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PSNP essp nutrition_seminar_may2014

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- Ethiopia has high levels of childhood undernutrition, with 44% of children under 5 being stunted. Undernutrition negatively impacts health, education outcomes, and economic productivity. - The Productive Safety Net Programme (PSNP) in Ethiopia provides cash and food assistance to over 7 million people, with the goal of stabilizing assets and food security. However, directly reducing undernutrition is not a core objective of the PSNP. - Preliminary analysis finds no association between participation in the PSNP and measures of childhood undernutrition, such as height-for-age and stunting. While the PSNP increases food access, this does not appear to translate into improved nutrition outcomes for young children.

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Guush Berhane, IFPRI John Hoddinott, IFPRI Neha Kumar, IFPRI May 13, 2014 Page 1 The Productive Safety Net Programme and the nutritional status of pre-school children in Ethiopia: Preliminary Results
• Ethiopia has high levels of chronic undernutrition. DHS (2011) – 44% of children under five are stunted (Have a height for age z (HAZ) score < -2) • Why does this matter? – Intrinsic. Chronic undernutrition is a marker of high levels of deprivation. Healthy, well- nourished children is an important development objective in itself. – Instrumental. Children who are undernourished are less likely complete school, have poorer cognitive skills in adulthood and are less economically productive. Evidence from other countries shows that a one SD reduction in HAZ increases the likelihood of being poor in adulthood by 10 percentage points If you care about economic growth and poverty reduction in Ethiopia, you should care deeply about reducing undernutrition Page 2 Introduction and Context
• Ethiopia operates one of the largest social protection programmes in Africa: The Productive Safety Net Programme (PSNP). • The PSNP reaches more than 7 million people in drought-prone woredas in Afar, Amhara, Oromiya, SNNP, Somale and Tigray • The objective of the PSNP is to stabilize household asset levels (thereby preventing recurrent shocks from forcing households into destitution) and improve household food security • The PSNP: – Is well targeted – Delivers significant resources (cash and food) to beneficiaries – Reduces the food gap – Stabilizes assets Page 3 Introduction and Context
• The PSNP is “loosely meshed” with direct efforts to reduce undernutrition in rural Ethiopia • Health Extension Workers should be part of PSNP’s administrative structures that oversee beneficiary selection and that hear appeals • PSNP woredas are co-located in areas where the Community Based Nutrition Program has been rolled out. In our data: Page 4 Introduction and Context Year CBN established Percent children <5 in sample 2008 13 2009 29 2010 20 2011 12 2012 26
• This presentation discusses results that are: PRELIMINARY PRELIMINARY • We use data collected as part of the PSNP evaluation in 2008, 2010 and 2012 – Participation in the PSNP – Anthropometry (heights and weights), ~7,500 observations across three years – More limited data on child diet, 6-24m, interaction with HEW and community health volunteers, knowledge of good nutrition practices – Household characteristics affecting both PSNP participation and pre-school nutrition • We explore preliminary associations between PSNP participation, duration of operation of CBN and anthropometric outcomes, mindful that reductions in chronic undernutrition are not a specific objective of the PSNP • We discuss implications of these preliminary results Page 5 Introduction and Context
Page 6 Trends in undernutrition (children 6-59m) HAZ Stunting (%) 2008 2010 2012 2008 2010 2012 Tigray -2.18 -2.29 -2.17 58.6 60.7 57.8 Amhara -1.79 -1.86 -1.92 47.5 50.3 49.2 Amhara HVFB -1.94 -2.05 -1.92 53.6 55.0 51.9 Oromiya -1.71 -1.80 -1.53 46.1 47.9 42.8 SNNP -1.94 -1.69 -1.76 50.2 46.2 47.3 Total -1.90 -1.91 -1.81 51.1 51.4 48.9 Sample size 3041 2845 2482
Page 7 Trends in undernutrition by beneficiary status (children 6-59m) HAZ 2008 2010 2012 HH is PSNP beneficiary -1.98 -2.04 -1.88 HH is non-beneficiary -1.85 -1.79 -1.78
• Look at association between being a PSNP participant and anthropometric outcomes controlling for: – Child characteristics (age, sex) – Caregiver characteristics (age, schooling) – Characteristics of the household head (sex, age) – Wealth (livestock holdings) – Housing quality (materials used to construct roof, walls) – Access to towns – When CBN began in woreda – Region • In each survey year, we find no association between being a PSNP participant and: – HAZ – Stunting – WHZ – Wasting Page 8 Regression analysis
