Nutritional impact of food price shocks and policy implications

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1 Nutritional impact of food price shocks and policy implications Emmanuel Skoufias and Hassan Zaman Lead Economists Poverty Reduction and Equity Group The World Bank April 2010

2 Structure Context poverty and nutrition trends Trends in global and domestic food prices Measuring the impact of the 2008 food crisis on undernourishment Food price shocks and micro-nutrient intake: evidence from Indonesia Policy issues and concluding thoughts

3 Faster progress in poverty reduction compared to nutritional indicators The number of poor people living on less than $1.25 a day in developing countries fell from about 1.8 billion in 1990 to 1.4 billion in 2005 from 42 percent of the population to 25 percent and the MDG target of halving poverty likely to be met. However, the developing world is not on track to halve the proportion of people who suffer from undernourishment. FAO estimates that the incidence of hunger increased to 1.02 billion in Moreover the proportion of children under five who are underweight declined from 33 percent in developing countries in 1990 to 26 percent in 2006, a much slower pace than needed to halve it by million preventable under-5 deaths associated with poor dietary quality

4 Lasting impact of economic shocks There are also significant long term impacts as households compromise on dietary diversity and cut back spending on health and education during crisis. e.g., Children born during droughts in Zimbabwe had significantly lower height during adolescence and enrolled into schools later than average. Under-five mortality went from 126 per 1000 in 1991 to 152 per 1000 in 1998 during the economic crisis in Cameroon. Here we focus our attention to the impacts of higher food prices on nutritional indicators and their policy implications.

5 Global food price trends Food price spike in 2008 but World Bank food benchmark index also increased 23% Jan-Dec 09

6 Domestic food price monitoring equally important Tracking domestic prices regularly is important in order to provide early warnings about food crises (eg Malawi in 2001, maize prices rose by 50% in one month following months of stability signaled food crisis) Domestic staple price increases in recent months in many countries greater than the rise in global grain prices (using FAO food price data in 58 countries). Localized factors conflict, supply disruptions, weather lead to divergence from global price trends especially in less integrated economies

7 Kenya maize prices compared with global prices

8 Domestic staple price increases (source Food Price Watch February 2010, World Bank) Price Increase, January October 2009 Average price increase, Country Food Item Caloric contribution Price Increase Country Food Item Caloric contribution Price Increase Nigeria Sorghum 13% 50% Mozambique Cassava 33% 61% Uganda Maize 10% 35% Dem. Rep. Congo Cassava 55% 60% Bhutan Rice.. 26% Sudan Sorghum 26% 38% Sudan Sorghum 26% 24% Kenya Maize 36% 21% Tanzania Maize 34% 23% Chad Sorghum 18% 18% Kenya Maize 36% 16% Burkina Faso Sorghum 27% 15% China Rice 27% 15% Tanzania Maize 27% 14%

9 Methodology for estimating undernourishment impacts of food price increases (details in Tiwari and Zaman (2010) The impact of economic shocks on global undernourishment Policy Research Working Paper 5215, The World Bank) 1. Estimate a calorie-income (Engel) relationship using a cross country panel for which data on per capita income (WDI) and per capita calorie consumption (FAO) was available (83 countries over 8 years, 742 observations) 2. Use income distribution data to generate a cumulative distribution function (CDF) for per capita income for every country. 3. Determine the minimum daily calorie intake threshold below which an individual is deemed undernourished.

10 Methodology for estimating nutritional impacts of food price increases (cont.) 4. Using the Engel relationship, determine what the income requirement for the threshold calorie level is. 5. Using the CDF we work out what fraction of the population cannot afford this level of calories, and use population weights to derive regional estimates for undernourishment. 6. When prices increase, Engle curve shifts down or to the right (price change multiplied by price elasticity of calories).

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12 Food price scenarios in 2008 and impact on undernourishment Partial Passthrough Full Passthrough % Increase from % 25% 35% 50% 35% 50% Sub-Saharan Africa 1% 4% 5% 7% 4% 6% Asia and Pacific -4% 6% 11% 19% 8% 14% Latin America and Caribbean 0% 10% 16% 24% 12% 18% Middle East and North Africa -1% 13% 20% 31% 15% 24% Total -2% 6% 10% 16% 7% 12% Baseline Full Pass through Partial Passthrough (incidence in millions) FAO % 25% 35% 50% 35% 50% Sub-Saharan Africa Asia and Pacific Latin America and Caribbean Middle East and North Africa Total

13 Bottom line estimate and methodological caveats Our preferred estimate relates to 35% price increase scenario (average food price change ) and partial pass-through of prices which implies 64 million more undernourished in 2008 relative to 2007 Caveats include (i) use of undernourishment as an indicator (ii) use of a single calorie price elasticity (iii) ignoring countryspecific variations in price pass through rates. We now transition to the next part of the presentation which focuses on micronutrient intake and the impact of shocks using the example of Indonesia.

