Analysis of the dynamics of carbon pricing: the role of speculation in the Emissions Trading System (ETS)

Abstract

Purpose – To align with the global goal of keeping the temperature rise to well below 2 degrees Celsius, a market-based policy initiative, the "Emissions Trading System (ETS)," is to mitigate climate change. However, the carbon allowances traded at the ETS are held and traded not only by polluting companies, but also emissions non-compliance financial firms. These financial firms though engage in speculation, there has not been any compelling evidence of the extent to which speculation matters in carbon pricing. To bridge this gap, this study is premised on three separate but related essays to: (i) determine the accurate framework for modelling the dynamics of carbon pricing; (ii) determine the extent to which speculation matters in the predictability of carbon pricing; and (iii) determine whether speculation undermines or benefits the emission reduction effect of carbon pricing. Methodology –We employ the GARCH-MIDAS econometric technique to test the hypothesis that an all-inclusive framework that reflects the emission compliance and emissions noncompliance dynamics of the ETS is the most accurate approach to modeling carbon prices. We also employ some verifiable econometric procedures to arrive at the Feasible Quasi Generalised Least Square (FQGLS) as the most appropriate estimator to address some of the biases in the predictability of carbon prices. Findings – A modeling framework that captures both emissions compliance and emissions noncompliance dynamics of the ETS is the most accurate to modeling carbon prices. We find that speculation is a good predictor of carbon prices. We find that both emission compliance and emission non-compliance dynamics of the carbon market matter for the emissions reduction effect of the ETS and for enhancing the accuracy of climate change forecasts. Research Contribution – The literature on emission trading has continued to ignore the speculative behavior of the emissions non-compliance firms in the ETS. As a result, we construct a composite news-based speculation index to simultaneously capture the emissions compliance and emissions non-compliance dynamics of the ETS in a single framework. We provide the literature with a data-driven framework upon which the predictive power of speculation is examined both in the predictability of carbon pricing and in the forecast of emission reductions.