Socio-economic scenarios Anand Patwardhan IIT-Bombay

Socio-economic scenarios

Anand PatwardhanIIT-Bombay

Anand Patwardhan, IIT-Bombay 2

Crude oil price forecasts


Why do we need scenarios?

The uncertainty explosion Prediction or planning Idea of “not implausible” futures Robustness vs. optimality Context for a forecast


Scenarios and V&A assessment

Hazard – exposure – impacts – response Scenarios for the individual layers and

their interactions Socio-economic and climate Relevant to the scale of assessment


Scenarios

Plausible, pertinent and logically consistent alternative stories of the future

Provide the context for a forecast Strategic thinking, and the quality of that

thinking rather than planning Exploratory (positive) and normative


Building scenarios

Central question / issue being considered What are the things that really matter? What are the key drivers (both micro and

macro)? What are plausible storylines for describing their

evolution? What are the interconnections and

dependencies? Can we quantify some of the drivers and their

measures?


Drivers

Socio-economic context Demographics Economic growth Consumer values and preferences

Technology What is pre-determined and what is

uncertain? What is constrained?


Links between the drivers

Energy consumption & per capita GDP


More linkages between drivers


Storylines

Interconnections and dependencies Describing future evolution What is consistency? In what way might dependencies change?

Dematerialization Income and energy


Decoupling drivers (income and energy)


Discontinuities and branching points

How might they happen?

Are there early indicators?

Where might they happen?


Where might they happen?

The climate system – collapse of the North Atlantic thermohaline circulation

The socio-economic system – early development of a hydrogen-based backstop energy system

What about from the coupled system? Is it less or more susceptible to discontinuity?


Past discontinuities in energy technology – non-marginal change in energy systems


Linking climate and socio-economic scenarios

Socio-economic scenarios lead to emissions lead to climate change

What about the reverse? For example, if we do carbon management on

a large-scale, what does that mean for the dynamics of the carbon cycle?

Feedback – what parts of the system can be treated as exogenous?


General to the specific

Global to local / regional Down-scale the global Or Use the global for checking consistency


Example: regional assessment (urban)

Drivers: Regional demographics, migration Economic growth Settlement characteristics

Storylines: Perhaps start from the SRES storylines Development with settlement form and

pattern Public infrastructure

Perhaps climate is exogenous


Judging scenarios

Recognizable and grounded in the present Empirical constraints

Plausible Internal consistency

Fit within models Challenge existing mental map Consequences for decisions


From scenarios to forecasts

Build forecasts in the context of scenarios Extrapolative

Statistical Model-based (example: diffusion models)

Pattern-based By analogy Precursors

Normative, goal-based Expert judgment (Delphi)


Forecasting issues

Attributes: explicit, reproducible, quantitative (?)

Value, skill, quality, reliability What do we want to forecast?


Issues

Tyranny of the present Discontinuities and surprise

Process improvement rather than prediction Scenarios as learning tools Process understanding rather than

specific outcomes From static to dynamic

Documents

Socio-economic scenarios Anand Patwardhan IIT-Bombay