14 Crises, Food Prices and the Income Elasticity of the Demand for Nutrients: Some Estimates from Indonesia (Skoufias E, S Tiwari, H Zaman 2010 forthcoming) Motivation Dietary diversity essential for addressing malnutrition Recent food price crisis heightened concerns about food security and deepening malnutrition. Nutrient-Income elasticity important parameter for policy (especially for cash transfer programs). Need have better understanding of how a policy variable may change at times crises in order to design more effective policies

15 Objectives 1. Estimate size of elasticity of demand for nutrients Macronutrients: calories, protein, carbohydrates, fat Micronutrients: calcium, phosphorous, iron, vitamin A (carotene), B1 (thiamin), C (ascorbic acid). 2. Whether elasticity of demand for nutrients varies with the economic conditions (e.g. level of relative prices for various food items)

16 Data and Context We use the 1996 and 1999 SUSENAS Surveys from Indonesia 7-day consumption recall survey more than 200 food items Same questionnaire applied at same period within the year 60,000 households interviewed in each survey round Representative of U/R areas within each province of Indonesia

17 Data The quantity of EACH food item converted to nutrient content using tables from Ministry of Health of Indonesia. Other studies usually apply conversion factors at group level (Pitt & Rosenzweig, 1985) Complications: Conversion factors missing for some food items (esp. prepared food) Nutrient-income relationship examined in 1996 (normal year) and in 1999 (crisis year when inflation was at its peak).

18 Methodology We conduct the analysis at two levels: 1. Examine the Starchy Staple Ratio (SSR) and assess its robustness to the price level using nonparametric and regression methods. SSR - the share of caloric availability derived from starchy staple foods (cereals and tubers). According to Bennett s Law this ratio is inversely related to the importance of inexpensive starches relative to higher quality, more expensive, and micronutrientrich foods in the diet. 2. Use pooled regression to estimate the elasticity of specific nutrients and test whether they are statistically different in the two periods.

19 Parametric Method Pooled Regressions OLS and IV ~ lnyjkt Dk Dt ln CON jkt ik pik X jt (ln CON jkt * D99) ik ( pik * D99) ( X jt * D99 i i ~ ) jt Here i, j, k and t index food group, household, geographic cluster of residence (village) and time period respectively. Accordingly, D k and D t are cluster and time fixed effects and D 99 is an indicator variable for CON: per capita household consumption p: cluster level price of food groups Y: Calorie share from major food groups, cereals and tubers(ssr), meat and fish, fruits and vegetables, dairy products and others.

20 Parametric Method Pooled Regressions (contd.) ~ lnyjkt Dk Dt ln CON jkt ik pik X jt (ln CON jkt * D99) ik ( pik * D99) ( X jt * D99 i i ~ X Controls - Logarithm of household size - No. of children 0-5 years of age, - No. of children 6-12 years of age, - No. of males and females and years of age - No. males grater than 55 years of age. - Whether the household head is a female, - A group of a group of dummy variables describing the educational level of the household head and his/her spouse, - The sector of employment of the household head and his/her spouse, (e.g. self-employed, unemployed or wage worker). ~ ) jt

21 RESULTS Bias due to measurement error (attenuation bias) in consumption expenditures is important and can result in misleading estimates IV estimates are generally larger than OLS estimates indicating that the attenuation bias due to errors in the measurement of CON may have overpowered the upward bias in the OLS that would be expected in case of correlated measurement errors. In both urban and rural areas, the elasticity of the complement of the calorie share from all food items other than cereals and tubers (1- SSR), declined significantly in The decline seems to be much larger in magnitude in urban areas.

22 Results In 1996, the elasticity of macronutrients are generally positive and significant and range from to for rural areas and to for urban areas. The elasticity for micronutrients range from to for rural areas and to for urban areas. The income elasticity seems to change significantly for some micronutrients (Vitamins A and C) while not at all for some others. For Vitamin A and Vitamin C, IV estimates are significantly lower in 1999 than they were in For all other micronutrients the income elasticity in 1999 = income elasticity in 1996

23 Policy considerations

24 Percentage of countries Percentage of countries Distribution of safety nets and food price policies during 2008 food crisis (source: Wodon Q and H Zaman (2010) Higher food prices in Sub-Saharan Africa: Poverty Impact and Policy Responses, World Bank Research Observer) Existing Safety Net Interventions (% of all 118 countries) Food Price Policies (% of all 118 countries) 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% -10% Cash transfer Food for work Food ration/ stamp School feeding 0% Source: Data based on responses from 118 country teams Source: Data based on responses from 118 country teams

25 Implications for safety net programs Since both calorie intake (hunger) and micronutrient shortfalls (dietary diversity) occur during food price spike nutritional supplementation programs need to be integrated with, or provided in addition to, cash-transfer safety net programs. Provision of fortified food based programs can be critical in achieving both calorie intake and diversity objectives while bearing in mind higher costs of food transfers. Nutritional interventions ought to focus on -9 months to 2 years age range. Most safety net programs are designed for either school age children or adults.

26 Implications for economy-wide food policies Subsidies important to distinguish between universal subsidies which depress incentives and take up large share of budget vs. smaller subsidies targeted at vulnerable groups and for fortified foods Stock management need to promote holding fortified foodgrains though professional management essential to minimize waste Tax cuts should they be targeted to nutrient rich food groups? 26

27 Concluding thoughts Global and domestic price trends of food staples can differ significantly; monitoring domestic staple prices essential as an early warning system for food crises Food price spikes lead to households both poor and vulnerable non-poor - switching away from nutrient rich foods and to lower calorie intake both can have irreversible nutritional consequences food crisis policy instruments likely to be re-used during any future food price spike so significant scope for technical assistance during a non-crisis period to make them more effective overall and specifically more nutrition-sensitive 27