Poverty Analysis of Rice Farming Households: A Multidimensional Approach.

Autor: ADENUGA, A. H., OMOTESHO, O. A, OJEHOMON, V. E. T., DIAGNE, A., OLORUNSANYA, E. O, ADENUGA, O. M.
Předmět:
Zdroj: Albanian Journal of Agricultural Sciences; 2013, Vol. 12 Issue 4, p641-651, 11p
Abstrakt: The official measurement and analysis of poverty in Nigeria has historically relied upon the single dimension, consumption based monetary approach with little attention on multidimensional poverty assessment. This study was therefore carried out to assess the multidimensional poverty index of rice farming households in Nasarawa/Benue Rice Hub, Nigeria. The study employed stratified random sampling technique to select 149 rice farming households in the study area. Descriptive statistics, the Alkire and Foster Multidimensional Poverty Index Methodology using two different cut-off points and the Tobit regression model were the main analytical tools employed for the study. The results of the multidimensional poverty index analysis revealed that female headed households were poorer than the male headed households. On the overall, 66 percent of the rice farming households was multidimensionally poor. The study also showed that the rice farming households were deprived in 48 percent of the dimensions. A multidimensional poverty index of 0.32 was obtained for the rice farming households in the study area with varying values obtained for the male and female headed households. The result of the Tobit regression model showed that gender of the household head, health, marital status and membership of association were the major determinants of multidimensional poverty of the rice farming households in the study area. The study concluded that the rice farming households in the study area were multidimensionally poor. It was recommended that the government should give priorities to the development of the rural areas with special consideration for women through the provision of essential infrastructural facilities. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index