Maria Borga, Achille Pegoue, Mr. Gregory M Legoff, Alberto Sanchez Rodelgo, Dmitrii Entaltsev, and Kenneth Egesa
This paper presents estimates of the carbon emissions of FDI from capital formation funded by FDI and the production of foreign-controlled firms. The carbon intensity of capital formation financed by FDI has trended down, driven by reductions in the carbon intensity of electricity generation. Carbon emissions from the operations of foreign-controlled firms are greater than those from their capital formation. High emission intensities were accompanied by high export intensities in mining, transport, and manufacturing. Home country policies to incentivize firms to meet strict emissions standards in both their domestic and foreign operations could be important to reducing emissions globally.
This issue of the IMF Research Perspective looks at the inter-connectedness of the world economic system and how diverse shocks can affect global supply chains. The articles in this issue track the way COVID-19 triggered disruptions in the supply chain and explains why trade networks are so difficult to disentangle. However, the pandemic is not the only event affecting global supply chains; cross-border spillovers of technology wars and natural disasters are other factors to consider. The overarching message from these articles is clear: there is a need for international cooperation to deal with the consequences of these shocks—whether it is ending the COVID-19 pandemic or mitigating climate change.
To reach the global net-zero goal, the level of carbon emissions has to fall substantially at speed rarely seen in history, highlighting the need to identify structural breaks in carbon emission patterns and understand forces that could bring about such breaks. In this paper, we identify and analyze structural breaks using machine learning methodologies. We find that downward trend shifts in carbon emissions since 1965 are rare, and most trend shifts are associated with non-climate structural factors (such as a change in the economic structure) rather than with climate policies. While we do not explicitly analyze the optimal mix between climate and non-climate policies, our findings highlight the importance of the nonclimate policies in reducing carbon emissions. On the methodology front, our paper contributes to the climate toolbox by identifying country-specific structural breaks in emissions for top 20 emitters based on a user-friendly machine-learning tool and interpreting the results using a decomposition of carbon emission ( Kaya Identity).