Vulnerability of Households to Disasters: An Analysis

from Disaster Prone Region in India

Unmesh Patnaik and K. Narayanan

Department of Humanities and Social Sciences

Indian Institute of Technology Bombay

Mumbai 400076

Introduction

People in developing countries are subject to a variety of risks concerning their livelihoods

The negative impacts of climate change (increased frequency of natural disasters, shifts in the rainfall pattern) is a serious concern for developing countries like India

Twenty-two of India’s states are regarded as particularly prone to natural disasters

On an average, direct natural disasters losses amount to up to 2% of India’s GDP

Risk to people living in developing countries

Direct Impacts

Indirect Impacts

As natural disasters are rare events and can happen on an unprecedented scale it may not be possible to fully hedge against them

Introduction contd.

According to India’s National Communication to UNFCCC

Variation in Annual Average Monsoon Rainfall

Decreasing Trends in Monsoon Rainfall

Rise in maximum temperature exceeding 40 Degree Celsius

Increase in frequency of Floods all over India with severity increasing

Earlier Findings (Patwardhan et al. 2003; Patwardhan and Narayanan, 2003; Patnaik and Narayanan, 2005) also suggest

Large variation in the extent of vulnerability

Clusters of vulnerability regions exist (low infrastructure and demographic development are also the regions of maximum vulnerability)

Many factors contribute to social and economic vulnerability (economic/social/demographic/location etc.)

Variability in rainfall will have major impact on food grain production in India and also on the economy as a whole (Kavikumar and Parikh, 2001)

Objectives

Understand the various risks faced by households living in

disaster prone regions of rural India

Study the vulnerability of the income of the households living in

vulnerable regions of India

Examine the determinants of income of the households using a

micro level production function approach

Determine the relationship between the level of income of the

households and household specific characteristics in presence of

shocks generated out of natural disasters

Examine the livelihood pattern and impact of natural disasters

on households

Study is in reference to the districts Gorakhpur and Maharajganj

in Eastern Uttar Pradesh

Data and Methodology

The data used in the analysis is derived from the household

surveys conducted in the study area during December, 2007 –

March, 2008

A total of 320 observations are used in the analysis out of which

200 households belonged to the flood affected area and 120

households belonged to the drought affected area

Since the production functions (Cobb-Douglas and Translog) are

sensitive to missing observations missing values have been

transformed based on literature

Most common remedy is to this problem is to add an arbitrary

constant

In the present analysis the procedure adopted by Cockburn

(2002) is followed

The Leontiff production function allows for missing values

Data and Methodology

The linkages between livelihood of households and disaster risk is

analysed using descriptive statistics of the sample primary data

The relationship between household income and a set of

independent variable is estimated using three specifications of a

micro level production functions

Income of households is assumed to be dependent on three inputs

of production namely; (i) capital (ii) land and (iii) labour

Demographic variables and additional variables capturing

household specific characteristics are used as additional

predictors

The exogeneous shock is captured by using a dummy that

depends on the reported crop loss due to extreme events

The Study Area

Uttar Pradesh (UP) is one of the largest and poorest states in India

with an annual per capita income of around INR 10,500 and

having roughly 40 percent of its population in the poverty group

In terms of the HD Index the state ranks 13 among the other

Indian states with a HDI value of 0.38.

The state has quite diverse regional characteristics and the

incidence of climate related natural disasters is reported in the

eastern region of the state

This region has witnesses around 25 flood events during the time

period 1950-2007 with the most recent one being reported in the

year 2007 and the events show an increasing trend

The Study Area

Evidence of shifts in rainfall pattern resulting in onset of

Droughts

Rainfall Gaps in critical time periods (crop cycle) also increasing

over years causing crop failures

Severe droughts were reported in the year 1987 and 2004 with

over Rs. 200 crores being spent from the CRF on provision food

grains during drought

Significant impact on the economy of the state has been reported

due to these disasters with the growth of all the sectors

contributing to the state GDP witnessing a severe downfall in the

years preceding the disasters

Livelihood Pattern

The household size in the sample varies from a maximum of

twelve members to a minimum of one (mean is around six

members)

About 35 percent in the sample report the presence of a migrant

member in their household confirming the official estimates of

large scale migration from the state

Majority of the households (about 80 percent) belong to the

poor and not so poor classes (below poverty line and 1-1.5 times

poverty line

The primary source of income of the households in the study

area is agriculture and around 66 percent of the households

derive their income from the agriculture

Households also engage in secondary activities (like non farm

wage labour, business, animal husbandry etc.)to enhance their

income

Impact of Floods on the Households

During the last ten years the frequency of floods has increased with major floods being reported during the years 1998 and 2007 and a minor flood occurred in the year 2001

