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Developing SocioDeveloping Socio--Economic Economic

Scenarios for India Scenarios for India

Purnamita Dasgupta

Institute of Economic Growth, Delhi

National Workshop

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Objectives

• To develop alternative socio-economic scenarios that

take into consideration a sustainable development

objective for India

• To develop a conceptual frame for indicative economic

costs of policies for adaptation to climate change,

specific focus on vulnerable groups.

• To illustrate the methodology with detailed studies,

focusing on agriculture as a key sector

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Methodology• Key markers of socio-economic vulnerability and

adaptive capacity were identified

• These include Geographical (inter-state variation and

coastal location), Demographic (inter-state population

distribution) and Coping vulnerability (income

differentials and access to basic facilities)

• Socio-Economic variables impacting each of the above

(through either an increase/decrease in vulnerability)

are then interacted in a dynamic simulation model

• Model provides: (a) alternative development pathways

through short to medium term projections over (b)

varying time scales (c) key parameters which can be

influenced to achieve desirable outcomes for

decreasing vulnerability.

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Gross Domestic Product

Poverty Reduction Sectoral Gross Domestic Product

�Food security

�Unemployment Reduction

�Access to Basic Services

Share of Agriculture Sector

Food grain Production

Conceptual Frame – Economy and Agriculture Module

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Area under Food grain

� Profitability

� Technology

� Climatic Factors

� Irrigation

� Other Socio-Economic Factor

� Share of Primary Sector

� Education

� Infrastructure

Food Production

Population

Per Capita Production

Conceptual Frame:

Dynamic Simulation of Food grain Production

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Gross DomesticProduct

Poverty

Reduction

Food Security,

Unemployment

Reduction,

Acess to Basic

Services

Sectoral

Gross

Domestic

Product

Share of

Agriculture

Sector

Area under

Foodgrain

area change dueto change inprofitability

factorchange inrelative

profitability

irrigated area

food grainnon-irrigated area

foodgrain

change in area

foodgrain

Proportion of land

irrigated

<Time>

food

production

Yield (irrigated)Yield

(nonirrigated)

Per capita

production

Population

in2

<Time>

<Time>

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Emerging Scenarios

• Time scale from current time period till 2030

• Reference scenario has current expectations and

assumptions of structural stability, and, concerns for

vulnerability without climate change impacts – results

available

• Optimistic Scenario improves on reference with rapid

technological progress and adaptive strategies –

results available

• Longer term Scenario Simulation – in progress

• Indicative Costs – framework developed; ongoing work

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Variable Reference Scenario

Optimistic Scenario

GDP growth rate (2020-2030) 7 % 8 %

Unemployment Rate 1% 1%

Income Poverty (Percentage BPL) 5% 5%

Sectoral Shares in GDP: Primary: (Secondary + Tertiary)

0.15: 0.85 0.10:0.90

Per capita Food Grain Production 182 kgs 198 kgs

Urbanisation 0.45 0.50

Access to basic amenities 100% 100%

Socio-Economic Scenarios for the Indian Economy, 2030

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Per C

ap

ita F

oo

dg

rain

Pro

du

ctio

n

17

0.0

0

17

5.0

0

18

0.0

0

18

5.0

0

19

0.0

0

19

5.0

0

20

0.0

02004-05

2005-06

2006-07

2007-08

2008-09

2009-10

2010-11

2011-12

2012-13

2013-14

2014-15

2015-16

2016-17

2017-18

2018-19

2019-20

2020-21

2021-22

2022-23

2023-24

2024-25

2025-26

2026-27

2027-28

2028-29

2029-30

op

timis

tic sce

na

rio

refe

ren

ce s

cen

ario

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Uncertainty Issues

• TFP, technological progress

• Limiting – cap values : land availability, irrigation

potential, population, relative international prices

• Turning points – thresholds : where these lie and extent

of certainty of occurrence

Quality Assurance

• Face Validity through repeated iterations – expected

and consistent signs and directions of flows

• Historical behaviour tests

• Reality checks with extreme values for parameters

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Adaptation Framework

• Response Levels

– Variables determining potential for adaptation: education,

technological development

– Variables impacted by the potential: e.g. water use efficiency

• Drivers of Change

– Policies - State; Initiative – Public or Private or both

– Agency – State as Enabler; Individual and Civil society –

diffusion, uptake, funding

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Adaptation Framework

• Costs

– Knowledge Advancement Costs : Awareness and

Media, R & D, Institutional Development

– Sustainability Transition Costs: building a climate

resilient society - most sectoral, context specific

approaches/estimates capture these (on track with

developmental goals) e.g.: R & D to installation of

early warning systems; from institutional

development to crop insurance at incremental

premiums for climate change

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Some Conceptual Concerns

• Developmental goals well defined for short term (e.g. MDGs);

taken care of in setting the time frames and targets (e.g.

literacy, poverty, access to basic amenities)

• Adaptation Costs – in short run cover for derailment of the

economy from the desired time path

• Currently available CC data for 2071-2100; socio-economic

modeling limitations beyond 2030.

• Therefore, adopt a Systems Equilibrium approach ----

Moving from last three decades till 2004-05, to a future 30 year

period: 2071 to 2100.

Advantage – CC data available, disadvantages – too much

uncertainty to risk putting one number to it, even for the

economist!!!

For the present, See Adaptation costs in terms of directions of

change. Illustrate for food grain production.

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Food grain prod. 2004-05

10.54

10.5

13.4

12.15

5.26

37.84

14.1

13.11

25.67

16.06

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Foodgrain prod. 2030 (opt.)

15.19

11.18

14.28

12.93

5.6

40.28

26.04

13.96

27.34

17.12

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Foodgrain prod. 2071, 2100

21.56

17.18

18.86

22.74

15.77

31.95

27.3

19.73

23.93

20.64

18.85

17.93

20.91

18.32

18.83

24.26

20.63

24.82

28.91

24.34

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Relative Change in foodgrain production

State Name 2030 relative to

2004-52071 relative

to 2030

2100 relative to 2071

Andhra Pradesh + + +

Gujrat + + +

Haryana + + +

Karnataka + + +

Madhaya Pradesh + + -

Maharastra + + -

Punjab + - +

Rajasthan + + -

Uttar Pradesh + - -

West Bengal + + +

India + - -

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Indicative Transition & Knowledge Costs

Adaptation to changing water availability for

agriculture in vulnerable areas

• Costs of weather insurance for typical rainfed

agriculture – private (esp. large and medium); social

/ government (small and marginal)

• Cost of water saving technology (drip and sprinkler

irrigation) – mostly private costing

• Cost of R & D in low water using crops – social/

government cost

• Cost of institutional development and resilience

build up for first two – both private and public; not

so for last. Rather, private agent may have incentive

to move into different land use.

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Adaptation Costs

• Various definitions and conceptual inconsistencies

exist in adaptation literature and available estimates

• Anticipated costs which maybe incurred by public

and private agents to plan for a change foreseen

with reasonable accuracy

• Critical – precision of extent and probability of

climate change impacts; incremental attributable to

CC; agency which bears the cost.

• Adaptation Funding for apportioning of costs between

2010 and 2100

• NREGA, BPL

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% NREGA employment , % BPL

2.78

26.97

0

42.5

10.63

16.33

14.74

15.65

2.56

18.94

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