Understanding SDG Interlinkages and Predictive Analysis for Sustainable Development

Summary

This project represents a significant step forward in the systematic analysis of Sustainable Development Goals (SDGs) targets and indicators, specifically within the context of the State of the Environment (SoE) reporting. The aim was to apply scientific assessments to support the Commissioner for Environment Sustainability Victoria by developing methodologies that highlight the interlinkages and predictive capabilities of selected SDG targets and indicators.

Project Phases and Objectives
The project was structured into comprehensive work packages, focusing on understanding the interlinkages among SDG targets and performing predictive analysis. Initially, the project aimed to develop methods for reporting on the connectivity of the SDG targets, which is essential for organising the SoE 2023 report. This involved identifying a subset of the 169 SDG targets that are most relevant for this purpose.

The subsequent focus was on predictive analysis, crucial for assessing causal interlinkages that inform decision-making processes. Various methods were explored, including qualitative, semi-quantitative (matrix/network analysis), quantitative (statistical correlation), and dynamic quantitative (modelling). These methods help in understanding how different SDG targets influence each other, thus aiding in policy formulation and prioritization.