Abstract:
Poverty brings to the forefront in economic development agenda in successive governments since independence in Sri Lanka. Thus, Sri Lanka has achieved higher human and social development bringing the country to the top of South Asian Region. Despite of the long-lasting ethnic conflict which hindered the economic development of the country, poverty head count ratio has been reduced tremendously by 2010. However, regional and sectoral disparities are significantly large and key concerns yet. Eighty three percent of the poor located in rural sector depicts that the poverty incidence in Sri Lanka is totally a rural phenomenon today. Thus, there is a need of detailed poverty analysis to have a clear understanding of the fundamental causes of poverty in the rural sector separately for developing an effective strategy to tackle the root causes of poverty.
This study focused on the key factors that determine household poverty in rural sector in Sri Lanka and to examine the behavior of the poverty determinants over time using disaggregated HIES data from 1990 and 2010. Thus, this study contributes likely determinants of household poverty in the rural sector using multivariate regression analysis (probit regression).
The estimates of the probit regression demonstrate almost all the covariates are statistically significant and economically meaningful. Increasing the number of years of schooling of the head of the household, and the other family members decreases household poverty in the rural sector. Further, age of the household head, head employment in public sector, head employed in non-agriculture sector, female adult ratio and foreign remittances are negatively correlated with household poverty. Conversely, the household size, dependency ratio, female headed household and head employed in private sector or self-employed are positively correlated with household poverty in the rural sector.
Almost all the coefficients (both positive and negative factors) show the declining trend of their impact on poverty over time while the magnitude of the female adult ratio has increased. Only variable that has change over time is head belong to minority group. In 1990, if the head is ethnic minority they are less likely to be poor, but in 2010 they are more likely to be poor in the rural sector.