USING THE MULTIDIMENSIONAL POVERTY INDEX

USING THE MULTIDIMENSIONAL POVERTY INDEX

For years, the government has relied on the Poverty Threshold Basket (PTB) method to measure poverty in the Philippines. This method assesses whether a household's income meets the minimum requirement for basic needs such as food, shelter, and clothing. While it has served as the traditional standard, it has its limitations, as poverty is a multidimensional issue that extends beyond mere income levels.

The good news is that there is now an alternative method of measuring poverty in the Philippines aside from the PTB method. Many countries worldwide are now using the Multidimensional Poverty Index (MPI) method, either in place of or alongside PTB, as a more holistic approach. The MPI assesses multiple factors that contribute to poverty, including health, education, and living standards.

There is nothing wrong with using both methods simultaneously. In fact, the data from both PTB and MPI could be compared to gain a better understanding of poverty incidence both locally and nationwide. The PTB method focuses on income sufficiency, while the MPI method examines whether households have access to essential goods and services. By analyzing data from both, policymakers can craft more comprehensive strategies to address poverty.

Personally, I find the MPI method more effective because it offers an opportunity to strategically remove households from the poverty line by ensuring they are no longer deprived of key goods and services. The MPI evaluates whether families have access to necessities such as clean drinking water, electricity, adequate housing, and education. By focusing on these deprivations, the government and non-governmental organizations (NGOs) can work towards sustainable poverty reduction.

However, I have noted that MPI has a certain weakness—it includes car or truck ownership as a criterion for determining whether a household is "not poor." This can be misleading, as not all families require personal vehicles to achieve a decent standard of living. Fortunately, I was able to clarify that having access to reliable public transportation can serve as a substitute for private vehicle ownership. Additionally, the MPI is flexible, meaning its criteria can be adjusted based on local economic conditions.

Since the MPI measures access rather than ownership, local government units (LGUs) and NGOs can play a crucial role in bridging gaps by providing necessary services and infrastructure. For example, instead of focusing solely on increasing household incomes, they can ensure that communities have access to quality healthcare, education, and utilities. This means that, in theory, certain households can "graduate" out of poverty simply by having access to essential services, even if their income remains low.

Just like the PTB method, the MPI method can be used to measure the incidence of poverty within an LGU. This means that, with the right strategies and interventions, it is possible for an LGU to become "poverty-free." Furthermore, with advancements in artificial intelligence (AI), it is now possible to analyze poverty status using machine learning tools. AI can process large amounts of data to identify trends, predict future poverty risks, and recommend targeted interventions.

That is my challenge to all LGUs across the country. Instead of depending solely on the national government to measure poverty in their areas, LGUs should adopt the MPI method and declare "data independence." By doing so, they can take ownership of poverty reduction efforts and implement localized solutions that directly address the needs of their communities.

I wonder which LGU will be the first to declare that they are "poverty-free" based on their own data analysis? More importantly, will they be able to sustain this status through continued efforts and strategic planning?

The conversation around poverty measurement is evolving, and by embracing the MPI, we can move towards a more inclusive and effective approach to eradicating poverty in the Philippines.

Ramon Ike V. Seneres, www.facebook.com/ike.seneres
iseneres@yahoo.com, 09088877282, senseneres.blogspot.com

04-08-2025

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