4Ps Effectively Targets Poor, But Data Gaps Persist

By Francis Allan L. Angelo

The Pantawid Pamilyang Pilipino Program (4Ps), the country’s flagship poverty reduction initiative, is effectively reaching its intended beneficiaries – yet persistent data accuracy challenges and urban-rural disparities are hampering its full potential, according to a new study from the Philippine Institute for Development Studies (PIDS).

The report, titled “Is the 4Ps Targeting and Reaching the ‘Right’ Beneficiaries? An Assessment of the Veracity of the List of Pantawid Pamilya/4Ps Beneficiaries,” was presented at a PIDS-hosted webinar on May 22 and assesses the veracity and targeting precision of the program, mandated under Republic Act No. 11310.

Among its major findings: nine out of 10 4Ps beneficiaries belong to the poorest half of Filipino households, and nearly 88 percent are within the bottom five per capita income deciles – figures that align favorably with international benchmarks for similar conditional cash transfer (CCT) programs.

“There has always been criticism against the 4Ps database that they may not all be really poor… but they are still low-income,” said Dr. Jose Ramon Albert, PIDS senior research fellow and lead author of the study.

Strong Targeting, But with Caveats

The study revealed that 71.9 percent of 4Ps beneficiaries come from the bottom three income deciles, pointing to strong progressive targeting.

Only a minimal portion of beneficiaries fall into the top income deciles, suggesting relatively low inclusion errors.

“This shows that the system generally works in directing aid to those who need it most,” Albert said. “But the challenge lies in the timeliness and accuracy of the data.”

While static information like names, birthdates and household addresses were found to be 99 percent accurate, dynamic data such as income, education, and employment status were considerably less reliable. Variables like marital status and employment consistency hovered between 37.7 percent and 67.4 percent accuracy.

“There are things that change very fast… even cell phone numbers,” Albert added. “So we need to find a way of making sure that we are constantly updating information.”

The lag is partly attributed to the 15-year gap between the original Listahanan data collection (2008–2009) and the 2024 verification survey, allowing considerable demographic and economic shifts to go unrecorded.

Urban Targeting Falls Behind

The most striking disparity is geographical: rural areas exhibit better targeting accuracy—around 70 percent—compared to only 40.6 percent in urban zones. In the poorest income decile, 27 percent of rural beneficiaries qualified, while only 7.9 percent of urban dwellers did.

Urban areas face unique challenges such as high-income volatility, informal settlements, and fluctuating employment conditions, which complicate traditional targeting mechanisms.

“We need specific urban models that can better capture or target the poor,” Albert emphasized.

Tech-Driven Overhaul

In response to these shortcomings, the Department of Social Welfare and Development (DSWD) is spearheading several digital reforms. At the center of this initiative is the Dynamic Social Registry, or iRegistro, designed to unify and digitize beneficiary data across government programs. It will enable real-time data syncing and allow beneficiaries to update their own records online.

“Regardless of the program, the moment a survey is completed, the information can become outdated immediately,” said Jimmy Francis Schuck, director of the DSWD’s National Household Targeting Office. “Employment status may change the next day.”

To strengthen identity verification and reduce fraud, DSWD will integrate the Philippine national ID system (PhilSys) with the registry, ensuring that updates and transactions are tied to a verified identity.

CBMS to Replace Listahanan

Complementing this effort, the Philippine Statistics Authority (PSA) is rolling out the Community-Based Monitoring System (CBMS), which will fully replace Listahanan by 2024.

“The 2024 CBMS will replace Listahanan… and authentication through the national ID will ensure beneficiaries are who they claim to be,” said PSA OIC-Deputy National Statistician Minerva Eloisa Esquivias.

CBMS, which combines geotagging, household profiling, and national ID verification, will underpin all social protection programs, including the Expanded Solo Parents Welfare Act and pensions for indigent senior citizens.

“We will make sure that all procedures in CBMS operations are followed and that there is technical assistance from us,” Esquivias added.

Graduation Support, Collaboration

From a policy standpoint, the findings have triggered renewed calls in Congress to fine-tune program graduation mechanisms and minimize targeting errors.

“There are constant complaints that the poor are left out, while non-poor households are receiving cash grants,” said Ma. Lourdes Mendoza, secretary of the House Committee on Poverty Alleviation.

Mendoza proposed that local government units (LGUs) support households transitioning out of the program, warning that premature exits without sustainable livelihood may result in families slipping back into poverty.

“Can LGUs support graduates of the program, especially in poor areas?” she asked. “We need to ensure that graduation reflects real improvements, not just box-checking.”

She also urged stronger interagency collaboration, noting that the 4Ps database should function as a “dynamic progress report card” that reflects health, education, and economic status in real time. However, limited data-sharing among government bodies like the Department of Labor and Employment (DOLE), PhilHealth, and the Department of Education has been a persistent bottleneck.

Innovation Roadmap

The study recommends adopting a three-phase implementation roadmap spanning 2025 to 2029. In the short term, DSWD and PSA aim to establish multi-source data bridges. The medium term focuses on data integration and real-time updates, while the long term envisions predictive modeling and artificial intelligence (AI) for poverty risk forecasting.

These tools will facilitate early intervention and potentially yield long-term cost savings.

“The technology exists; now we need the will and coordination to implement it,” said Albert. “Otherwise, we risk misallocating billions meant for the poorest Filipinos.”

As the Philippines moves toward more data-driven governance, the 4Ps program faces a critical turning point. While PIDS findings affirm the program’s strong targeting performance, its outdated data infrastructure demands immediate upgrades.

Without these reforms, the government risks misallocating public funds and failing to reach the poorest households.

“We owe it to every Filipino taxpayer—and to every family in poverty—to make this program smarter, faster, and more responsive,” said Mendoza.