Poverty Incidence and its Determinants in the Estate Sector of Sri Lanka

Type Journal Article - Journal of Competitiveness
Title Poverty Incidence and its Determinants in the Estate Sector of Sri Lanka
Author(s)
Volume 4
Issue 1
Publication (Day/Month/Year) 2012
Page numbers 44-55
URL http://www.researchgate.net/profile/Vijayakumar_Sinnathurai/publication/230641749_Poverty_Incidence_​and_its_Determinants_in_the_Estate_Sector_of_Sri_Lanka/links/0912f5025320832b57000000
Abstract
Poverty measurement and analysis are needed to identify the poor, the nature and extent of
poverty and its determinants, and to assess the impact of policies and programmes on the poor.
The government of Sri Lanka has been spending huge sums of money for poverty alleviation
and social welfare since its independence. Yet, poverty is still severe and widespread in Sri
Lanka, especially in the estate and rural areas .The objective of this study is to find out and
analyze the significant determinants of the incidence of poverty in the estate sector where the
highest level of chronic poverty and unemployment exist. The national and regional poverty
survey data and other official socio economic cross sectional data from selected provinces were
used to analyze the extent of poverty in plantation sector in which 89 Divisional Secretariat
from provinces such as Subaragamuva, Central and Uva were considered for the analysis. The
econometric model were fitted and estimated in this study. Furthermore, Log transformation
was conducted and heteroskedasticity problem was detected with the use of statistical software.
The Ordinary Least Square (OLS) regression analysis clearly indicates that, variables
such as industrial employment, education, access to market and infrastructure significantly and
negatively affect the poverty incidence of the estate sector. Also, agricultural employment has a
negative impact but not significant. The R2 of 0.82 explains the statistical fitness of the model
and the Prob (F-statistics) also confirms it. Analysis with the Durbin–Watson stat confirms
that, there is no auto correlation between the variables. The results emphasize the need for
adapting policies for regional infrastructural improvement as well as market and educational
development in the plantation sector.

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