Developing and applying input-output analysis tools for assessing sustainability and informing global frameworks

Abstract

This thesis takes a double-materiality approach, first by considering global warming, in quantifying the cost of a climate catastrophe generally and on sectors and regions, using robust, holistic and standardised input-output (IO) analysis. Acting locally at the enterprise level, IO analysis is used with process-based data where possible for comprehensive Climate-and-Nature reporting, from financial and broader impact perspectives. Global frameworks for mandatory human rights and environmental due diligence (mHREDD) are expanding their reach and interoperability, so the question of whether IO analysis is applicable to modern slavery reporting is also analysed. IO analysis is an ideal vehicle for interrogating indicators of additive quantum along the entire inter-industry value chain, so if global modern-day slavery could be reliably estimated then it could be used to trace supply-chain risk. However, no global data could be recommended for the calculation of modern-slavery multipliers but this research recommends tailored risk analysis in areas supported by rich data. To apply IO analysis across the value chain for established indicators, a hybrid-[lifecycle assessment] LCA-IO analysis framework is developed to extend downstream IO analysis to the enterprise level using estimated income per sector for the reporting entity. Next, a model is built that includes income and expenses; IO analysis is then applied to reporting in line with the International Sustainability Standards Board generally, as well as across scope-3 Greenhouse Gas Protocol categories and biodiversity-related indicators for the Taskforce on Nature-related Financial Disclosures.