INDIA NATIONAL REPORT ON DISASTER RISK, POVERTY AND HUMAN DEVELOPMENT RELATIONSHIP Disaster Risk Reduction and Poverty : Case study of Orissa and Tamil.

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INDIA NATIONAL REPORT ON DISASTER RISK, POVERTY AND HUMAN DEVELOPMENT RELATIONSHIP Disaster Risk Reduction and Poverty : Case study of Orissa and Tamil Nadu Final Review Meeting: Asia – Bangkok India Report November 5, 2008

2 Introduction Chapter 1 – Overall hazard vulnerability & poverty in India, Framework, Methodology Chapter 2 – Mapping socio-economic vulnerabilities Chapter 3 – Mapping of Hazard Risk Chapter 4 – Mapping of disaster impacts Chapter 5 – Vulnerabilities and Disaster Linkages Chapter 6 – Way forward

3 NSDP and Per Capita NSDP GR ( to ) NSDPPer Capita NSDP Orissa Tamil Nadu India India Per Capita GDP ($PPP) (2006) = US$ 3,452 India GDP at Current Prices, = Rs. 25,716 Tamil Nadu Per Capita Net State Domestic Product (NSDP) ( , at current prices) = Rs. 29,958 (1.16 times of India) Orissa Per Capita Net State Domestic Product (NSDP) ( , at current prices) = Rs. 17,299(0.67 times of India)

4 GDP Composition In Orissa 36% GDP from primary sector & just 20% from secondary sector In India, just 22% GDP from primary sector & 25% from secondary sector In Tamil Nadu, 30% GDP from secondary & just 14% GDP from primary Jobless growth in India primarily because of relatively small secondary sector

5 Employment & Urbanization  Just 27.5% population in India living in urban areas  Orissa, just 15% living in urban areas  Tamil Nadu 44% living in urban areas  59% of working population in India employed in primary sector when its GDP share is only 22%  64% or working population in Orissa employed in primary sector, when its GDP share is 36%  Inspite of high urbanization level, 46% of workers in Tamil Nadu engaged in primary sector with income share of 14 %  India in general and both states in particular have stress in rural economy

6 Comparing Indian and international poverty lines

7 Poverty Profile - India  Incidence of poverty in India, the Head Count Ratio is 28.7% for rural and 25.7% for urban in  millions in rural and millions in urban areas live below the officially defined poverty line in  Total million population living below poverty line in  Just million population have come out of poverty from to (in last 10 years)  Slowing down of poverty decline is inspite of high economic growth rate in this period.  Growth is accompanied by increasing inequalities

8 Rural Poverty - India  There is regional dimension to rural poverty. Eastern states have the highest rural poverty followed by western states & southern states

9 Poverty Among SC, ST and All - Rural  Rural poverty also has social dimension; The HCR among Scheduled Tribes (STs) is 48% and among Scheduled Castes (SC) is 35% in

10 Poverty in Orissa  47% rural population below official poverty line  44% urban population below official poverty line  Increase in urban poverty from 41% to 44% in to period  Rural poverty gap index value 12.1 and urban PG index value 14.1 in  Gini coefficient increased in rural from 24.6 to 28.5  Gini coefficient in urban increased from 30.7 to 35.4  Poverty among SCs is 50% and among STs is 77%  SCs 16.5% of state’s population and STs 22.1%

11 Poverty in Tamil Nadu  23% rural population below official poverty line  22% urban population below official poverty line  Decrease in urban poverty from 40% to 22% in to period  Rural poverty gap index value 3.7 and urban PG index value 5.3 in  Gini coefficient increased in rural from 31.2 to 32.2  Gini coefficient in urban increased from 34.8 to 36.1  Poverty among SCs is 30% and among STs is 31%  SC 19% of state’s population and STs just 1%

12 IMRs - Manifestation

13 Malnourishment Among Children

14 Hazard prone areas of India Of the 35 states and union territories, 27 area hazard prone 241 districts are multi-hazard prone May to November months are the most hazard-prone DisasterVulnerable States/ Regions 1Tsunami*Tamil Nadu, Kerala, Pondicherry and Andaman & Nicobar Islands 2EarthquakeAcross the country with moderate – high intensity (over 65% of the areas of India is vulnerable to earthquake) 3CyclonesCoastal areas – particularly in East coast & Gujarat (8% of area) 4FloodsIndo-Gangetic plains and Brahamaputra basin (approx comprises 40 million hectares prone to floods) 5 DroughtsA slow disaster across the country (approx 68% of cropped area affected) 6Forest FiresHimalayan Forests 7LandslidesSub-Himalayan region & western Ghats in particular

15 Earthquake Hazard

16 Wind & Cyclone Hazard

17 Wind & Cyclone Hazard Zone, Orissa  Whole of coastal region is hazard proof

18  Coastal Tamil Nadu is also hazard proof

19 Annual trends of Disaster - Orissa  Higher incidence reported after 2003 in Orissa because of better reporting  Question of quality of data

