The poor are not evenly distributed within the country and they do not
share the same socio-economic and demographic characteristics. It is against
this background that analysis of the characteristics that differentiate the poor
from the non-poor in Ghana cannot be underestimated. Poverty indicators
make it possible to analyze the likely determinants and are, therefore, essential
for formulating policy interventions that may contribute directly or indirectly
to its alleviation. This study therefore aims at determining the most important
characteristics that differentiate poor households from non-poor households in
To achieve this objective, data was obtained from the Ghana Statistical
Service. It consists of 49,005 households surveyed in the country of which
17.2 percent were classified as being poor (extremely poor). The analysis of
the data relied mainly on logistic regression. It was found that the region a
household resides in, the number of persons in that household, access to
improved sources of water and sanitation, are the most important
characteristics. These and other interesting results are discussed.
CDR, C (2021). MODELING POVERTY STATUS OF GHANAIANS: A LOGISTIC REGRESSION APPROACH. Afribary.com: Retrieved April 15, 2021, from https://afribary.com/works/modeling-poverty-status-of-ghanaians-a-logistic-regression-approach-1
Coalition, CDR. "MODELING POVERTY STATUS OF GHANAIANS: A LOGISTIC REGRESSION APPROACH" Afribary.com. Afribary.com, 08 Apr. 2021, https://afribary.com/works/modeling-poverty-status-of-ghanaians-a-logistic-regression-approach-1 . Accessed 15 Apr. 2021.
Coalition, CDR. "MODELING POVERTY STATUS OF GHANAIANS: A LOGISTIC REGRESSION APPROACH". Afribary.com, Afribary.com, 08 Apr. 2021. Web. 15 Apr. 2021. < https://afribary.com/works/modeling-poverty-status-of-ghanaians-a-logistic-regression-approach-1 >.
Coalition, CDR. "MODELING POVERTY STATUS OF GHANAIANS: A LOGISTIC REGRESSION APPROACH" Afribary.com (2021). Accessed April 15, 2021. https://afribary.com/works/modeling-poverty-status-of-ghanaians-a-logistic-regression-approach-1