Can monetary poverty measurement detect multidimensionally deprived? Evidence from Egypt
In: International journal of development issues, Band 23, Heft 1, S. 24-39
Abstract
Purpose
This paper aims to examine the mismatch between multidimensional deprivation and monetary poverty in identifying the poor in Egypt and investigates their determinants empirically.
Design/methodology/approach
The paper uses the Alkire-Foster multidimensional poverty measurement method using data from Egypt's 2017/2018 Household Income, Expenditure and Consumption Survey (HIECS 2017/2018). Using a logistic regression model, the paper assesses the empirical relationship between multidimensional and monetary poverty and their determinants at the aggregate level and by dimension.
Findings
The paper demonstrates a significant mismatch between multidimensional and monetary poverty measures, underscoring their complementary nature. Statistics indicate that both measures overlap in classifying 35.81% of Egyptians, whereas monetary poverty ignores 63.12% of multidimensionally poor in at least one dimension. Regression estimates show a significant moderate negative association between expenditure per capita and multidimensional poverty and its dimensions. Moreover, they show that household head's gender, age, education attainment, marital status, job proficiency, household size and location affect poverty mismatch and match in Egypt.
Practical implications
This paper offers Egyptian policymakers the multidimensional poverty index that enables more efficient designing and targeting of poverty alleviation programs and assessing current poverty alleviation programs to modify them if needed.
Originality/value
To the best of the authors' knowledge, this study is the first to examine the mismatch between both poverty measures in Egypt, using the recent full data set of HIECS 2017/2018. This paper confirms that depending only on monetary measures can send inaccurate insights for crafting effective social policies. Also, it offers policymakers a comprehensive insight into the country's poverty landscape, which enable more efficient design, targeting of poverty alleviation programs and monitoring their effectiveness.
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