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.