Estimation of Aspect Based Multidimensional Poverty in Rural Haryana
Advances in Research · pp. 1–8 · Published 10 Jul 2017
10.9734/AIR/2017/34765Abstract
The issue of poverty estimation in India has been drawing attention since independence. The process for measuring poverty in India was initiated in early sixties, when a working group from planning commission provided a quantification of minimum food and non-food requirements of individuals for a healthy living. Theoretical developments on poverty measurement have gradually shifted from the traditional unidimensional approach to the multidimensional concept. [1] Pointed out that the study of poverty should identify and analyze attributes than monetary which directly influence the individual welfare. In the present study, estimation of poverty in rural Haryana has been undertaken on the aspects of drinking water, sanitation and housing facilities. For estimation of the poverty, the secondary data on selected indicators of drinking water, sanitation and housing facilities from 69th round of National sample survey office (NSSO) survey have been utilized. The multidimensional poverty index (MPI) using the dual cut-off method based on the counting approachhas been applied for estimation of the aspect based multidimensional poverty in rural Haryana. It involves counting the different types of deprivation that individuals experience at the same time. These deprivation profiles are analysed to identify who is poor, and then used to construct a MPI. Using the MPI, the districts Mewat, Rohtak, Palwal, Jhajjar and Fatehabad have higher value of MPI and indicating high level of poverty while districts Rewari, Kaithal, Bhiwani, Mahendragarh, Kurukshetra, Faridabad and Ambala were found in better condition. Effective awareness programmes about various schemes provided by government should be conducted so that villagers get to know about various benefits and the ways of approaching for getting benefits given by state/central government.
Cited by 2
A. Mehta · International Journal For Multidisciplinary Research · 2023
Nitin Tanwar · Economic Affairs · 2019
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