Examining Poverty Dynamics in Ghana: Evidence from Longitudinal and Repeated Cross-Sectional Data

dc.contributor.authorGafa, Dede
dc.contributor.authorHodey, Louis
dc.contributor.authorSenadza, Bernardin
dc.date.accessioned2024-04-10T13:53:52Z
dc.date.available2024-04-10T13:53:52Z
dc.date.issued2024-04-10
dc.description.abstractThis article examines poverty dynamics in Ghana using the Ghana Socioeconomic Panel Surveys (GSPS) and a synthetic panel based on repeated cross-sectional data (the Ghana Living Standard Surveys (GLSS). It provides insight into the extent of poverty mobility and persistence in Ghana, and the factors that explain poverty transitions. The results show that upward mobility has been a key feature of Ghana's poverty transitions between 2006 and 2019. However, there are still high probabilities of poverty persistence and downward mobility among initially poor and non-poor households, respectively. Furthermore, notable heterogeneities exist in poverty transitions across socioeconomic groups. Poverty is more chronic in rural areas and the northern parts of Ghana compared with urban and southern regions, respectively, and among households headed by persons from opportunity-deprived backgrounds. Other characteristics such as the gender of the household head, his/her occupation, and level of education, as well as the number of dependents, are important correlates of poverty persistence and downward mobility in Ghana. Hence, addressing chronic poverty requires targeted policies that foster more inclusive and sustainable growth in rural areas and northern parts of Ghana, and improved access to opportunities for people from disadvantaged backgrounds, the unemployed, and those in vulnerable employment. Key words: Poverty dynamics; Synthetic panel; Africa. JEL classification codes: D63; I32.
dc.identifier.urihttps://publication.aercafricalibrary.org/handle/123456789/3764
dc.language.isoen
dc.publisherAfrican Economic Research Consortium
dc.titleExamining Poverty Dynamics in Ghana: Evidence from Longitudinal and Repeated Cross-Sectional Data
dc.typeArticle
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