In the 2007 floods 68 percent of the households reporting crop damage due to the floods. The range of damage in monetary terms ranges from Rs. 500 to Rs. 70,000

Around 42 percent of the household report of having suffered complete damage to their dwelling structures while 18 percent suffered damage after which the dwelling structure was not usable anymore

Although the region is prone to floods the majority of the households (around 62 percent) have not reported any change in their sources of livelihood post floods

Around 78 percent of the households in the sample report that they are unable to cope with disasters with their current sources of livelihood

Impact of Droughts on the Households

Around 91 percent of the sample reported of having suffered crop damage because of drought

The analysis reveals that mean damage to paddy has been around Rs. 7380 and the range of the reported damage amount in the sample ranges between Rs. 1000 to Rs. 60,000

About 84 percent of the respondents believe that the disaster mitigation policies undertaken by the government agencies are not sufficient for the drought mitigation

Households generally have trust in insurance providers like insurance companies and banks for mitigation as around 77 percent of the households said that they have trust on insurance providers

There is a general increase in the rainfall gaps and almost the entire sample believed that rainfall gaps are increasing over the years matching with the scientific evidence of incidence of changes in rainfall pattern

Determinants of Household Income

Models

1 2 3 4 5

6 7 8 9

ln ln(kap)+ ln(L)+ ln(lab)+ (age) + (mig)

+ (bpl)+ (shg) (shk)+ (edn)i

iY

u

2 2 2 2

1 2 3 3 4 5 6 7

8 9 10 11 12 13

14 15 16 17 18

ln ln (L)+ ln (lsk)+ ln (lab)+ ln (kap)+ (L ) (lsk ) + (lab )+ (kap )

+ (kap lsk) (kap L)+ (kap L) (lsk L) (lsk lab) (lsk kap)

(age)+ (mig)+ ( )+ ( )+ (shk)+

iY

bpl shg

19 (edn)+ iu

1 2 3 4 5 6

7 8 9 10

11 12 13 14 15 16

(kap)+ (lsk)+ (L)+ (lab)+ (edn) [ ]

+ [ ]+ [ ]+ [ ] [ ]

+ [ ]+ (age) (mig) (bpl) (shg)+ (shk)+

i

i

Y kap lsk

kap L kap lab lsk L lsk lab

L lab u

Translog

Cobb Douglas

Leontief

Variables and Description

Variables Description Definition Mean S.D.

Y Income Total Income of the household in Rs. 46245.15 66574.78

kap Productive Assets Value of the productive assets owned by the

household and used in farming (like ploughs,

hoes, tractor, thresher etc.) in Rs.

27693.19 88884.49

L Land Land in hectares owned by the household 0.77 1.21

lab Labour No. of adults of the household employed in

farming

3.78 1.8

lsk Livestock Total value of livestock of the household in Rs. 4934.58 7217.91

age Age Age of the head of the household 50.05 13.99

mig Migration Dummy = 1, if the household has a migrant

member;

=0 otherwise

0.34 0.47

bpl Below Poverty Line Dummy = 1, if the household belongs to below

poverty line;

=0 otherwise

0.53 0.49

shg Self Help Group Dummy= 1, if the household is a member of self

help groups;

=0 otherwise

0.09 0.29

shk Shock Variable Dummy = 1, if the household reports of having

suffered crop damage due to flood or drought in

the past;

=0 otherwise

0.75 0.43

edn Education Head Number of years of education of the head of the

household

7.83 3.86

ResultsCobb Douglas Trans-log Leontief

Independent

Variables

Coefficient Marginal

Effects

Coefficient Marginal

Effects

Coefficient Marginal Effects

kap 0.185

(0.034)***

0.185 -0.182

(0.392)

-0.182 0.116

(0.151)

0.116

L 0.124

(0.036)***

0.124 0.125

(0.382)

0.125 -3680.041

(15945.61)

-3680.041

lab 0.543

(0.107)***

0.543 -0.026

(0.252)

-0.261 -250.21

(2252.22)

-250.21

lsk 0.023

(0.031)

0.023 0.248

(0.355)

0.248 -0.555

(1.372)

-0.555

age 0.004

(0.002)*

0.004 0.003

(0.002)

0.003 241.018

(160.77)

241.018

mig 0.216

(0.075)***

0.216 0.221

(0.084)***

0.221 9588.931

(7532.046)

9588.931

bpl -0.223

(0.075)***

-0.223 -0.232

(0.075)***

-0.232 -12951.89

(4868.0)***

-12951.89

shg 0.015

(0.12)

0.015 -0.009

(0.117)

