Modeling and forecasting carbon dioxide emissions in China using Autoregressive Integrated Moving Average (ARIMA) models

Thabani Nyoni and Chipo Mutongi

MPRA Paper from University Library of Munich, Germany

Abstract: This research uses annual time series data on CO2 emissions in China from 1960 to 2017, to model and forecast CO2 using the Box – Jenkins ARIMA approach. Diagnostic tests indicate that China CO2 emission data is I (2). The study presents the ARIMA (1, 2, 1) model. The diagnostic tests further imply that the presented best model is stable and hence acceptable for predicting carbon dioxide emissions in China. The results of the study reveal that CO2 emissions in China are likely to increase and thereby exposing China to a plethora of climate change related challenges. 4 main policy prescriptions have been put forward for consideration by the Chinese government.

Keywords: ARIMA model; China; CO2 emissions (search for similar items in EconPapers)
JEL-codes: C53 Q47 Q52 Q53 Q54 (search for similar items in EconPapers)
Date: 2019-05-06
New Economics Papers: this item is included in nep-cna, nep-ene, nep-env and nep-tra
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:93984

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