting CO2 emissions have been of importance as it could help the government to improve energy policies and plans. In this paper, we forecast the future carbon dioxide emission (CO2) through estimating the short and long-run causal correlation between CO2 emission, economic growth (Y), oil price (OP), consumption of renewable (RE), energy (E) in Thailand for the period 1990 to 2016 using autoregressive distributed lag (ARDL) approach. The result indicates that in the long term, consumption of renewable, energy and oil price increase of 1% each decrease CO2 emission by 5.66%, 14.73% and 5.07% respectively. The result of forecasting CO2 emission base on variance decompositions found that in the future next 14-year decrease CO2 emission 30.17%, which is higher than the target set to reduce CO2 emissions by 20-25% within 2030 year. The country should be adjust the structure of energy use to reduce pollution. 

Keywords: Forecasting, Carbon dioxide emission, Variance Decomposition

JEL Classifications: P28, Q42, Q43, Q47, Q48

DOI: https://doi.org/10.32479/ijeep.7918


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