-0.009 -8766.467

(7088.51)

-8766.467

shk -0.253

(0.082)***

-0.253 -0.212

(0.083)***

-0.212 -8555.936

(4207.78)**

-8555.936

Edn -0.004

(0.009)

-0.004 -0.009

(0.009)

-0.009 66.349

(734.91)

66.349

L2 - - 0.046

(0.021)**

0.046 - -

lsk2 - - -0.001

(0.02)

-0.001 - -

lab2 - - 0.012

(0.4)

0.127 - -

kap2 - - 0.024

(0.017)

-0.022 - -

kap*lsk - - -0.022

(0.026)

-0.01 - -

kap*L - - -0.01

(0.036)

0.033 - -

ResultsCobb Douglas Trans-log Leontief

Independent

Variables

Coefficient Marginal

Effects

Coefficient Marginal

Effects

Coefficient Marginal Effects

kap*lab - - 0.033

(0.062)

0.023 - -

lsk*L - - 0.023

(0.027)

-0.01 - -

lsk*lab - - -0.0006

(0.063)

-0.006 - -

L*lab - - -0.018

(0.06)

-0.018 - -

kap1/2*lsk1/2 - - - - -0.00002

(0.00002)

-0.00002

kap1/2*L1/2 - - - - 0.028

(0.236)

0.028

kap1/2*lab1/2 - - - - 0.029

(0.138)

0.029

Lsk1/2*L1/2 - - - - -1.872

(3.03)

-1.872

lsk1/2*lab1/2 - - - - 1.165

(1.616)

1.165

L1/2*lab1/2 - - - - 17217.96

(12278.34)

17217.96

Constant 7.733 (0.449)*** 9.22 (2.38)*** 23846.66 (11643.01)**

F value 26.05*** 16.16*** 7.92***

R2 0.461 0.49 0.41

N 320 320 320

Dependent Variable:

ln Income

Dependent Variable:

ln Income

Dependent Variable: Income

Significant at 10%(*), 5%(**) and 1% (***); Figures in parenthesis show the Standard Errors

Note: Similar results are also obtained when consumption of the households is used as the dependent variable instead of income

Results and Discussion

In the Cobb Douglas case seven explanatory (out of ten)

variables turn out to be statistically significant with three factors

of production capital, land and labour turn out to be highly

significant

The dependent variable (income of the households) is highly

sensitive to the input variable labour as a unit change in this

variable is likely to result in a fifty percent increase in the

income level of the household

Similarly, the marginal effect of other two variables capital and

land are 0.18 and 0.12 respectively

Since the coefficient for migration is also positive it can be

inferred that the migrant members in family add to the

household income

Results and Discussion

With respect to household specific characteristics, three variables are significant; (i) age of the head of the households, (ii) presence of a migrant in the family, and (iii) dummy variable capturing the households living below poverty line

The dummy variable for households living below poverty line has a negative sign implying that if a household belongs to below poverty line group than it has a negative impact on its income level

The dummy variable crop damage capturingthe negative impacts of shocks on the income level of a household displays a negative sign and is also highly significant across all functional forms

The F value (26.05) is highly significant thereby rejecting the null hypothesis that all estimated parameters are equal to zero

Summary and Conclusions

The production function estimates obtained suggest that the

Cobb-Douglas production function is a good fit for the data as

compared to the other two production functions namely the

Translog and the Leontief

These results are not very surprising as a number of studies have

found similar results

Cockburn (2002), Lambert and Magnac’s (1992) in study of

household income function from an agricultural household

model report that the results obtained from using a CES or CD

production function are better as compared to the Generalized

Leontief / Translog results in terms of precession

The analysis undertaken in the paper suggests that income of the

households is negatively related to endogenous shocks arising

out of disaster events

Summary and Conclusions

Hence it can be said that the income level of the household is

highly susceptible and inversely related to the shocks generated

out of climate related disaster events like flood and drought

Household specific characteristics like age, economic status of

the household and presence of out-migrants is positively

significant in determining the level of income of the households

Therefore, continuous exposure to these disasters over the years

will result in ever decreasing income level of households living

in these regions and over a period of time they will be in a state

of chronic poverty

Policy Implications

Policy makers in developing countries face multiple

development challenges as vulnerability to natural disasters can

aggravate poverty and make it harder to achieve the

development goals

People living in absolute poverty will not be able to cope up

with the impacts of disasters which are likely to worsen due to

climate change

Concentration should be on increasing the resilience of the

households to disasters by empowering them to raise their levels

of income with adequate employment opportunities

Empowerment of people for improving the basic quality of life

will be helpful in raising adaptive capacity of households

Thank You