LSE Logo

The value of using systems mapping to help Ministries of Finance understand the impacts of transformative climate policy

LSE Logo
Download Report PDF

Institution
University of Oxford
Author(s)
Dr. Pete Barbrook-Johnson, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford
Published
Topic Area
Other analytical approaches and methodologies
Citation

University of Oxford (2025) The value of using systems mapping to help Ministries of Finance understand the impacts of transformative climate policy, Contribution to ‘Compendium of Practice from a Global Community of Ministries of Finance and Leading Organizations’, Coalition of Finance Ministers for Climate Action

Copied

While quantitative analysis is typically the dominant approach in economic analysis for climate action, this narrows perception and analysis to topics and issues that are easily quantifiable and for which reliable data is available.

This leaves out many vitally important influences and effects of climate action, such as political pushback and trust, and informal economic sectors, which are complex and dynamic and therefore difficult to model or consider intuitively. In this context, non-quantitative methods can help assess how systems work, including feedback effects, relationships, trade-offs, and synergies, though it is crucial that outputs are directly usable for such methods to be useful.

Key Messages

  • Systems mapping refers to a suite of related methods that all attempt to describe or model a system. A common organizing principle in many (but not all) methods of system mapping is the use of networks of boxes and arrows, representing factors and their causal influence.
  • Two specific types of systems mapping—causal loop diagrams (CLDs) and participatory systems mapping (PSM)—have been used extensively in policy analysis. PSM could be used to show the coverage of a selection of quantitative models (i.e., which variables, factors, and parts of a system are or are not covered by the models), while CLDs could be used to show which key forms of feedback are covered in quantitative models. PSM can also be used to inform a policy’s Theory of Change (as discussed below) or strategic business case.
  • Risk-opportunity analysis (ROA) is an expanded form of cost-benefit analysis (CBA) that is useful in the context of transformational change, where narrow or point estimates can be meaningless. The aim is still to produce quantitative estimates of risks and opportunities but focuses more on distributions of outcomes based on bestand worst-case scenarios, rather than single figures.
  • Within ROA, a CLD exercise can be used to scope out the dominating feedback in a policy area first, before choices on quantitative modeling are made. This can help ensure the identified dynamics are better represented, or where they are missing, the omission is clearer. PSM could be used to build a larger picture of a policy area to help understand what topics are not being modeled quantitatively and the areas in which there is weaker or no evidence.
  • Theory of Change diagrams attempt to describe the “theory of change” of an intervention (i.e., the assumptions, intentions, and causal thinking behind it). They do this by showing the inputs, activities, outputs, outcomes, and long-term impacts of a policy, using a network of boxes and arrows. This can help discipline policy design discussions but has mostly been used ex-post to inform the design of evaluation studies.
Keywords
complexitynon-quantitative methodspolicy designpolicy prioritiessystem dynamics