• Results do not change when we do the following robustness checks : – Including or dropping different sets of control variables – Changing variables (eg maternal age v log maternal age) – Running estimates separately by region – Restricting age ranges (eg 6-24m, 12-24m etc) – Measuring PSNP participation (eg Public Works beneficiary, duration of participation) • There are a number of extensions to be considered (which is why results are preliminary) – Improved accounting of selection into PSNP (eg thru use of matching methods) – Assess competing effects of PSNP transfers (which might ↑HAZ) and work effort (which might ↓HAZ) • But there are also reasons to expect that these extensions will not change these basic results Page 9 Regression analysis
Page 10 HAZ and maternal schooling -2.4-2.2 -2 -1.8-1.6-1.4-1.2 -1 0 1 2 3 4 5 6 7 8 Grades of schooling, mother 95% CI lpoly smooth kernel = epanechnikov, degree = 0, bandwidth = 1.08, pwidth = 1.62
In the last month: PSNP Beneficiary status in 2012 Have you been visited by a Health Extension Worker Have you been visited by someone from the Women’s Development Army Have you been given information about foods to feed young children Have you heard about information about foods to feed young children on the radio Does household boil drinking water before use? PSNP beneficiary 33.3% 18.2% 26.0% 14.9% 11.4% Non-beneficiary 33.4 14.5 28.5 20.2 11.2 Page 11 Access to information about nutrition No difference in access to information by PSNP status
Percent consuming any: Region Pulses Dark, leafy vegetables or Vitamin A rich fruits Other fruit or vegetables Milk or other dairy products Eggs Meat, poultry or fish Fats or oils Tigray 22.5 14.7 8.5 12.4 20.9 3.9 17.1 Amhara 16.0 16.0 12.3 21.7 7.5 6.6 21.7 Amhara HVFB 15.5 7.7 4.5 13.5 3.9 5.8 8.4 Oromiya 7.5 14.5 13.7 48.6 9.8 3.5 15.7 SNNP 4.0 30.5 12.0 37.5 5.5 2.5 15.5 All 11.5 17.3 10.7 30.7 9.1 4.1 15.3 Page 12 Foods consumed by children 6-24 months, previous day, by region, 2012 46 percent consumed none of these food groups 11 percent consumed three or more four percent consumed four or more Oromiya has highest % of dairy consumption and highest mean HAZ
• We see no association between PSNP participation and measures of undernutrition in these data • Important to remember that results are preliminary but also consistent with international experience • This is suggestive that an assumption that the PSNP alone can reduce undernutrition in rural Ethiopia may well be incorrect. Instead, a more powerful approach may well be one where the PSNP is “tightly wedded” – To direct nutrition interventions – Expansion of access to a wider range of foods Page 13 Summary and discussion

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PSNP essp nutrition_seminar_may2014

  • 1. Guush Berhane, IFPRI John Hoddinott, IFPRI Neha Kumar, IFPRI May 13, 2014 Page 1 The Productive Safety Net Programme and the nutritional status of pre-school children in Ethiopia: Preliminary Results
  • 2. • Ethiopia has high levels of chronic undernutrition. DHS (2011) – 44% of children under five are stunted (Have a height for age z (HAZ) score < -2) • Why does this matter? – Intrinsic. Chronic undernutrition is a marker of high levels of deprivation. Healthy, well- nourished children is an important development objective in itself. – Instrumental. Children who are undernourished are less likely complete school, have poorer cognitive skills in adulthood and are less economically productive. Evidence from other countries shows that a one SD reduction in HAZ increases the likelihood of being poor in adulthood by 10 percentage points If you care about economic growth and poverty reduction in Ethiopia, you should care deeply about reducing undernutrition Page 2 Introduction and Context
  • 3. • Ethiopia operates one of the largest social protection programmes in Africa: The Productive Safety Net Programme (PSNP). • The PSNP reaches more than 7 million people in drought-prone woredas in Afar, Amhara, Oromiya, SNNP, Somale and Tigray • The objective of the PSNP is to stabilize household asset levels (thereby preventing recurrent shocks from forcing households into destitution) and improve household food security • The PSNP: – Is well targeted – Delivers significant resources (cash and food) to beneficiaries – Reduces the food gap – Stabilizes assets Page 3 Introduction and Context
  • 4. • The PSNP is “loosely meshed” with direct efforts to reduce undernutrition in rural Ethiopia • Health Extension Workers should be part of PSNP’s administrative structures that oversee beneficiary selection and that hear appeals • PSNP woredas are co-located in areas where the Community Based Nutrition Program has been rolled out. In our data: Page 4 Introduction and Context Year CBN established Percent children <5 in sample 2008 13 2009 29 2010 20 2011 12 2012 26
