Causality indices for bivariate time series data: A comparative review of performance

Journal article

Countries worldwide are leveraging the 2030 Agenda and its 17 Sustainable Development Goals (SDGs) for building a more resilient and sustainable future. One solution in this endeavour is transitioning towards a bioeconomy (BE), utilizing renewable resources and low-carbon value chains to meet food, energy, and materials demands. However, BE is neither inherently circular nor sustainable, compromising SDGs’ progress. Therefore, we conducted a detailed ex-post analysis using correlation, transfer entropy, and network analysis to understand the complex interactions between BE and SDGs. Moving beyond correlation, we explored the directional influence of interactions within the BE-SDG nexus. Our findings reveal a robust bidirectional influence between 19 BE criteria and 109 SDG targets across all goals among 48 European countries. While BE can drive progress toward SDGs, a balanced distribution of synergies and trade-offs constrains its impact. Collaborative efforts among European countries would effectively drive towards achieving both BE and SDGs. SDG 13 has positive influences from lowered fossil fuel emissions and negative ones due to land use changes and intensified agriculture, which releases stored carbon. Similarly, SDG 15 emerges as a positive influence, as healthy ecosystem services foster a resilient BE. Despite efforts towards SDG 12, Europe's unsustainable consumption impedes BE supply chains. While BE practices are intended to accelerate sustainability, they fall short of playing a transformational role in achieving the SDGs. A shift towards a cohesive, collaborative strategy that leverages synergies and mitigates trade-offs can enhance the BE's impact, advancing Europe closer to achieving the 2030 Agenda

Authors: Edinburgh, T; Eglen, SJ; Ercole, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: American Institute of Physics
• Journal: Chaos: An Interdisciplinary Journal of Nonlinear Science
• Volume: 31
• Issue: 8
• Pages: 083111-083111
• Publication date: 2021-08-01
• DOI: 10.1063/5.0053519
• EISSN: 1089-7682
• ISSN: 1054-1500
• Language: English
• Keywords: Econometrics; Geology; Series (stratigraphy); Time series; Bivariate analysis; Causality (physics); Bivariate data; Statistics; Mathematics