Data Analyst | Applied Econometrics | Causal Inference | Machine Learning | Data Science

Multidimensional Poverty Comparison in Africa (2011 vs 2018)

📊 Tracking Multidimensional Poverty in Africa
This visualization compares deprivations (in % of the population) across 9 essential dimensions between 2011 and 2018, using data from the Global MPI (OPHI – Oxford).

🗝️ Dimensions Covered:

  • Child Mortality
  • Years of Schooling
  • School Attendance
  • Cooking Fuel
  • Sanitation
  • Drinking Water
  • Electricity
  • Housing
  • Assets

✅ Key Findings

  • Notable improvements in access to electricity, education, and household assets in many countries.
  • However, persistent or stagnant deprivation remains in critical areas like housing and safe drinking water in others.
  • The map provides a powerful snapshot of country-level progress, though inter-country comparisons should be made cautiously due to context-specific factors.

🧰 Tools Used

  • Data: Global MPI – Oxford Poverty and Human Development Initiative (OPHI)
  • Visualization: Python, Seaborn, Matplotlib

📷 Visualization

MPI Comparison Heatmap

🏷️ Tags

#DataForDevelopment, #MPI, #Africa, #DataScience, #Python, #GlobalMPI, #OPHI, #DevelopmentEconomics, #PovertyMapping, #IDH, #DataViz