Greenhouse Gas Emissions Determinants Using Empirical Datasets in the Southeast Asian Region

  • Juvyneil E. Cartel Chemical Engineering Department, Eastern Visayas State University, Tacloban City, 6500 Philippines
  • Evelyn A. Cardoso Chemical Engineering Department, Eastern Visayas State University, Tacloban City, 6500 Philippines
Keywords: panel data analysis, GHG emissions, regression model


Greenhouse gas (GHG) emissions of the ten-member countries of Association of Southeast Asian Nations (ASEAN) were determined using panel data analysis. The longitudinal data were subjected to sensitivity analysis, multiple correlation, and regression analyses to examine statistical correlation among the identified variables. The findings revealed that the urban population is significantly associated with GHG emissions mostly induced by industrial development. Meanwhile, forest cover and population density among the member countries statistically influenced GHG emissions. Likewise, the urban population showed direct bearing with GHG emission while access to clean fuels, forest cover and population density inversely correlate with GHG emissions. In large part, forest cover influenced the dynamic condition of GHG emissions based on sensitivity analysis. The resulting regression model further confirmed that forest cover essentially contributed to the minimizing effect of GHG emissions. However, the model explained only 37.15% of the deviance in the prediction of total GHG. In conclusion, forest cover programs in the member countries played as the primary determinant of GHG emissions, which are limited to the carrying capacity of the forest lands. Nonetheless, other determinants should not be neglected for they still contribute to the increase of GHG emission level. To reduce the level of GHG emissions, ASEAN governments must formulate policies and programs that favor access to fuels and people awareness on reforestation initiatives. Detrimental human activities related to GHG emissions in the urban area have to be reduced in order to curtail GHG emissions.