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Socio-economic scenarios Anand Patwardhan IIT-Bombay.

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Presentation on theme: "Socio-economic scenarios Anand Patwardhan IIT-Bombay."— Presentation transcript:

1 Socio-economic scenarios Anand Patwardhan IIT-Bombay

2 Anand Patwardhan, IIT-Bombay2 Crude oil price forecasts

3 Anand Patwardhan, IIT-Bombay3 Why do we need scenarios? The uncertainty explosion Prediction or planning Idea of “not implausible” futures Robustness vs. optimality Context for a forecast

4 Anand Patwardhan, IIT-Bombay4 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

5 Anand Patwardhan, IIT-Bombay5 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

6 Anand Patwardhan, IIT-Bombay6 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?

7 Anand Patwardhan, IIT-Bombay7 Drivers Socio-economic context Demographics Economic growth Consumer values and preferences Technology What is pre-determined and what is uncertain? What is constrained?

8 Anand Patwardhan, IIT-Bombay8 Links between the drivers Energy consumption & per capita GDP

9 Anand Patwardhan, IIT-Bombay9 More linkages between drivers

10 Anand Patwardhan, IIT-Bombay10 Storylines Interconnections and dependencies Describing future evolution What is consistency? In what way might dependencies change? Dematerialization Income and energy

11 Anand Patwardhan, IIT-Bombay11 Decoupling drivers (income and energy)

12 Anand Patwardhan, IIT-Bombay12 Discontinuities and branching points How might they happen? Are there early indicators? Where might they happen?

13 Anand Patwardhan, IIT-Bombay13 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?

14 Anand Patwardhan, IIT-Bombay14 Past discontinuities in energy technology – non-marginal change in energy systems

15 Anand Patwardhan, IIT-Bombay15 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?

16 Anand Patwardhan, IIT-Bombay16 General to the specific Global to local / regional Down-scale the global Or Use the global for checking consistency

17 Anand Patwardhan, IIT-Bombay17 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

18 Anand Patwardhan, IIT-Bombay18 Judging scenarios Recognizable and grounded in the present Empirical constraints Plausible Internal consistency Fit within models Challenge existing mental map Consequences for decisions

19 Anand Patwardhan, IIT-Bombay19 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)

20 Anand Patwardhan, IIT-Bombay20 Forecasting issues Attributes: explicit, reproducible, quantitative (?) Value, skill, quality, reliability What do we want to forecast?

21 Anand Patwardhan, IIT-Bombay21 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


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