Examining the link between carbon dioxide emissions and the share of industry in GDP: Modeling and testing for the G-7 countries

In this paper, the relationship between per capita CO2 emissions and the share of industrial value added in gross domestic product (GDP) for the G-7 countries is discussed using a novel approach. It is assumed that per capita CO2 emissions are correspondent to the share of industrial value added in GDP. A model is developed using hidden Markov process to search this initial assumption. In the model, the data for industrial share in GDP are assigned to be the observations, while the data for per capita CO2 emissions represent the hidden process, which may be then predicted using the ratio of industrial value added to GDP. The data set covers the period from 1970 to 2008 and the model is tested for the G-7 countries. The study findings show that, except in the case of Canada, the hidden Markov model performs reasonably well in tracking per capita CO2 emissions. The study results provide also a basis for a number of policy implications. - Highlights: → Industrial production is the driving force of CO2 emissions in the G-7 countries. → It is possible to produce CO2 emissions data from the industrial production data. → The hidden Markov model performs well in tracking per capita CO2 emissions. → The method is validated for six of the G-7 countries.