The Determinants of Inequality and Income Gap between Urban and Rural Areas in Cameroon: Evidence from the ECAM3 Household Survey

Abstract

This paper analyzes the determinants of income and the urban-rural income gap to highlight the urban-rural inequality problem in Cameroon. It concurrently uses the OLS regression, the conditional quantile regression as well as the Blinder-Oaxaca decomposition techniques to achieve this objective. The findings of OLS estimations show that human resources and social as well as physical capital play a major role in the improvement of welfare. Household size reduces the consumption expenditures both in rural and urban areas. The regions where the households reside also affect consumption expenditures. Household heads who work in the services sector and trade are better-off than those working in the other sectors of the economy. However, quantile regressions results show that households headed by the old people enjoy a higher level of welfare in the upper quintiles of the distribution of consumption. Household heads who work in the industrial sector have a negative relationship with consumption at the 10th quintile of the distribution of household expenditures in the urban area. In the rural area, household heads working in the services sector have a positive relationship with consumption only at the 50th and 90th percentiles of the distribution of expenditures, whereas those belonging to the 10th quintile have a negative relationship with consumption. In the rural area, the average time span spent to reach an asphalted road has a stronger positive impact on the consumption of households belonging to the 90th percentile of the distribution of expenditures. Being a member of an association has a significant positive effect only on the consumption of households belonging to the 10th quintile of the expenditures distribution. The study results derived with the help of the Oaxaca-Blinder decomposition method show that 59 percent of the welfare gap between urban and rural areas may be explained by differences in the characteristics, and most particularly in physical assets and education. The remaining 41 percent of the welfare gap is explained by discrimination.