A study of Some Poverty Measures Using Spatial Regression Analysis Case Study for Mauritania

Abstract

Poverty and welfare are dependent on many factors, such as access to services and command over resources provided by institutions and the environment, time constraints, incentives (market prices), behavior of the household and its members, dependency rate, etc. Poverty can thus be described, defined and thus understood in several ways. The central objective of the Millennium Goals, agreed by 149 countries at the UN Millennium Summit in New York, is the halving of poverty by 2015. In official discourse for example, by the World Bank and major donors almost every policy is currently assessed in relation to its impact on poverty, ranging from individual empowerment, debt relief to macro economic stabilization (Caterina, eta!., 2003). The lack of information on the determinants of poverty in many developing countries, especially in Mauritania is one of the serious inhibiting factors for devising correct and effective policies for poverty alleviation. Many studies have focused on providing poverty profiles of different countries (Appleton, et a!., 1999). The poverty profile is a descriptive tool that provides key information on the correlates of poverty. Although a poverty profile is insightful, such a bivariate exercise is limited in its usefulness because it shows how poverty levels are correlated with one characteristic at a time. In doing so, it does tend to simplify complex relationships. Poverty maps are other tools that provide important information on the spatial distribution of poverty within a country.