The United Nations Development Program (UNDP) has supported the conduct of an intensive data validation to address missing or truncated information from the local poverty index data collection process by the Liberia Institute for Statistics & Geo-Information Service (LISGIS).
This is part of Phase One of the Community-Based Local Multidimensional Poverty Indicator (CB-LMPI) survey. The validation aimed to identify and rectify data discrepancies and was used as an opportunity to share field experiences on data cleanup.
It is a follow-up on engaging communities to address issues of incomplete or truncated data collected.
The exercise held in Nimba and Gbarpolu counties brought together over 25 participants from counties who participated in the recent survey at various locations.
The primary aim was to lay a solid foundation for designing a robust household survey instrument for data collection across selected electoral districts in Bomi, Bong, Cape Mount, Gbarpolu, Lofa, Nimba and Rivercess Counties.
It can be recalled that last year, UNDP supported LISGIS to collect qualitative data focusing on rural community poverty dimensions aligning with the development of local Multidimensional Poverty Indexes (MPIs) in Liberia, emphasizing a co-creation approach.
The process was designed to capture the subjective experiences and perspectives of individuals, households, and communities regarding the root causes and dynamics of poverty.
It was followed by a validation and training workshop in January this year on Local Poverty Measurement which facilitated the development of questionnaires for the field deployment of digital data collectors in selected communities.
During the data submission process, critical questions were found unanswered or answered incompletely, resulting in missing or truncated data.
This issue, attributed to enumerator oversights, respondent non-responses, or technical glitches, poses a significant challenge to the completeness and accuracy of the collected information.
It is in this regard that the data validation workshop held March 11- 24, 2024 in Ganta and Gbarpolu became relevant.
Speaking during the exercise, UNDP National Economic Specialist Stanley Kamara, explained that to address the data discrepancies, enumerators are tasked with revisiting forms, contacting respondents for missing information, and reviewing their notes and records to complete data entry.
Kamara emphasized that the workshop was organized against this backdrop to establish an agreement on emerging key dimensions, indicators, and their respective weights as well as to conduct a technical review of the dataset cleanup and preliminary insights and assess implications.
He said as part of the corrective measures for data validation and refinement, enumerators will perform additional household revisits to collect additional testimonies and information to address the issue of missing or truncated information.
“The team is committed to monitoring and resolving these issues through training sessions on data collection processes, ensuring meticulous data management practices, and conducting follow-up visits to ensure resolution,” Kamara noted.
The UNDP National Economic Specialist said the exercise when completed successfully in the targeted counties, will pave the way to produce the first-ever multidimensional poverty profile for a community or electoral district.
This invaluable data will further inform evidence-based resource allocations, contributing to more targeted poverty eradication strategies.
The UNDP Regional Service Center for Africa (RSCA) is pioneering the “New Poverty and Inequality Metrics” project, aimed at refining comprehensive, inclusive, and integrated program solutions within targeted UNDP Inclusive Growth initiatives.
With a focus on marginalized communities, the project utilizes local-level data on multidimensional poverty and inequality. Operating in regions of Burkina Faso, The Gambia, Liberia, and Sierra Leone, it seeks to bridge the gap between national-level poverty assessments and grassroots realities.
Employing a collaborative approach, the project ensures inclusive representation of poverty nuances. Community engagement initiatives have led to the formulation of evolving dimensions and indicators, now undergoing validation at the local level.
