Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Putting Children First: Session 1.6.A Yele Batana - Do demographics matter for the poverty of African children? [23-Oct-17]


Published on

Putting Children First: Identifying solutions and taking action to tackle poverty and inequality in Africa.
Addis Ababa, Ethiopia, 23-25 October 2017

This three-day international conference aimed to engage policy makers, practitioners and researchers in identifying solutions for fighting child poverty and inequality in Africa, and in inspiring action towards change. The conference offered a platform for bridging divides across sectors, disciplines and policy, practice and research.

Published in: Government & Nonprofit
  • Be the first to comment

  • Be the first to like this

Putting Children First: Session 1.6.A Yele Batana - Do demographics matter for the poverty of African children? [23-Oct-17]

  1. 1. Do Demographics Matter for African Child Poverty? Yele Batana, World Bank, John Cockburn, Université Laval & PEP,
  2. 2. OUTLINE  Introduction  Main demographic features  Methods of poverty adjustment  Age group poverty comparisons  Between-country poverty comparisons  Sensitivity analysis  Conclusion
  3. 3. INTRODUCTION • Strong correlations between per capita poverty and demographics (household size and composition). • National poverty lines are often established based on a reference household with given size and composition.  First, the basic caloric requirement of an adult is defined  An average food consumption structure is used to derive the required food expenditure • The international poverty line is determined as mean of national lines for the 15 poorest countries. • Failure to address the issue may lead to underestimate poverty, especially for African children.
  4. 4. INTRODUCTION • How to obtain more accurate child poverty measure and make more appropriate between-country comparisons? • Deaton (2003) and Ravallion (2015) suggest the use of a reference household as a pivot for equivalence approach. • Newhouse et al (2017) estimate child global poverty using this suggestion  child-adult gaps remain significant. • What happens when focusing on African region where demographic disparities are high among and within countries?
  5. 5. MAIN DEMOGRAPHIC FEATURES • There are significant disparities between countries in terms of demographics. • On average size varies from 3.5 to 9.5 members. Figure 1: Average household sizes and standard deviations in African countries
  6. 6. MAIN DEMOGRAPHIC FEATURES • The composition of household, measured by the average proportion of children varies between countries. • Share of under-18 varies from 20% to over 50%. Figure 2: Proportion of children in African countries
  7. 7. METHODS OF POVERTY ADJUSTMENT • Equivalence scales  Traditional equivalence scales  Deaton (2003) and Ravallion (2015) suggestions  The search for a "pivot" household  Pivot based on the average caloric requirement of 2100 cal  Pivot using international poverty line Eq ref Eq ref Ny y N N  
  8. 8. AGE GROUP POVERTY COMPARISONS • With adjustment between groups of child disappear. • Child-adult gap is reduced from 11.4 to 6.7 percentage points. Age groups Per capita approach FAO/WHO equivalence scale Square-root equivalence scale 0-4 52.8 46.4 43.8 5-9 50.1 46.6 43.0 10-17 48.8 46.8 40.2 0-17 50.4 46.6 42.1 +18 39.0 39.9 37.0 All 44.5 43.2 39.5 Table 1: Poverty rates in Africa by age group ($1.90 a day, 2011 PPP)
  9. 9. AGE GROUP POVERTY COMPARISONS • Breakdowns by household size confirm gap reductions. • The gap is lowest for households of 3 or 4 members. • No clear monotonous trend with size but growing trend with number of children. Figure 4: Differences in poverty between children and adults
  10. 10. BETWEEN-COUNTRY POVERTY COMPARISONS • Countries with high average household sizes and child shares  high reductions in child poverty. (Mali, Senegal, Niger, Burkina Faso, etc.) Figure 5: Differences between adjusted and initial poverty rates for children by country
  11. 11. BETWEEN-COUNTRY POVERTY COMPARISONS • Mixed results for adult poverty, with half of countries experiencing reductions while the other knows increases. Figure 6: Differences between adjusted and initial poverty rates for adults by country
  12. 12. BETWEEN-COUNTRY POVERTY COMPARISONS • Child-adult gaps reduced by more than half in 9 countries. (Cape Verde, Chad, Ethiopia, Lesotho, Liberia, Mali, Mauritania, Niger, and South Sudan) Figure 7: Differences in poverty between children and adults by country
  13. 13. SENSITIVITY ANALYSIS • Child poverty is sensitive to scale factor but not to child discount factor. • Child-adult poverty gap is sensitive to both factors. Figure 8: Child poverty in Africa by child discount and scale factors Figure 9: Child-adult poverty gap by child discount and scale factors
  14. 14. SENSITIVITY ANALYSIS • This confirms previous results, and the sensitivity of adult poverty to child discount factors. Figure 10: Child and adult poverty incidence by child discount or scale factor
  15. 15. CONCLUSION • Poverty may be biased for some household groups when demographics are different from that of the reference. • As a result, poverty is not be comparable between countries with various demographics as in Africa. • The real challenge is to properly remove the bias caused by demographics on poverty measurement. • Adjustment is not about canceling child-adult poverty gap, but should to capture the real inequality in wellbeing distribution among children and adults.