Version 1
: Received: 15 August 2023 / Approved: 16 August 2023 / Online: 17 August 2023 (08:44:48 CEST)
How to cite:
Isah, K.; Raheem, I.; Adelakun, J. Testing the Emissions Reduction Effect of Carbon Pricing: A Predictive Analysis of the Role of Speculation. Preprints2023, 2023081249. https://doi.org/10.20944/preprints202308.1249.v1
Isah, K.; Raheem, I.; Adelakun, J. Testing the Emissions Reduction Effect of Carbon Pricing: A Predictive Analysis of the Role of Speculation. Preprints 2023, 2023081249. https://doi.org/10.20944/preprints202308.1249.v1
Isah, K.; Raheem, I.; Adelakun, J. Testing the Emissions Reduction Effect of Carbon Pricing: A Predictive Analysis of the Role of Speculation. Preprints2023, 2023081249. https://doi.org/10.20944/preprints202308.1249.v1
APA Style
Isah, K., Raheem, I., & Adelakun, J. (2023). Testing the Emissions Reduction Effect of Carbon Pricing: A Predictive Analysis of the Role of Speculation. Preprints. https://doi.org/10.20944/preprints202308.1249.v1
Chicago/Turabian Style
Isah, K., Ibrahim Raheem and Johnson Adelakun. 2023 "Testing the Emissions Reduction Effect of Carbon Pricing: A Predictive Analysis of the Role of Speculation" Preprints. https://doi.org/10.20944/preprints202308.1249.v1
Abstract
Despite providing some critical financial services to support the operation of Emissions Trading Systems (ETS), such as increasing market liquidity and price visibility and allowing operators to hedge against future fluctuations, there is growing concern about the potential threat of financial actors' speculation behaviour to the ETS's effectiveness. To confirm or alleviate the fear associated with such concern, we employ both ex-post and ex-ante approaches to determine the role of speculation in the emission reduction effect of the ETS and its forecasting power in predicting climate change. In addition to confirming carbon prices and the speculation behaviour of the emissions non-compliance actors in the ETS as accurate predictors of climate change, we also show that they both matter in the emission reduction effect of the ETS. We use several verifiable econometric approaches to select the Feasible Quasi Generalised Least Squares (FQGLS) as the best estimator for addressing some of the biases in climate change predictability. We demonstrate that a predictive model combining the complementing dynamics of the EST emissions compliance and emissions non-compliance features forecasts climate change more accurately. We demonstrate the robustness of our findings for both in-sample and out-of-sample forecasts and across different forecast horizons by using alternative approaches to evaluate forecast performance.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
