Urban Poverty and its Dynamics in Ethiopia: Evidence from Panel Household Survey
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Date
2018-10
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Addis Ababa University
Abstract
Although there are some empirical researches undertaken on poverty in Ethiopia, there is a need
for new researches that make use of recent data set and improved methods. Moreover, little
research is done on the variables that affect the dynamics of poverty to understand what
determines households to fall into and move out of poverty. Using Ethiopian Socioeconomic
Survey (ESS) wave 2 (2013/14) and wave 3 (2015/16) data, this research identified the
correlates of poverty, and the factors that determine the movement of households into and out of
poverty. To this end, Kripfganz and Schwarz’s sequential (two-stage) regression is used as a
primary tool of analysis. The findings from this sequential regression are then compared with
two other alternative methods of estimation: Logit Random Effect regression and Logit Fixed
Effect regression. The research found that dependency ratio, age of household head and the
square of age of head of household are strongly associated with poverty of households.
Moreover, it was found that households with illiterate heads have a higher probability of falling
into poverty, as compared to the base group of households headed by one with adult and
informal education. A multinomial logistic regression undertaken to capture the probability of
moving into and out of chronic poverty showed that ownership of nonagricultural business has
the tendency to decrease the (relative) probability of a household being chronically poor, rather
than move out of poverty. The research finally recommended that the government need to design
polices and incentive packages for head of household to get into literacy programs. Family
planning scheme should also augment the poverty reduction programs as it reduces the
dependency rate. It is also recommended that the government needs to design appropriate
entrepreneurial-oriented economic policies and incentive packages that support households to
start up businesses.
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Keywords
ESS, Poverty, Poverty dynamics, Urban poverty