Beneficiaries of N5k Stipends was done by GEJ – Presidency

During the 2015 general elections, President Buhari had promised to pay stipends to poor Nigerians every month.

That program was kicked off late last year under the social investment program.

Questions had been raised as to how the Presidency identified and selected beneficiaries of the program.

The presidency revealed that a Community-Based Targeting (CBT) model of the World Bank was used.

It further revealed that the model was actually the brainchild of former President Goodluck Jonathan, GEJ.

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Vice President Yemi’s spokesperson, Mr. Laolu Akande, made the revelations.

He said Jonathan’s model was used in nine States including Bauchi, Borno, Cross Rivers, Ekiti, Kwara, Kogi, Niger, Osun and Oyo.

Akande explained how the CBT model was used two years ago to identify most of the beneficiaries in the pilot states.

“There is no way anyone can describe the selection of the beneficiaries of the CCT as partisan.

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“The beneficiaries from eight of the nine pilot States were picked even before this administration came into office.

“First, the officials at Federal level, working with the State officials, identify the poorest Local Government Areas.

“They use an existing poverty map for the State.


According to Akande, a team of locals is identified and trained to sensitize leaders in their communities.

“Various poverty criteria have been thrown up so far.

“In some cases, people have said it’s the number of times they eat.

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“Another poverty indicator is the number of times firewood is used in the house or the size of farmland.

“Then the groups resume in plenary and report back the criteria and parameters discussed.

“Once that is done at the groups, everybody comes together again with names compiled by each group.

“When the same name features in at least two of the three groups, it is qualified to be listed on the Social Register.

“At this stage, we now enumerate the members of the household and open a bank account for each of the caregivers.

“We do this by capturing the biometric data of households identified as among the poorest and vulnerable.”