20 Annual Disaster Trend – Tamil Nadu

21 Literacy Rate, MaleFemale Rural Orissa Tamil Nadu All India Urban Orissa Tamil Nadu All India

22 SC – ST Literacy

23 Orissa  Cyclone dominates disaster events  Epidemics lead population affected  Epidemics lead human deaths followed by cyclone

24  Buildings largely damaged by cyclone  Property loss due to floods

25 Tamil Nadu  Largest data cards of fire  Largest proportion of population exposed is floods  Largest death because of Tsunami

26  Largest proportion of buildings damaged because of floods  Largest property damaged because of floods  Tamil Nadu

27 Key development and poverty challenges  Rural poverty  Low ranking on Hunger Index of India. Tamil Nadu and Orissa in category of alarming level of hunger  Increasing inequalities  Children and women’s health  Low female literacy (taken as proxy for poverty in some studies such as Gujarat State’s HDR)  A quarter in Tamil Nadu and about half households in Orissa live in temporary house structures. This is also a proxy for poverty

28 Methodology Enhance Poverty OutcomesDisaster Risk  The reverse loop Disaster Risk to Poverty requires longitudinal household level data, which not available at the moment in India Attempt is to capture poverty through  Head Count Ratio (Private estimates)  Proportion of SC and ST (Population Census) (Proxy for poverty)  Temporary Housing (Population Census) (Proxy for poverty) District Level Analysis of these dimensions of poverty with disaster data Relationship of Poverty and Disaster Risk captured through correlations & scatter diagrams

29 Data issues  A Caution – District Level Poverty estimates are private estimates and not individual estimates. Official level poverty estimates are only upto state level  Disinventar Data – Better reporting in the last three years  TN – Tsunami dominates the impacts which cannot be seen across all the districts (More than half the deaths in last 10 years is because of tsunami)

30 Poverty disaster linkages – Some observations  Tamilnadu reports 283 epidemic-related deaths whereas the figure for Orissa is a shocking The poverty-disaster link can be established here.  In Tamil Nadu, epidemic related deaths localised in 4 backward districts, in Orissa spread throughout the state indicating poor public provisioning of health care.  No death due to heat wave reported in Tamil Nadu inspite of warm climate indicating possibility of quicker access to emergency care.  In Orissa, the bulk of disaster loss is borne by the coastal districts which are not only at much higher levels of per capita income, but also are better off in terms of infrastructure and human poverty criteria than the interior districts. This is in part the consequence of locational vulnerability to climatic hazards, and may also reflect the greater degree of urbanization and higher density of population of the coastal districts.

31  Flood deaths are higher in Tamil Nadu than Orissa because of higher population density in the former.  Fire related deaths in Tamil Nadu are higher than in Orissa and are concentrated in the industrialized belt of Chennai, Tiruvallur, Kancheepuram and Vellore

32 Correlations – Poverty with disaster impacts Orissa Of HCR with % permanent housing % ST 0.72 % SC % temporary housing Deaths per 100,000 population - floods Deaths per 100,000 population - cyclone Deaths per 100,000 population - heatwave Deaths per 100,000 population – fire Deaths per 100,000 population - epidemics -0.41

33

34 Correlations – Poverty with disaster impacts Orissa Of % SC with % permanent housing % temporary housing 0.37 Deaths per 100,000 population - floods 0.16 Deaths per 100,000 population - cyclone Deaths per 100,000 population - heatwave Deaths per 100,000 population – fire 0.21 Deaths per 100,000 population - epidemics 0.23

35 Correlations – Poverty with disaster impacts Orissa Of % temporary housing with Deaths per 100,000 population - floods 0.21 Deaths per 100,000 population - cyclone 0.40 Deaths per 100,000 population - heatwave 0.22 Deaths per 100,000 population – fire 0.10 Deaths per 100,000 population - epidemics 0.46 Population exposed (per 100,000 total population) 0.57 Population exposed to floods (per 100,000 total population) 0.51 Population exposed to cyclone (per 100,000 total population) 0.54 Population exposed to lightning (per 100,000 total population) 0.31 Population exposed fire (per 100,000 total population) 0.65

36 Orissa

37 Tamil Nadu

38 Orissa Tamil Nadu

39 Tamil Nadu Orissa

40 Conclusions  The correlations presented are indications of relationship existing  Two states taken contrast each other in development trajectories and nature of state policy i) Orissa historically less developed, agricultural, subsistence economy, a section of population adversely impacted by degrading natural resources. Inefficient state in intervening for welfare. ii) Tamil Nadu, historically well developed, industrial economy, with a long history of welfare interventions. Efficient welfare state

41 Way forward  This report should lead to developing data base of households in disaster prone areas. This should lead to longitudinal data sets. Disaster management has been mainstreamed in India in the 11 th Plan Document and such data can be useful.  Move towards district level poverty estimates  Improvement in Disinventor data itself.