Measuring and Integrating Non-Financial Parameters in Project Decision Making
Extractive industry investments are oftentimes divisive. Those that support a project, will likely emphasize the benefits resulting from tax revenues and employment. Those that oppose the project, will often highlight the adverse impacts on the environment and impacted communities.
To date, this debate can be informed by several tools. On the benefit side, stakeholders can use fiscal analyses to forecast tax revenues and multiplier tools to estimate job and economy-wide impacts. On the negative impact side, environmental, social and human right impact assessments are primarily used to analyze and mitigate the consequences that the proposed project may have on nature and impacted communities.
However, these assessments are made in isolation using different matrices, making them difficult to compare. CCSI is seeking to advance the integration of non-financial costs and benefits in fiscal assessments to better inform the debate. The Modelling for Sustainable Development: New Decision for a New Age book, which was co-authored by CCSI, outlines how to take a more holistic approach to modelling in order make better informed decisions.
At the EITI Global Conference in 2019, CCSI with its partners, NRGI and Engineers Without Borders – Mining Shared Value, hosted a side-event to present the work to date and start the conversation with other stakeholders about how to advance the thinking and knowledge sharing in this space. This blog reports on the outcomes of the event. It was agreed that as a first step a listserv would be created, where experts and interested stakeholders can share experiences, knowledge and tools on this topic. Please reach out to firstname.lastname@example.org if you would like to be added to this listserv. The aim is to create a community of practice that shares experiences and can provide guidance to stakeholders interested in doing a more detailed and integrated assessment than the more traditional analysis of revenue flows.