  • 5. • This presentation discusses results that are: PRELIMINARY PRELIMINARY • We use data collected as part of the PSNP evaluation in 2008, 2010 and 2012 – Participation in the PSNP – Anthropometry (heights and weights), ~7,500 observations across three years – More limited data on child diet, 6-24m, interaction with HEW and community health volunteers, knowledge of good nutrition practices – Household characteristics affecting both PSNP participation and pre-school nutrition • We explore preliminary associations between PSNP participation, duration of operation of CBN and anthropometric outcomes, mindful that reductions in chronic undernutrition are not a specific objective of the PSNP • We discuss implications of these preliminary results Page 5 Introduction and Context
  • 6. Page 6 Trends in undernutrition (children 6-59m) HAZ Stunting (%) 2008 2010 2012 2008 2010 2012 Tigray -2.18 -2.29 -2.17 58.6 60.7 57.8 Amhara -1.79 -1.86 -1.92 47.5 50.3 49.2 Amhara HVFB -1.94 -2.05 -1.92 53.6 55.0 51.9 Oromiya -1.71 -1.80 -1.53 46.1 47.9 42.8 SNNP -1.94 -1.69 -1.76 50.2 46.2 47.3 Total -1.90 -1.91 -1.81 51.1 51.4 48.9 Sample size 3041 2845 2482
  • 7. Page 7 Trends in undernutrition by beneficiary status (children 6-59m) HAZ 2008 2010 2012 HH is PSNP beneficiary -1.98 -2.04 -1.88 HH is non-beneficiary -1.85 -1.79 -1.78
  • 8. • Look at association between being a PSNP participant and anthropometric outcomes controlling for: – Child characteristics (age, sex) – Caregiver characteristics (age, schooling) – Characteristics of the household head (sex, age) – Wealth (livestock holdings) – Housing quality (materials used to construct roof, walls) – Access to towns – When CBN began in woreda – Region • In each survey year, we find no association between being a PSNP participant and: – HAZ – Stunting – WHZ – Wasting Page 8 Regression analysis
  • 9. • Results do not change when we do the following robustness checks : – Including or dropping different sets of control variables – Changing variables (eg maternal age v log maternal age) – Running estimates separately by region – Restricting age ranges (eg 6-24m, 12-24m etc) – Measuring PSNP participation (eg Public Works beneficiary, duration of participation) • There are a number of extensions to be considered (which is why results are preliminary) – Improved accounting of selection into PSNP (eg thru use of matching methods) – Assess competing effects of PSNP transfers (which might ↑HAZ) and work effort (which might ↓HAZ) • But there are also reasons to expect that these extensions will not change these basic results Page 9 Regression analysis
  • 10. Page 10 HAZ and maternal schooling -2.4-2.2 -2 -1.8-1.6-1.4-1.2 -1 0 1 2 3 4 5 6 7 8 Grades of schooling, mother 95% CI lpoly smooth kernel = epanechnikov, degree = 0, bandwidth = 1.08, pwidth = 1.62
  • 11. In the last month: PSNP Beneficiary status in 2012 Have you been visited by a Health Extension Worker Have you been visited by someone from the Women’s Development Army Have you been given information about foods to feed young children Have you heard about information about foods to feed young children on the radio Does household boil drinking water before use? PSNP beneficiary 33.3% 18.2% 26.0% 14.9% 11.4% Non-beneficiary 33.4 14.5 28.5 20.2 11.2 Page 11 Access to information about nutrition No difference in access to information by PSNP status
  • 12. Percent consuming any: Region Pulses Dark, leafy vegetables or Vitamin A rich fruits Other fruit or vegetables Milk or other dairy products Eggs Meat, poultry or fish Fats or oils Tigray 22.5 14.7 8.5 12.4 20.9 3.9 17.1 Amhara 16.0 16.0 12.3 21.7 7.5 6.6 21.7 Amhara HVFB 15.5 7.7 4.5 13.5 3.9 5.8 8.4 Oromiya 7.5 14.5 13.7 48.6 9.8 3.5 15.7 SNNP 4.0 30.5 12.0 37.5 5.5 2.5 15.5 All 11.5 17.3 10.7 30.7 9.1 4.1 15.3 Page 12 Foods consumed by children 6-24 months, previous day, by region, 2012 46 percent consumed none of these food groups 11 percent consumed three or more four percent consumed four or more Oromiya has highest % of dairy consumption and highest mean HAZ
  • 13. • We see no association between PSNP participation and measures of undernutrition in these data • Important to remember that results are preliminary but also consistent with international experience • This is suggestive that an assumption that the PSNP alone can reduce undernutrition in rural Ethiopia may well be incorrect. Instead, a more powerful approach may well be one where the PSNP is “tightly wedded” – To direct nutrition interventions – Expansion of access to a wider range of foods Page 13 Summary and discussion