In recent years, the Philippines has witnessed a shift in its policy priorities. During the last administration, poverty reduction efforts were overshadowed by a strong emphasis on addressing crime and drug-related issues. This focus diverted attention and resources away from tackling the persistent challenges of poverty and inequality. However, the current administration has commendably redirected its focus towards poverty alleviation, as evidenced in the Philippine Development Plan 2023-2028. This most recent PDP notably prioritizes inclusive growth and emphasizes sustainable development including human capital development in the context of innovation and the need to be globally competitive. 

Globally, there is a growing interest in accurately monitoring and understanding poverty trends especially with the commitment to the 2030 Agenda for Sustainable Development and the Sustainable Development Goals. This interest is crucial for developing effective strategies to combat poverty. In the Philippines, the Philippine Statistics Authority (PSA) employs two primary measures for government to track poverty: (a) the traditional money-metric poverty incidence, which assesses poverty based on income levels of households; and (b) the multidimensional poverty index (MPI), a more comprehensive approach that considers various factors affecting an individual’s quality of life, such as education, health, and living standards. The MPI makes use of data from another PSA survey, the Annual Poverty Indicator Survey, but efforts have been made to estimate MPI with the pilot Community Based Monitoring System. 

There are, however, growing concerns that these measures might still not reflect the actual portrait and extent of poverty in the country despite the PSA’s adherence to global statistical standards and practices. This article aims to delve into these issues, exploring how poverty might be more pervasive in the Philippines than official statistics suggest. By examining the limitations of current poverty measures, this discussion seeks to provide a more nuanced understanding of poverty in the Philippines and the challenges ahead in addressing it based on accurate data.

Counting the poor

In a 2019 Rappler article, the process of measuring poverty in the Philippines was outlined, an approach that is fairly common to many developing countries. This process involves three key steps:  

1. Defining a welfare indicator 
2. Setting a poverty line.  
3. Summarizing the poverty data. 

The first step typically involves indicators based either on household income or consumption. Household income includes all income sources such as employment, social transfers, and rent. Meanwhile, household consumption encompasses all expenditures, including both market purchases and non-market items valued at local market prices. Consumption-based measures are often favored for assessing poverty, especially in lower-income countries. This is because consumption tends to be more stable than income, which can fluctuate yearly and throughout one’s life. People generally find it easier to recall what they’ve spent rather than what they’ve earned, making consumption data more reliable. Income data, on the other hand, is frequently underreported due to forgetfulness, tax evasion motives, or illegal income sources. It may also be difficult for income to be reported accurately among those with vulnerable jobs, such as farmers and various workers in the informal sector. The accuracy of income data can be higher among those with stable salaries, making it relevant in certain contexts. The bias in expenditure data is complex; for instance, the poor might overstate their spending due to social pressures. The Family Income and Expenditure Survey (FIES), the triennial survey conducted by the PSA, can also lead to respondent fatigue given its length (as average interview time is five hours), thus affecting data accuracy. Additionally, income data collection is often simpler than tracking numerous consumption items. Given all these issues, it is not clear-cut whether consumption-based measures are superior to income-based ones for poverty assessment, although the advantage slightly goes to consumption. A global survey by the United Nations Statistical Division showed a split preference: half of the surveyed countries use expenditure measures, 30% use income (including China, Malaysia, and the Philippines), and 12% use both.

As regards the second step, the Philippines, similar to many developing countries, sets its poverty lines using the cost-of-basic needs (CBN) approach. This method calculates a food threshold based on calorie requirements, supplemented by a non-food allowance to establish a total poverty threshold. The Philippines uniquely employs province-specific “low-cost” menus in both urban and rural areas as an artifice to determine the food threshold, with a focus on nutritional adequacy. However, there are ongoing concerns about the accuracy of these menus in reflecting the actual annual food budget of the poor, and efforts are being made to revise them for more consistent and accurate poverty lines.

