socioeconomic impacts of climate change: case of...

Department of Humanities & Social Sciences

Indian Institute of Technology Bombay, Mumbai, India

Socioeconomic Impacts of Climate Change:

Case of Rural Households in India

Dr. K. Narayanan

Institute Chair Professor & Head

Email: [email protected]

To be Presented at the Panel Discussion:

Social Science Issues in Energy and Environment

McDonnell Academy Global Energy and Environment Policy

International Symposium on Energy & Environment

Abundant Clean Cost-effective Energy Systems for Sustainability

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Introduction

• Climate Change and Economics

– “Climate change is the most severe problem that we are

facing today - more serious even than the threat of

terrorism” [Sir David King]

– Economic implications of climate events such as global

warming and the costs of tackling

– The role of economic policy instruments

– The close linkages between world economic performance,

the man-made forces influencing climate change, and the

role of technological change in reducing greenhouse gas

emissions

9 January 2013 2 KNN-MAGEEP-2012

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Contd…

• Country Specific Effects

– Vulnerability to climate change mainly depends on economic position and infrastructure capacity of different regions.

– Climate change effects impose significant additional stress on ecological and socioeconomic systems.

– Technologically advanced countries are prepared well for responding to climate change, particularly by developing and establishing suitable policy, institutional and social capabilities for dealing with the consequences.

– However, the poor and developing countries are mostly affected by climate change, because they are not having enough and sound technologies or scientific development to deal with this impact.


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Contd…

• From Macro to Micro Economics of Climate Change – Microeconomics of climate change deals with the

vulnerability due to climate change on households

– This phenomenon is more severe for the developing

countries

• due to constrains on public spending

– Hence, studying socioeconomic impacts of climate change,

at the household level, becomes important for developing

nations, particularly in formulating adaptation and

mitigation strategies

– This presentation is focused on the rural households in

Indian Economy


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Objectives

• We try to look at the following impacts of climate

change on rural households

– The ex-post implications of climate related disasters

– The energy poverty pattern due to the extreme events and

– To model & analyze the determinants of vulnerability due

to climate shocks


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Indian Climatic Condition

• The climate along the Indian coast varies from true tropical

region in south to that of sub-tropical and arid environment in

Kachchh in northwest.

• Rainfall varies from only 300 mm in the semi-arid region of

Kachchh in western part of Gujarat State to average maximum

of 3200 mm in Andaman-Nicobar Islands in south.

• On the eastern coast, there are gigantic deltas of the Ganges-

Bramhaputra, Krishna-Godavari, and Mahanadi, which

support large area of river estuaries and excellent growth of

tidal forests.

• Most of the rivers in India flow to east-coast in the Bay of

Bengal and carry tremendous amount of silt during monsoon.


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Contd…

• India is subject to a wide range of climatic conditions from the

Himalayan winters in the north to the tropical climate of the

southern neck of land, from the moist, rainy climate in the

north-east to the arid Great Indian Desert in the north-west,

and from the marine climates of its vast coastline and islands

to the dry continental climate in the interior.

• Specifically, the coastal India is subject to higher degree of

vulnerability due to extreme climate/weather events


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The Study Area

• The selected study area is Kendrapara District in Odisha State

of India, that lies in the east coast

• Two blocks namely Rajanagar and Mahakalpada are choesen

based on the vulnerability index (Narayanan et al., 2011, Report

submitted to MoEF, GoI)

Mahakalpada Block

Rajanagar Block

Map not to scale, source: Kendrapara District Office


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Contd…

• Kendrapara District lies in 20º 20’ N To 20º 37’ N Latitude and

86º 14’ E To 87º 01’ E Longitude and situated in central coastal

plain zone as per the Agro-Climatic Classification of Odisha.

• Four other districts surround Kendrapara District and a part is

bounded by the Bay of Bengal.

• Bay of Bengal lies in the eastern part of the district.

• The coastline covers 48 km stretching from Dhamra Muhan to

Batighar.

• Kendrapara district headquarters is 85 km from the State

headquarters.


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Distribution of the Cyclones during 1971 to 1990

State/District Depression Storm Severe Storm Total

Odisha

2 0 1

52 (100%)

9 2 1

7 1 2

5 0 3

7 3 0

3 1 0

5 0 0

Kendrapara 7 1 2 10 (20%)

20% of cyclone [in the State] occurred in Kendrapara District.

From the vulnerability analysis also it was found that

Kendrapara is one of the most Vulnerable districts of

Odisha State in India.


