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Food and Nutrition Security in Papua New Guinea: Correlates of Individual Expenditure Levels

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WORKSHOP
Linkages of Agriculture, Nutrition and Economic Development
Co-Organized by IFPRI, UPNG, INA, Australian National University, and Department of Foreign Affairs and Trade
JUN 12, 2019 - 09:00 AM TO 12:30 PM +10

Published in: Government & Nonprofit
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Food and Nutrition Security in Papua New Guinea: Correlates of Individual Expenditure Levels

  1. 1. Food and nutrition security in Papua New Guinea: correlates of individual expenditure levels Regina Nukundj, Emily Schmidt and Rachel Gilbert Department of Agriculture and Livestock International Food Policy Research Institute June 12, 2019 Holiday Inn Port Moresby, Papua New Guinea
  2. 2. A call for engagement in Papua New Guinea • El Niño affected an estimated 700,000 people in 2016, creating severe food shortages • Climate shocks (drought / flood / frost) and natural disasters significantly affect rural household food security • 80% of the population in PNG is semi-dependent on rain-fed subsistence farming (Bourke, 2017) • However, lack of current rural data collection or production statistics exist for PNG
  3. 3. • The recent Multi-Sectoral National Nutrition Policy, 2016- 2026 and the National Food Security Policy, 2018-2027 used old survey data: 1. National Demographic Health Survey (2006) 2. NSO Household and Income Expenditure Survey (2010) 3. NSO National Population Survey (2011) 4. National Nutrition Survey (2005) • For more recent evidence-based policies, there is a need for a regular national agriculture and rural food system survey PNG lacks baseline and monitoring data to inform evidence-based policy development
  4. 4. • 2018 household survey on food systems designed to inform agriculture and nutrition linkages in rural households • Survey focused on four districts where World Vision is currently implementing programs • Nuku in West Sepik • Maprik in East Sepik • Middle Ramu in Madang • Buin/Siwai in ARoB Collaborative effort to inform food production, consumption and household resilience
  5. 5. 2018 household survey of rural food systems in PNG • Implemented from May to July 2018 • Interviewed 1,026 households from 70 communities in 4 areas: • Survey aimed to understand food systems in rural PNG and the resilience of those systems • Agricultural production • Labor; income sources • Consumption / expenditure • Weather and economic shocks • Experiences of food insecurity • Nutritional status of children
  6. 6. On average, 70% of value of food consumed is own-produced 70% 47% 69% 84% 71% 28% 50% 29% 12% 28% 0% 20% 40% 60% 80% 100% All Households ARoB East Sepik Madang West Sepik Share of value of food consumed by source Gift Purchased Own produced • Own-production in Middle Ramu survey households makes up 84% of consumption • ARoB is less dependent on own production, however market price fluctuation and cash crop production shortfalls would affect household buying power
  7. 7. Own produced food links directly with calorie intake • Suggested calorie intake of an average individual: 2,250 kcals per person per day • In all regions, poor households are not consuming the daily recommended calorie level 0 500 1000 1500 2000 2500 3000 3500 4000 Non-Poor Poor Non-Poor Poor Non-Poor Poor Non-Poor Poor Non-Poor Poor National ARoB East Sepik Madang West Sepik Caloriesperpersonperday Average calories per person per day by poverty status Other (inc. dairy) Fats Vegetables Fruits Meat/Fish/Eggs Starch Grain Calorie Target
  8. 8. Food security: Access to food during the 4 weeks prior to the survey • Overall, 45% of sample households worried about having enough food during the four weeks prior to the interview • In Middle Ramu, 65% of the sample households worried about not having enough to eat due to lack of food • About 19% of the households in Nuku district went to sleep hungry due to lack of food 45% 9% 54% 65% 48% 13% 0% 13% 17% 19% 0% 10% 20% 30% 40% 50% 60% 70% All HHs ARoB East Sepik Madang West Sepik Worry not have enough food Eat less Go to sleep hungry
  9. 9. Shocks to agricultural production; coping strategies used 25 24 14 10 0 5 10 15 20 25 30 Floods Drought or irregular rains Crops damaged by insects, disease, animals Price fluctuations Most important recent shock, percent of households reporting 608 233 208 187 seek assistance from wontok rely on less preferred less expensive food worked for food only borrowed food, helped by relatives Coping mechanisms employed, number of households reporting • About 25% of households reported experiencing a flood or a drought during the last 5 years • More than half of households depend on their Wantok for assistance if their crops fail • Approximately 25% rely on less preferred foods or worked for food only to meet food needs
