Global Carbon di Oxide Emissions in Hamilton Filter Model

Abstract

The paper examined the cyclical trends, seasonal variation and seasonal adjustment of global CO2 emission from 1970 to 2018 through the application of Hamilton regression filter model. ARIMA (4,0,0) forecasting model for 2030 has been added with the Hamilton filter model and observed that the new model is stable, stationary and significant in which volatility is being minimised and the heteroscedasticity problem is totally disappeared.