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Accueil du site → Doctorat → Australie → 2016 → Determinants of poverty and inequality in Botswana

University of Western Australia (2016)

Determinants of poverty and inequality in Botswana

Zelda Achieng Okatch

Titre : Determinants of poverty and inequality in Botswana

Auteur : Zelda Achieng Okatch

Université de soutenance : University of Western Australia

Grade : Doctor of Philosophy (PhD) 2016

The main objective of this study is to examine the determinants of poverty and inequality in Botswana over the period 2002/03 to 2009/10. Botswana has experienced an impressive economic growth in GDP by world standards, with annual growth rates averaging 9% between 1966 and 2008. Its real per capita income also increased considerably from US$469 to US$6261 during the same period. Moreover, poverty declined from 59% in 1985/86 to 30% in 2002/03 and to 20% in 2009/10. Unfortunately, this remarkable economic performance has not been accompanied by a decline in inequality. Botswana’s Gini coefficient increased from 0.573 in 2002/03 to 0.635 in 2009/10. Although there has been a decline in poverty over the years, its level still remains unacceptably high. This is inconsistent with Botswana’s national objectives, one of which is the reduction of poverty and inequality. The Government of Botswana has declared a target of total elimination of absolute poverty by 2016. Hence, Botswana makes an interesting case for such a study given the increasing inequality levels and high poverty levels in the midst of impressive economic performance.

Using data on Botswana from the Household Income and Expenditure Survey (HIES) of 2002/03 and the Botswana Core Welfare Indicator Survey (BCWIS) of 2009/10, several techniques are adopted to examine the determinants of poverty and inequality. First, ordered probit regressions, levels regressions and quantile regressions are employed for estimating the determinants of poverty at household level. Second, sub-group inequality decomposition, factor income decomposition and regression-based inequality decomposition are utilised to determine factors driving income inequality at household level in Botswana. Third, a static microsimulation model is utilised to examine the impact of VAT changes, during the period under consideration, on poverty and inequality in Botswana. The study further decomposes the vertical, horizontal and re-ranking effect of VAT.

The findings of the study indicate that the most dominant determinant of poverty in Botswana is lack of education, with primary education being an important factor for reducing income inequality. A similar impact is also observed in regards to number of livestock owned per household. Other important determinants include number of children per household ; the number of cattle owned per household ; and age of the household head. The study also finds that VAT changes in Botswana have negligible impact on poverty but a significant impact on inequality. The findings of this study are expected to have significant policy implications for Botswana given its national objectives of reduction of inequality and elimination of poverty by 2016.


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