On the other hand, the World Bank uses international poverty lines to monitor global poverty. The first Sustainable Development Goal (SDG) targets the eradication of extreme poverty, defined as living on less than $2.15 a day in 2017 PPP prices. In 2021, the Philippine Statistics Authority (PSA) reported that the national poverty lines averaged P12,030 per month for a family of five, closely aligning with the $3.65 PPP international poverty line for lower middle-income countries. However, this figure is significantly lower than the $6.85 PPP line for upper middle-income countries, suggesting an underestimation of poverty as the Philippines approaches this income category.

Table 1. Official (Monthly) Poverty Lines vs International Poverty Lines for a family of five 

Year	Food Threshold	Official Poverty Line	$2.15 equivalent in PhP	$3.65 equivalent in PhP	$6.85 equivalent in PhP
2015	6,620	9,478	6,089	10,337	32,933
2018	7,553	10,756	6,678	11,336	36,118
2021	8,379	12,030	7,276	12,352	39,354

The final step in poverty measurement involves the National Statistics Office such as the PSA summarizing poverty data from its household surveys typically with the poverty rate or poverty incidence, i.e., the proportion of poor people. Poverty incidence is released by the PSA for both households and persons. The PSA has also generated poverty rates at smaller areas by innovatively integrating survey data with censuses, and even with satellite imagery. 

The PSA also innovatively integrates survey data with censuses and satellite imagery to generate poverty rates at smaller areas. However, comparing poverty rates across areas can be misleading due to varying total populations. For example, regions like the Bangsamoro Autonomous Region of Muslim Mindanao (BARMM) may have high poverty rates but a smaller number of poor persons compared to other regions. Traditional poverty measures, such as poverty incidence, fail to capture the intensity and severity of poverty. While other measures like the poverty gap and squared poverty gap exist, they are complex and less used in practical applications.

Underestimation of poverty among specific groups

The current approach to measuring poverty, a challenge not exclusive to the Philippines, assumes all members of a poor household are poor. This methodology likely leads to an underestimation of poverty among specific groups in the Philippines, such as women, persons with the disability, and the elderly (Table 2). This is due to its failure to account for household composition variations and unequal welfare distribution within households.

Table 2. Poverty Incidence among Basic Sectors: 2015, 2018, and 2022 

	2015	2018	2021
Women	23.9	16.6	18.4
Children (below 18(	33.5	23.9	26.4
Youth (aged 15 to 30)	20.5	14.7	16.6
Senior Citizens (aged 60 and above)	14.4	9.1	10.3
Urban Folk	13.2	9.3	11.6
Rural Folk	34.0	24.5	25.7
Migrant and Formal Sector Workers	14.4	8.8	10.2
Farmers	40.8	31.6	30.0
Fisherfolk	36.9	26.2	30.6
Self Employed and Unpaid Family Workers	26.2	18.0	18.7
Persons with Disability (15 and over)	–	14.7	17.2

Towards more accurate poverty assessments

To address these issues, using equivalence scales can offer a more accurate poverty assessment by adjusting the poverty line based on household composition. Additionally, emerging methods like the collective household model (also called the workhorse model) which consider resource distribution and consumption economies within households. For example, research in Bangladesh shows that a third of elderly, women, and children in households classified as non-poor often live below the international poverty line, indicating that poverty in these groups can be under counted.    

Adopting these new methods in the Philippines could significantly impact poverty reduction policies and actions. By acknowledging the diverse needs within households, these approaches can lead to more effective strategies, ensuring that no Filipino is left behind in the country’s development path. – Rappler.com

Dr. Jose Ramon “Toots” Albert is a professional statistician who holds a PhD in Statistics from the State University of New York at Stony Brook. Toots is a Senior Research Fellow of the government’s think tank Philippine Institute for Development Studies (PIDS), and a past president of the country’s professional society of data producers, users and analysts, the Philippine Statistical Association, Inc. for 2014-2015.  From October 2012 to February 2014, he was seconded to the now defunct National Statistical Coordination Board (NSCB) as the NSCB Secretary General. He is currently a professorial lecturer at the De La Salle University. He has worked in nearly three dozen economies across the world largely on poverty analysis and related development issues such as gender equality, social inclusion, and income inequality.