  10. 10. Large consumption differences exist between poor and non-poor individuals 0 500 1000 1500 2000 2500 3000 Non-Poor Poor All Households Calories/person/day Other (inc. dairy) Fats Vegetables Fruits Meat/Fish/Eggs Starch Grain 0 10 20 30 40 50 60 70 Non-Poor Poor All households Gramsofprotein/person/day Approximately 48% of the sample is living below the (spatially adjusted) poverty line of 4.1 kina per person per day (1.23 USD per person per day) TargetTarget
  11. 11. Want to understand the correlates of increased expenditure levels Why are some households better off? • Use regression analysis to understand associations between higher income levels and household and biophysical characteristics • Want to take into account a series of factors that may affect household income: Variables included in OLS regression Effect Sig. Household head age - ** Whether head is a male or female Education completed of household head ** Household size - *** Number of males in household (age 15-64) Number of females in household (age 15-64) + * Formal wage employment + ** Household has a migrant + *** Head’s parents born in the village + ** Land ownership + *** Experienced drought in the past 5 years - *** Experienced flood / heavy rains in past 5 years + * Average rainfall 1989-2018, mm/year Elevation (meters above sea level)
  12. 12. Establish that total expenditure is a good measurement Asset index includes 6 items: Chair (table chair or upholstered chair) Radio Generator Solar Panel Mobile phone Bicycle 468101214 Expenditure(Kina/person/day) 0 .2 .4 .6 .8 1 Asset index 95% CI lpoly smooth Expenditure is spatially-adjusted. • Data were collected between May – July, 2018: seasonal differences may be present in overall consumption expenditure data • Comparing expenditure data with a variety of asset indices suggest that the data are representative of overall income levels within the sample
  13. 13. 46810 Expenditure(Kina/person/day) 0 2 4 6 8 10 Household size 95% CI lpoly smooth Expenditure is spatially-adjusted. 456789 Expenditure(Kina/person/day) 20 30 40 50 60 Age of household head (years) 95% CI lpoly smooth Expenditure is spatially-adjusted. • As the household head age increases, the overall per capita expenditure decreases • As the household size increase, the overall per capita expenditure decreases Household composition is significantly correlated with expenditure levels
  14. 14. 5678 Expenditure(Kina/person/day) 0 2 4 6 8 10 Land owned and cultivated (hectares) 95% CI lpoly smooth Expenditure is spatially-adjusted. • For each extra hectare of land an individual owns, their total expenditure increases by about 1.5% • If an individual earned at the poverty line of 4.1 kina per day, an extra hectare of land would increase their expenditure to 4.16 kina per day Individuals that own more land have moderately greater total expenditure
  15. 15. Education is important in rural areas • Individuals in a household whose head attended some school (literacy program, incomplete primary, etc.) are associated with a 5% greater expenditure compared to no schooling • Similar relationship for individuals in a household whose head completed primary school • Secondary school completion is associated with a 10% increase in overall expenditure
  16. 16. Drought has significant and potentially lasting effects on overall expenditure • Individuals that reported experiencing a drought during the last 5 years are associated with 5% less total expenditures compared to individuals that did not experience a drought
  17. 17. Ideas for supporting greater rural resilience • Decrease the barriers to entry for primary education • Substantially reducing or not requiring school fees may increase overall enrollment and school attendance • Providing school feeding programs to incentivize families to invest in education • Develop greater / more expansive agricultural extension programs to promote crop diversification, improved seed varieties, small livestock ownership, etc. • Promote income diversification including off-farm work (small businesses) and wage labor • Provide ‘insurance’ via social safety net programs (work-for-food / cash transfer programs) to insure that vulnerable populations are receiving basic needs.
  18. 18. Thank you

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