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Vulnerability Analysis

• Data Source: Census of India and District Statistical

Handbook, Kendrapara, Government of Odisha

• Vulnerability pattern

2 56

419

554

228

104

24 13 7 0

100

200

300

400

500

600

<0.05 <0.1 <0.15 <0.2 <0.25 <0.3 <0.35 <0.4 <0.45

No

. o

f V

illa

ges

Index Value

Socioeconomic Vulnerability


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Contd…


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Contd…

• Change in Land use Pattern

Class % Area

1973 1990 2001

Water Body 7.72 5.11 16.46

Settlement 2.90 7.03 23.73

Wasteland 55.83 43.72 40.25

Forest 9.91 5.93 8.80

Agriculture 26.54 38.22 10.76 7.72

2.9

55.83 9.91 26.54

5.11

7.03

43.72 5.93

38.22

16.46

23.73

40.25 8.8

10.76

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Water Body Settlement Wasteland Forest Agriculture

2001

1990

1973

Insights from the land use pattern • Water body has decreased from 1923-1990 and increased during 1990-2001,

Settlement has increasing from 1973 to 2001

• Wasteland has decreasing from 1973 to 2001, Forest land has decreasing from

1973 to 2001, Agricultural land has decreasing from 1973 to 2001


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Data

• For Vulnerability analysis at Block-level

– Secondary data from Census of India (1991)

– District Statistical Handbook on Kendrapara (various years)

– Agriculture Statistics, Government of Odisha (Various years)

• For Household Level Analysis

– From two coastal blocks, six most vulnerable blocks were identified based socioeconomic vulnerability index

– Primary data collected (Stratified random sampling) for 150 households

9 January 2013 KNN-MAGEEP-2012 14

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Construction of Variables

• Measuring Poverty – Following FGT index, poverty is defined as

• Vulnerability Class – Defined as losses due to cyclone with respect to poverty index as:

– In case of vulnerability class-1 the percentile rank takes higher than 70 percentile, for class-2 it takes value between 50-70 percentile and for the class-3 the rank takes the value from 0-50 percentile

• Energy Poverty – Energy Poverty is defined as:

– Households below the mean Ep are considered to be energy-poverty and above Ep, otherwise

0,1

1

N

i

i

z

G

NP

Household theof Income

Loss TotalRank PercentilecV

t1-t

t1-t

Income Income

Exp Fuel Exp Fuel

pE


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Vulnerability Classes and

Poverty

• Vulnerability class-1 defines

the severe vulnerable

households in the sample.

Accordingly class-2 and class-

3 are the moderate and least

vulnerable households

• 60% of the household fall in

severe vulnerability, 25% fall

in moderate and 15% of

households fall in least

vulnerability

• From the figure we can

observe that most of the poor

households are classified in

Vulnerability class-1 and class-

2, however non-poor are

classified in Vulnerability

class-3

60% 25%

15%

Vulnerability classification of Sample Households

Vulnerability class-1 Vulnerability class-2 Vulnerability class-3

78% 74%

24%

22% 26%

76%

0%

20%

40%

60%

80%

100%

60% 25% 15%


Distribution of Poor & Non-Poor within Vulnerability classes

Poor Non-Poor

Comparison of Vulnerability and Poverty


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Energy-Poverty and Poor

• 79% of household are

categorized under energy poverty

and 21% of sample are non

energy poor

• In energy poverty category 65%

of households fall in Severe

vulnerable class, 21% are in

moderate vulnerability class and

only 14% are in least

vulnerability class

• For energy non-poor category 47

of them are from vulnerability

class-1, 29% are from

vulnerability class-2 and 24% are

from vulnerability class-3

• Linking energy poverty and

vulnerability gives us the

conclusion that vulnerable are

also energy poor.

79%

21%

Classification of Energy Poor

Energy-Poor-1 Energy-Poor-2

65% 47%

21%

29%

14% 24%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

79% 21%

Energy-Poor-1 Energy-Poor-2

Energy-Poverty and Vulnerability Classes


Comparison of Energy-Poverty and Poor


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Determinants of Asset Loss and Crop Damage

• The Asset loss function of the households due

to cyclone is estimated using the following

functional form:

• The Crop Damage function of the households

due to cyclone is estimated using the following

functional form:

ecturedamagtentofstruncomeag,exLitracyD,i

teD,BPLD,e,sexD,casilysize,agincome,famfAssetLoss (1.1)

(1.2)

landBPLagprimaryincage

productionliterateDcasteDsexDfamilysizefCropDamage

,,,

ln,,,,


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Determinants of Asset Loss

Dependent Variable: Damage of Assets Coefficient t statistics

Income of the Household 0.02 1.9*

Family Size 9.12 2.08*

Age of the head 9.69 2.54***

Sex of head Dummy -16.50 -1.96**

Caste Dummy -4.65 -2.51***

BPL Status Dummy 6.31 2.11***

Literacy Dummy -4.61 -0.65

Primary income agriculture Dummy -4.03 -2.48***

Extent of household damage Dummy 9.48 2.24***

Constant 3.75 2.82

R2 0.25

0.24

F( 9, 140) 2.89**

Number of observation 150

2_

R


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Contd…

• Determinants of higher losses are characterized

by the following household composition

– Bigger family size

– Higher income group

– Families with older household head

– Female headed households

– Backward classes families

– Households depending on agriculture as primary

source of income and,

– Higher damage of structure of the house


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Determinants of Crop Damage

Crop damage Coefficient t statistics

Family size 7.67 2.97***

Sex of head Dummy -1.30 -2.27***

Caste Dummy -7.98 -2.75***

Literacy of the head Dummy 8.78 1.94*

Log of Production (last year) -4.98 -2.98***

Age of the head 6.56 2.85***

Primary income agriculture Dummy -6.01 -2.21***

Land holding 2.22 3.16***

Income 1.15 1.4

BPL Dummy 9.43 2.24**

Constant -5.11 -0.56

F( 10, 139) 3.81*

R2 0.21

0.19

Number of observations 150 2_

R


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Contd…

• Determinants of Crop Damages are characterized by the following household composition – Bigger family size

