Poverty Incidence and its Determinants in the Estate Sector of Sri Lanka
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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Tomas Bata University in Zlín
2012-03-01
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| Series: | Journal of Competitiveness |
| Subjects: | |
| Online Access: | http://www.cjournal.cz/files/84.pdf |
| Summary: | 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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| ISSN: | 1804-171X 1804-1728 |