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IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India, 2002 
  
5.0 CONCLUSIONS 
For many developing countries like India, natural resource 
endowments are the most significant component of national 
wealth. There is a danger that poorly designed policies, rapidly 
increasing populations and poverty could irretrievably damage 
their capital stock. Data on both socio-economic and natural 
resource variables are usually unavailable at sufficient detailed 
level (cadastral information or even individual settlements) to 
examine this. Collecting these data sets are also unaffordable 
because of competing demands for limited budgetary resources. 
What this desk study tired to show was that despite these 
practical problems, existing sources of wasteland statistics in 
conjunction with other socio-economic data could lead to a 
more aggregative, regional-level analysis of natural resource 
use-poverty-public policy linkages and suggest the appropriate 
institutional interventions for poverty alleviation. 
In conclusion, many macro-economic policy instruments, such 
as investments in rural infrastructure, education etc result in 
stock changes of physical capital in identifiable areas and thus 
possibly could alter the relationship between incidence of 
poverty and natural resources degradation. The economic 
policy instruments, if translated from conventional monetary 
aggregates to spatial ‘stocks’ or areal densities (Beckmann and 
Pun 1985, Jagannathan Vijay N, 1989), it is possible to evolve 
the appropriate institutional interventions, which could lead to 
substantial poverty reduction as well as enrichment of natural 
resources base. 
Appendix -I 
Rural Infrastructure Index 
Rural infrastructure consists of certain key indicators, which 
facilitate livelihood access. They reflect certain basic amenities 
available in rural areas such as: 
Road length per thousand persons 
Percentage of villages without electricity 
Percentage of households without electricity and 
Percentage of households without piped water 
Road length facilitates transport of more food to the villages. 
Electrification helps better production. Electrification also helps 
processing industries and other non-agricultural enterprises, 
which would enhance livelihood access and food access. 
Better water supply and availability of electricity in the 
households would enhance the capacity for enterprise. 
Productivity of the rural population would go up if there were a 
reduction in the time and effort involved in carrying water and 
fuel from long distances. Rural infrastructure has a direct 
bearing on livelihood access and food access. For livelihood 
access, markets and credit institutions are also very important. 
The chosen indicators are first converted into indices and then 
averaged together to get the composite index. The method of 
calculating the index is as follows for all the indicators, except 
*Road length per thousand persons' 
lij 2 (Xij - Ximn) / (Ximx - Ximn) 
Xij = ith Rural infrastructure indicator in the jth state 
Ximx- ith Rural infrastructure indicator with maximum value 
among all the states indicating the worst situation (This gets the 
value of one) 
Ximn = ith Rural infrastructure indicator with minimum value 
among all the States indicating the best situation (This gets the 
index value of Zero) 
In respect of Road length per thousand population, the 
following formula was used to get the Index of road length. 
Iij 2(Ximx -Xij )/(Ximx - Ximn) 
I RI = Index of Rural Infrastructure is calculated as follows: 
IRI= ( X (li) /n) * 100 
*' 2 1 to 4 Rural infrastructure indicators - 
'j 2 1 to 16 states in the country 
The composite Index is the average of all the four indices. Each 
index measures the distance of the state from the worst possible 
situation, compared to the distance between the best and the 
worst states. A composite rural infrastructure index of 99 
percent for Bihar means that Bihar has to travel 99 percent of 
the distance to reach the level of state with best infrastructure. 
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Beckmann, M and T Pun, Spatial Economics: Density, 
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Dalton, George, 1981, Research in Economic Anthropology , 
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Food Insecurity Atlas of Rural India, 2001,World Food 
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Food and Agricultural Organisation (FAO), (1996), Food for 
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Food and Agricultural Organisation (FAO), (2000), The State 
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