Time Series Analysis for the Dynamic Relationship between an Enterprise’s Business Growth and Carbon Emission in Taiwan

Abstract

<jats:p>Since the Paris Agreement came into effect in 2016, governments worldwide have established goals for future carbon emission reduction. Enterprises and governments have begun to pay attention to the management of carbon emission. This study explored the dynamic relationship between business growth and carbon emission performance by constructing and using a time series model to predict the trend of carbon emission. The time series method (ADF unit root test, cointegration test and VAR model etc.) was adopted to investigate 805 companies listed on the Taiwan Stock Exchange from 2012 to 2017 as the sample of this study. The carbon emission performance variables include: total carbon emission, annual increase of carbon emission, and annual increase rate of carbon emission. The business growth variables include: growth rate, stability of growth, and years of establishment. The results showed a long-term dynamic relationship between business growth and carbon emission performance. Therefore, using the time series method can assist enterprises in developing green strategies, strengthen carbon emission prediction and management capacities, reduce operating costs and risks, and actively achieve the ideal of sustainable development.</jats:p>

Climate Change-Greenhouse Gas Emissions Analysis and Forecast in Romania

“…In their research, Ding et al [37] explored the dynamic relationship between business growth and carbon emissions performance by constructing and using a time series model to predict the trend of carbon emissions. They used the time series method (ADF unit root test, cointegration test, and VAR model) to investigate 805 companies listed on the Taiwan Stock Exchange from 2012 to 2017.…”