# **2. Enhancing Policy Effectiveness through Multidimensional Poverty Measures**

Multidimensional poverty measures provide a broader perspective on human deprivation by encompassing various aspects such as health, education, and standard of living. Unlike monetary poverty measures that focus primarily on income, multidimensional indicators capture a wider range of deprivations, offering policy makers a more comprehensive understanding of the factors contributing to poverty. This approach allows for the design of integrated interventions that address the root causes of poverty across various dimensions. For example, policies aimed at reducing multidimensional poverty can simultaneously target issues such as access to health care, educational opportunities, and social inclusion, holistically tackling the interconnected aspects of poverty and improving overall well-being.

Furthermore, multidimensional poverty measures are particularly valuable for capturing the experiences of vulnerable and marginalized groups, who may face various forms of deprivation not fully represented by income-based measures alone. For instance, women, children, older people, and people with disabilities often face multidimensional forms of deprivation that incomebased measures struggle to capture (Alkire and Foster, 2011; UNDP, 2019; World Bank, 2011; UNICEF, 2016). By incorporating dimensions that, one way or another, touch gender inequality, intergenerational poverty, and social exclusion, multidimensional poverty indices provide a more inclusive representation of poverty, ensuring that the most vulnerable populations are not overlooked in policy discussions and resource allocation.

Research in development economics has highlighted that income-based poverty measures may not fully capture the complexity of human deprivation. Notably, Amartya Sen's work underscored the importance of considering multiple dimensions of well-being—such as health, education, and social inclusion—alongside income when assessing poverty (Sen, 1999). This broader perspective has led to the development of the MPI, which measures poverty across these various dimensions (Alkire, 2007). Studies using MPI suggest that traditional income-based poverty measures might underestimate the extent of poverty and overlook disparities in deprivation across different dimensions (Alkire et al., 2015).

Moreover, empirical evidence indicates that economic growth does not uniformly lead to reductions in monetary poverty, which underscores the value of a multidimensional approach to poverty measurement (Alkire et al., 2013). For instance, research by Cruz et al. (2015) demonstrated that economic growth can sometimes disproportionately benefit specific groups or regions, leaving others behind and leading to persistent monetary poverty. By considering multiple dimensions of deprivation, multidimensional poverty measures provide a more nuanced understanding of poverty dynamics. This allows policy makers to tailor interventions more effectively to meet the distinct needs of various population groups (Alkire et al., 2015).

Studies have demonstrated that multidimensional poverty measures are particularly effective in identifying vulnerable and marginalized populations whom income-based measures may not fully represent. For example, Alkire & Santos (2013) found that women and children are often disproportionately affected by multidimensional poverty, especially in access to education and health care. Similarly, Palmer et al. (2015) highlighted that people with disabilities face specific challenges that income-based measures may not capture, emphasizing the need to consider disability as a dimension of poverty. These findings support multidimensional measures as a complementary tool to provide a more comprehensive and inclusive poverty assessment.

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