Employing the shared socioeconomic pathways to predict CO2 emissions

Predicting CO2 emissions is of significant interest to policymakers and scholars alike. The following article contributes to earlier work by using the recently released "shared socioeconomic pathways" (SSPs) to empirically model CO2 emissions in the future. To this end, I employ in-sample and out-of-sample techniques to assess the prediction accuracy of the underlying model, before forecasting countries' emission rates until 2100. This article makes three central contributions to the literature. First, as one of the first studies, I improve upon the Representative Concentration Pathways (RCPs) by incorporating the SSPs, which did not exist when the RCPs have been released. Second, I calculate predictions and forecasts for a global sample in 1960-2100, which circumvents issues of limited time periods and sample selection bias in previous research. Third, I thoroughly assess the prediction accuracy of the model, which contributes to providing a guideline for prediction exercises in general using in-sample and out-of-sample approaches. This research presents findings that crucially inform scholars and policymakers, especially in light of the prominent 2 degrees C goal: none of the five SSP scenarios is likely to be linked to emission patterns that would suggest achieving the 2 degrees C goal is realistic.