The Relationship Between Growth, Poverty And Income Inequality

Abstract

Mozambique like many other developing countries has faced lack of information and sometimes there is no detailed information about the poverty and inequality at district levels. This research investigates the quality of growth in Sofala province, a province which is located in the central region of Mozambique. Since the quality of growth comes from the analysis of poverty and inequality indicators, the research specifically investigates the relationship between growth, poverty and inequality thorough an assessment of the pro-poor growth of Sofala province during the period of 1996 to 1997 and 2002 to 2003. The methodology used to analyze the pro-poor growth in Sofala province combines both, qualitative and quantitative data. A recent technique of Poverty Mapping that user Small Area Estimation which consists of combining two data sources: Census and Household Survey was used to estimate poverty and inequality class of measures at disaggregated geographical units such as districts. Applying the technique of Poverty Mapping, a Census of 1997 and IAF 1996 to 1997 and IAF of 2002 to 2003 data sources were combined to update poverty and inequality indicators of Sofala’s 13 districts. The welfare measures of interest, poverty and inequality class of measures were updated applying consumption model using the household expenditure of 8,604.391 Meticais a day. Once the estimates were computed, maps creation using the GIS information was straightforward. A number of maps concerning poverty, inequality and the assessment of these indicators during the period 1996 to 1997 and 2002 to 2003 were presented. In general, the conclusion of this study shows that 59% of the districts have presented a pro- poor growth of 33% which presented an anti pro-poor growth, and 8% which present an inconclusive growth. In order to reduce poverty in Sofala province in general there is a need to design policies of poverty reduction. Some of the following points have to be taken into account: agricultural performance, the number of existing schools, hospitals and food security. These are the variables that appear to explain poverty and inequality in the province of Sofala.