– Literate households



– Higher land holding households

– Households those are in BPL

• However, – Households those are female headed, reported higher

production in the previous year, agriculture as a primary source of income are those who have less crop damage due to the cyclone. Income of the household does not explain the crop loss in the estimation


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Energy Poverty and Vulnerability

• Domestic energy poverty refers to a situation where a household does not have access or cannot afford to have the basic energy or energy services to achieve day to day living requirements (Pachauri, et al., 2004)

• We have tried to link energy poverty with vulnerability due to climate change.

• Hence, two groups [non energy poor and energy poor in the sample] are created

• Further, we have tried to estimate the income shock due to cyclone and related it to energy poverty at household level.


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Probability of Energy Poverty during Cyclone

Energy Poverty Dummy Coefficient z Value

BPL Dummy -1.01 -2.49***

Income from Migrants -2.08 -3.33***

Saving -1.66 -2.81***

Agriculture as Primary Source of Income -0.67 -2.83***

Use of fuel other than wood -0.48 -1.98**

Other non food expenditure 0.00 1.97**

Literacy Dummy -0.28 -0.45

Crop Damage 0.00 -2.47***

Constant -1.19 -0.93

Log likelihood -48.41

LR Chi2(8) 36.01***

Pseudo R2 0.27

Number of observations 150


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Contd…

• The major determinants of probability of energy poverty during climate extreme events are as follows: – Households are vulnerable and are characterized in

energy poverty when they, • Belongs from BPL category

• Less income from Migration

• Less saving potential

• Agriculture as primary source of income

• When use fuel other than wood

• Higher crop damage due to climate event

• However, are less vulnerable when they have higher non-food expenditure and literacy is not a determinants of energy poverty


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Finding from the Study

Asset & Crop Damage Function

– Bigger family size

– Higher income group


– Female headed households


– Households depending on agriculture as primary source of income

– Higher damage of structure of the house

– Households those are in BPL

Probability of Energy-Poverty

– Belongs from BPL category

– Less income from Migration

– Less saving potential

– Agriculture as primary source

of income

– When use fuel other than

wood

– Higher crop damage


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Poverty-Vulnerability-Energy Poverty

• Less Income

• Less expenditure on food and basic needs

• Higher family size

• Less land holdings

Poverty

• Structure Damage

• Loss in agriculture

• Loss in income

Vulnerability • Unavailability of

fuel during extreme climate events

• Higher dependency on wood for fuel

Energy Poverty


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Conclusion and Policy Suggestions

• Impact on infrastructure; loss of physical capital; impact on agriculture; damage to environment and human capital are the direct impacts on the socioeconomic set up.

• The indirect ones include loss of production of goods and services, loss of future harvests and income. – further, we found that vulnerability due to cyclone for rural households

is directly related to level of income, employment, and institutional support.

– However, degree of vulnerability differs among income groups • where, less income groups are more exposed

• for crop damage higher land holding households are most sufferers

• poverty directly related to vulnerability

• higher dependence on natural resources makes household more vulnerable

• In case of energy poverty, income class and vulnerability due to climate change are directly related

• probability of energy poverty is more with high family size and less income


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Contd…

• From a policy formulation point of view, we conclude that people living in absolute poverty will not be able to cope up with the impacts of disasters, and their status will further worsen due to challenges posed by climate change.

• In addition, hazards of climate change pose severe challenge in availability of energy and to the energy consumption pattern at the household level.

• Our analysis suggests that disaster mitigation policies have to be integrated with sustainable development strategies in general, and poverty alleviation measures & building institutional supports in particular.

• This, in turn, will enable people to hedge against the large scale negative impacts of climate change and climate related disasters.


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References

Adger, W. N., (2003), “Social Capital, Collective Action, and Adaptation to climate Change” Economic Geography, Vol. 79

Adger, W. N., (2006), Vulnerability, Global Environmental Change, Vol. 16

Blaikie, P., Cannon, T., Davies, I. and Wisner, B. (1994), At Risk -Natural Hazards, People's Vulnerability, and Disasters, London, Routledge

Fahmy, E., (2011) The definition and measurement of fuel poverty, Consumer Focus Briefing Paper

Jones, R.N., (2001), An Environmental Risk Assessment / Management Framework for Climate Change Impact, Natural Hazards, Vol. 23

Narayanan, K et al (2011), Project Report submitted to Ministry of Environment, Govt. of India.

Pachauri, S., A. Mueller, A. Kemmler and D. Spreng, (2004), On Measuring Energy Poverty in Indian Households, World Development, Vol. 32, No. 12


Department of Humanities & Social Sciences

Indian Institute of Technology Bombay, Mumbai, India

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