Why carbon offsets may fail in complex systems: A causal inference perspective

Social-ecological system dynamics present a fundamental challenge to the attribution of changes in carbon stocks to actions taken by carbon offset sellers. We illustrate this challenge by demonstrating theoretical limitations to causal attribution in two cases from Brazil and India. We show that carbon outcomes in these nature-based carbon offset projects emerge from non-linear and independent dynamics that are the result of the inherent complexity of social-ecological systems, where large numbers of variables jointly influence causal processes. This creates high levels of uncertainty about the causes of outcomes, and thus makes it very difficult to attribute changes in carbon storage to specific causes, such as offset-funded programs. Furthermore, the predominant solution to this problem suggested in the literature, improved causal inference methods, fails to address the challenge because these methods are designed to estimate average effects across many cases, not to measure causality in specific cases. Even well-designed and resourced projects, such as our two cases, must demonstrate their own measurable impact to serve as offsets, and our analysis suggests that current methods are unable to overcome the joint challenges of causal complexity and methods that estimate average, not individual effects. The need for offsets to demonstrate individual causality makes them quite different from analogous conservation tools such as Payment for Ecosystem Services (PES), highlighting why project-based offsetting consistently struggles to meet the expectations of credibility. To achieve effective climate change mitigation, policymakers need to focus on policies that do not depend on inherently uncertain causal attribution.