Analyzing Co2 emission in developing countries using auto regression and auto regression walk forward: A time series approach

Abstract

With the expansion of global industry and human civilization, the use of fossil fuels is increasing at an alarming pace, resulting in severe environmental problems, including the greenhouse effect. Carbon dioxide is a significant greenhouse gas that contributes to the greenhouse effect. According to research, the mean annual temperature of the Earth's surface, averaged across the whole globe, has been rising over the last 200 years. In this rapid growth of carbon emission, the developing countries have been increasing their share into the bucket. Much research has been conducted on developed countries but little has been done with developing countries. This paper utilizes the datasets on Carbon emission in India and Bangladesh; two developing countries to analyze the effect of expanding industrialization on carbon emission. This paper analyzes Carbon Emissions using the dataset of the year 1960 to 2018. The main objective of this paper is to analyze Carbon Emissions using time series algorithms. Autoregression is a popular method of analyzing and forecasting data. The paper focuses on Auto Regression and Autoregression with walk forward method to analyze carbon emission rates in developing countries such as Bangladesh, India.