Robustness & Measurement of Multidimensional Poverty Index In Iraq
DOI:
https://doi.org/10.33095/n4w7ca27Abstract
Purpose: This paper aims to measure poverty in Iraq and its sub-indicators using a multidimensional methodology. It also examines the robustness and sensitivity of the estimated indicators and models the determinants of poverty through a binary logistic regression approach.
Theoretical framework: Poverty is commonly measured through two primary methodologies. The first is a one-dimensional approach, which defines poverty as insufficient income to meet a specific set of needs required for a decent standard of living. The second is a multidimensional approach, which aligns with Amartya Sen's capabilities framework. Sen conceptualizes poverty as "the deprivation of basic capabilities rather than merely as lowness of incomes, which is the standard criterion of poverty identification" (Sen, 1999, p. 87). Income, while significant, represents just one dimension of capabilities and cannot substitute for other crucial aspects that contribute to poverty, such as deficiencies in health, education, and employment.
Design/methodology/approach: Previous studies on modeling poverty determinants in Iraq have predominantly employed a one-dimensional approach focused on income poverty. While valuable, this approach provides an incomplete understanding of poverty's multifaceted nature. This study proposes an indicator to measure poverty in Iraq using a multidimensional methodology. The analysis incorporates three dimensions of the global Multidimensional Poverty Index (education, health, and standard of living) and adapts the measurement indicators to reflect Iraq's specific context. Data from the sixth edition of the Multiple Indicator Cluster Survey (MICS-6) conducted in 2018 was utilized, employing the Alkire-Foster method to compute multidimensional poverty indicators.
Findings: The estimates revealed that 27% of Iraq's population experienced multidimensional poverty, with a multidimensional poverty gap of 11.7% and an intensity of poverty at 43.5%. The binary logistic regression results indicated that higher educational attainment of the household head and an improved wealth index significantly reduce the likelihood of multidimensional poverty. Additionally, households in rural areas were found to be more vulnerable to multidimensional poverty than those in urban areas.
Research, Practical & Social implications: This study seeks to enhance researchers' focus on poverty by exploring its diverse and multifaceted dimensions within the Iraqi context. By incorporating relevant and updated variables, it aims to enrich the discourse on poverty measurement and analysis.
Originality/value: The proposed indicator serves as a valuable analytical tool for identifying the most vulnerable individuals and highlighting the specific dimensions in which they face deprivation. This enables policymakers and stakeholders to allocate resources effectively and design targeted interventions to alleviate poverty.
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References
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