Robust choice of design standard
Design options are tested across a set of climate, demand and cost scenarios to find those that perform acceptably in most futures, rather than best in one.
GRA · Development Finance Nexus
Spatial financeWhere capital meets hazard, exposure and transition
Decision analysis for development finance
Decision analysis under uncertainty structures choices that development finance institutions face when outcomes are uncertain and objectives conflict: which projects to prepare, how to allocate risk, when to act and when to keep options open. It makes trade-offs and assumptions visible to the decision holders.
01Contents
Decision analysis for development finance in five parts.
02Application
What decision analysis under uncertainty does here.
Decision analysis under uncertainty provides structured methods for choosing among options when outcomes are uncertain and objectives conflict. It makes trade-offs and value judgements explicit. In development finance, critical infrastructure and economic development, decision analysis helps choose actions that perform acceptably across interconnected risks and uncertain futures. It clarifies when to act now and when to keep options open. The canonical description is on the STEM Commons.
Multi-criteria pipeline screening
Candidate projects are scored against stated criteria such as development impact, readiness, fiscal cost and safeguard risk, with weights set and owned by the deciding institution.
Value of further diligence
Before commissioning more studies, the analysis asks whether the information could change the decision, and by how much, so that diligence effort follows the uncertainty that matters.
03Monitor
Uncertainty analysis.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Uncertainty analysis
Development finance · Decision analysis for development · Run R-9648
Sensitivity rankedGRA · Development Finance Nexus
Total-order sensitivity
Output distribution
Inputs
| Pipeline value | Beta | local bn, stated | expert elicitation |
| Projects screened for climate risk | Uniform | of pipeline, stated | expert elicitation |
| Safeguard incidents | Normal | incidents, stated | expert elicitation |
| Disbursement ratio | Uniform | of commitments, stated | expert elicitation |
04Data
What the method consumes.
Datasets and records used by decision analysis under uncertainty on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Scenario sets for climate, demand and prices | Futures to test options against | MODELLED |
| Cost and benefit estimates | Option performance | ESTIMATED |
| Expert elicitation | Probabilities where data are thin | DECLARED |
| Stakeholder preference surveys | Weights for competing objectives | REPORTED |
05Scenario model
Policy paths and what they do to the risk.
How three families of instruments change a risk outcome over time with adoption lags, coverage and compliance, the policy scenarios behind transition and physical risk assessments. Scenario: named assumptions about the future, not a forecast.
Controls
- Baseline trend of the outcome
- 2.0% a year
- Coverage of the instrument
- 70%
- Compliance
- 75%
- Effect size, against the teaching value
- 100%
- Years ahead
- 20 years
Readouts
- Largest reduction at the horizon
- Regulation
- Its reduction against the baseline
- 21%
Numbers, methods and sources
| Year | Baseline | Regulation | Economic incentive | Information and capacity |
|---|---|---|---|---|
| 0 | 100.0 | 99.5 | 98.8 | 99.1 |
| 1 | 102.0 | 101.2 | 100.1 | 99.8 |
| 2 | 104.0 | 102.5 | 101.1 | 99.9 |
| 3 | 106.1 | 103.5 | 101.6 | 100.0 |
| 4 | 108.2 | 103.7 | 101.8 | 100.7 |
| 5 | 110.4 | 103.2 | 101.7 | 102.1 |
| 6 | 112.6 | 102.0 | 101.6 | 103.9 |
| 7 | 114.9 | 100.4 | 101.6 | 105.9 |
| 8 | 117.2 | 99.2 | 102.1 | 108.0 |
| 9 | 119.5 | 98.6 | 102.9 | 110.1 |
| 10 | 121.9 | 98.9 | 104.2 | 112.3 |
| 11 | 124.3 | 99.7 | 105.7 | 114.5 |
| 12 | 126.8 | 101.1 | 107.4 | 116.8 |
| 13 | 129.4 | 102.7 | 109.4 | 119.2 |
| 14 | 131.9 | 104.5 | 111.4 | 121.6 |
| 15 | 134.6 | 106.5 | 113.5 | 124.0 |
| 16 | 137.3 | 108.5 | 115.7 | 126.5 |
| 17 | 140.0 | 110.7 | 118.0 | 129.0 |
| 18 | 142.8 | 112.9 | 120.4 | 131.6 |
| 19 | 145.7 | 115.1 | 122.8 | 134.2 |
| 20 | 148.6 | 117.4 | 125.2 | 136.9 |
Methods
- Tools of government Hood (1983), The Tools of Government, Macmillan
- Carrots, sticks and sermons Bemelmans-Videc, Rist and Vedung (1998), Transaction
- Diffusion of innovations Rogers (2003), Diffusion of Innovations, Free Press
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page's map can draw:
- Borders Natural Earth
- Cities Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Development Finance Nexus in Foundry
- Tested at Development Finance Nexus in Universe
- Codified in Finance, Insurance and the Economy in Standards
- Published in Development Finance Nexus in Reports
- Taught in Faculty of Finance and Economics in Academy
06Validation
How results are checked.
Analyses are checked through sensitivity analysis, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.
| Check | How it is done |
|---|---|
| Sensitivity analysis | The ranking of options is tested against changes in weights, probabilities and costs |
| Elicitation protocol | Expert judgements follow a documented protocol with calibration and stated ranges |
| Retrospective review | Past decisions are compared with outcomes to test whether the analysis would have helped |
Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.
07Exposure, loss and capital
What decision analysis for development finance means for exposure, loss and capital.
The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.
Transmission channels
How a shock in decision analysis for development finance reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
NGFS climate scenarios · Network for Greening the Financial SystemIFRS S2 Climate-related Disclosures · ISSBTCFD recommendations · Financial Stability Board TCFDPrinciples for the effective management of climate-related financial risks · Basel Committee on Banking Supervision
08Connections
Topics that rely on this method.
09Stewardship
Who maintains the method.
Systemic Risk Management stewards decision analysis under uncertainty for the Consortium and reviews how it is applied across platforms.
10Connected
Where this page leads across the Consortium.
11Questions
Questions and answers.
What are the limits of decision analysis under uncertainty in this field?
Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.
How are results checked?
Analyses are checked through sensitivity analysis, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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