In the early 2000s, Colombia faced challenges with its poverty data: outdated methodologies led to fluctuating poverty statistics, and the public lost trust in the numbers. Supported by national experts and development partners such as The World Bank, ECLAC and UNDP, Colombia’s National Department of Administrative Statistics (Departamento Administrativo Nacional de Estadística - DANE Colombia) and Planning Ministry (Departamento Nacional de Planeación) set out to overhaul its approach.
The Two Requirements for Effective Statistics
Effective policy-relevant statistics must meet two critical requirements: they must be accurate, and the public must trust in their accuracy. Just as voting machines must count votes correctly and foster public confidence in the results, poverty data must not only reflect the true picture but also be perceived as reliable by society. This second requirement is distinct from and just as vital as the first.
The MESEP Process
Through the Misión para el Empalme de las Series de Empleo, Pobreza y Desigualdad (MESEP), Colombia created a transparent, participative process anchored in international standards. Over its course, MESEP achieved data consistency, reassessed poverty benchmarks, and instituted sustainable methodologies, developing interim methodology, and eventually a final approach. This effort led to a reestablished trust in Colombia’s poverty statistics, setting a benchmark for other countries facing similar challenges.
Resilience Through Change
Remarkably, this process demonstrated resilience by withstanding several changes in leadership and administration. Over 32 months, it persisted through transitions involving:
- Three directors of DNP
- Two directors of DANE
- Multiple deputy directors
- Two presidential administrations
This continuity, despite leadership changes, underscored Colombia’s commitment to institutionalizing transparent and credible poverty measurement; and the importance of having a sound and trusted process in place.
Lessons for Today
This transformation underscores the power of collaboration, transparency, and a commitment to data integrity. Colombia’s experience highlights the importance of robust, credible data as a foundation for effective policy and poverty reduction.
This experience is a concrete lesson for many other countries, sectors and policy relevant indicators at a time when trust on facts and evidence is at an all-time low. Sound statistics must be technically rigorous, but also accepted and understood by society.
Acknowledgment
The successful transformation of Colombia’s poverty measurement methodology through the MESEP was driven by the dedication and expertise of an exceptional team of Colombian experts. Key contributors included:
- Jorge Iván González, Manuel Ramírez, Carlos Eduardo Vélez, Mauricio Santa María, Juan Carlos Feres, Jairo Nuñez Mendez, and Alejandro Gaviria
- Christian Jaramillo, Carlos Sepulveda, Juan Mauricio Ramírez, and Roberto Angulo
- José Fernando Arias, Guillermo Rivas, Alejandro Mateus, Sandra Álvarez, Francisco Espinosa, Diana Carolina Nova, Rocío Bermúdez, and Claudia Gordillo
- Sandra Guayazán, Carlos Arturo Mora, R.Andres Castaneda Aguilar, Bernardo Atuesta Montes, Diana Esperanza Sánchez, and Silvia Esperanza Botello
- Daniel Valderrama, Juan Carlos Ramírez, Olga Lucia Acosta, Javier Herrera, Xavier Mancero, Darwin Cortés, Luis Carlos Gómez, Eduardo Freire, and Irma Parra
- Carolina Renteria, Hernando José Gómez, Esteban Piedrahíta, Jorge Bustamante, and Héctor Maldonado
Their collaborative work helped create a transparent, credible poverty measurement framework that has set a new benchmark for Colombia and beyond.
In memory of my friend and mentor John L. Newman, a World Bank retiree, Global Lead on Welfare Measurement and Statistical Capacity, and Lead Economist who first represented the World Bank at the MESEP.
Full case study: World Bank Documentation
João Pedro Azevedo is the Chief Statistician at UNICEF and an expert in analyzing social and economic trends to inform public policy. Member of the MESEP as World Bank representative. He is passionate about leveraging data to promote equitable growth and development.