Poverty Index as a Tool for Adaptation Intervention to Climate Change in Northeast India.
Malini Nair, N. H. Ravindranath, Nitasha Sharma, Ruth Kattumuri and Madhushree Munshi | July 2014
The Inter Governmental Panel on Climate Change (IPCC) (2007) reports that the number of extreme events of precipitation and temperature in India are projected to increase in the short-term. The negative effects of this climate change in rural populations of India may include crop and livestock loss, livelihood risk, health and sanitation disruptions and shelter risk. Overseas Development Assistance, in the form of aid, will help the rural communities in countering these losses; several development agencies already require that the adaptation to climate change risks be included in as project activities in the aid program. However the accurate targeting of developmental aid is often difficult in developing countries due to uneven and cluster-like development of areas. To help counter this problem, we develop a poverty index intended to assist the prioritisation of the development aid towards the communities at risk, in order of their need. The district-wise poverty index was created for seven states of North-East India, a region that has high imbalances in development, to exhibit its effectiveness. The poverty index has been developed from the district-wise data available from the North-East Data Bank (DoNER). The indicators chosen were selected to adequately represent the poverty of the people as well as to act as a prioritising mechanism in a data scarce region. The inclusion of a Gini coefficient of land distribution is new to the development of a poverty index, this is a tool included to capture the high inequality in land distribution pattern in North East India, which in turn affects the distribution of income, since most of the population is Agriculture-dependent. Although primarily developed for North-East India, this poverty index can be used in developing countries with regional imbalances of development. If the biophysical factors affecting vulnerability are known, this index can be used in a weighted combination with vulnerability.