1. Monitoring Hunger & Food Security: Mirage or Reality? Pietro Gennari, Food and Agriculture Organization of the United Nations XX ICABR Conference, Ravello, June 26 - 29, 2016 Session 02-01: New Data for the Bioeconomy: Agriculture and Supply Chain

2. Global Food Security monitoring The Prevalence of Undernourishment (PoU) Methodology Recent criticisms The hunger metrics mirage: assumptions and proposals Monitoring hunger: from the MDGs to the SDGs The Food Insecurity Experience Scale (FIES) Assumptions The Rasch model The questionnaire Definition of a global standard Implementation strategy & main results Conclusions Outline

3. FAO mandated by member countries to monitor Food Security (Article 1 FAO Constitution). Role recognized by the international community Six editions of the World Food Survey from 1946 to 1996 1996 FAO World Food Summit set the global target to halve the number of hungry people by 2015 Indicator selected: Prevalence of Undernourishment (PoU) State of Food Insecurity in the World (SOFI) published yearly since 1999 MDGs - Target 1.C: Halve, between 1990 and 2015, the proportion of people who suffer from hunger PoU one of the 2 official MDG Indicators to monitor 1.C Progress at global, regional and country level reported in SOFI and in the Global MDG Report (since 2002) 2015 = Transition from the MDGs to the SDGs Goal 2 = “End hunger and malnutrition” with 5 targets & 3 MoI Global Food Security monitoring

4.  Definition: % of the population with an habitual daily energy intake lower than what is required for an active and healthy life. Comparison between:  Probability density function of habitual daily Dietary Energy Consumption of a representative individual, and:  Daily Minimum Dietary Energy Requirement (MDER)  Indicator of chronic hunger = captures the evolution of fundamental, not contingent, elements that drive long term nutritional status  Not supposed to monitor seasonal food shortages or temporary food price crises  Indicator monitoring only caloric intake  Not monitoring other types of nutritional deficiencies, not correlated with caloric deficiency  Need of a suite of indicators to monitor different dimensions of food insecurity and malnutrition Prevalence of Undernourishment (PoU)

5. Probability density function of habitual daily Dietary Energy Consumption of a representative individual MDER f(x) PoU

6. Choice of the distributional model: lognormal or skew-lognormal Mean: mainly from Food Balance Sheets, data reconciled with HH surveys whenever possible Coefficient of variation and skewness: measures of inequality: from HH surveys; model-based when HH surveys not available Threshold: Minimum Dietary Energy Requirement (MDER), weighted average of the minima of the ranges of “normal” requirement for each class of the population by sex and age Continuous effort to improve the methodology: – Major revision in 2012 – Methodological refinements in 2014 – Parameters updated regularly; Improve basic agricultural statistics in countries through a global programme of statistical capacity development Key Parameters

7.  Indicator reflects only trends in food supply, non in access to food  Elementary data used to compile the estimate are not reliable and methodology is too complex. Better assessment of undernourishment would be possible using only existing surveys  PoU underestimated because the MDER assumes a light physical activity level => most people in developing countries are subject to heavy physical work  FAO manipulation of hunger estimates to obtain more funding (overestimation of the impact of the food price crisis of 2008; underestimation due to the metodological revision of 2012)  Indicator overestimating progress in hunger reduction of countries with high fertility rates (P. Pingali: “The hunger metrics mirage: there’s been less progress on hunger reduction than it appears” PNAS, vol. 113 no. 18, 2016) Recent criticisms to the PoU

8.  Population growth affects only the denominator and not the numerator of the PoU. In reality:  Population and Undernourishment are not independent variables;  Population growth in poor countries is higher in poor families and therefore rapid population dymanics, coeteris paribus, should increase the poverty rate & the PoU.  This problem is common to all population-based relative indicators  Food aid is not taken into account in the total food supply of the FBS, which is not correct. “The hunger metrics mirage”: wrong assumptions

9.  Hunger target: absolute reduction rather than relative reduction. But:  Only monitoring absolute progress would completely overlook progress made in small food insecure countries. FAO has always monitored both the WFS and MDG hunger targets.  Any absolute target can be translated into an equivalent relative target, conditional to a certain rate of population growth.  The new SDG target pointing to “hunger eradication” overcomes this conundrum, as the target focuses on the final value not on progress.  Independent expert assessment of the reliability and suitability of the currently available hunger statistics. But:  Continuous peer-review by countries and international experts. PoU confirmed as SDG indicator to monitor target 2.1  Who will decide the composition of the independent scientific committee? To whom it will report?  Same arrangement needed for all the SDG indicators, not only the PoU  Validating the methodology, not every single country data “The hunger metrics mirage”: the right proposals?

10. Monitoring hunger: from the MDGs to the SDGs Target 2.1: By 2030, end hunger and ensure access by all people, in particular the poor and people in vulnerable situations, including infants, to safe, nutritious and sufficient food all year round  Focus on food access  the PoU combines food availability and food access  Target universal, not limited to developing countries  PoU is irrilevant for developed countries  Target more ambitious: eradicating, not halving hunger  The PoU threshold of 5% is too high  Emphasis on monitoring inequalities within countries  PoU estimates currently available only at national level  Need for real-time assessment to guide policy interventions  PoU projections based on 2-3 year old data

11. New indicator to monitor SDG Target 2.1 based on a direct measure of people’s ability to access food Prevalence of moderate or severe food insecurity in the population Enables assessment of the depth of food insecurity (moderate, or severe) => can be used in developed countries A new metric that can be used for both households and individuals. In the latter case, it allows proper analysis of gender related food insecurity disparities Short questionnaire (8 yes/no questions) can be easily applied in virtually any household or individual survey Rapid and low cost – enables timely global monitoring A sound statistical methodology (Item-Response Theory) allows assessment of reliability and precision of the measures Allows for disaggregation by socio-demographic groups or by geographical location. Governments can thus use the indicator for targeting interventions, and monitoring/measuring impact of policies/programmes Food Insecurity Experience Scale (FIES) 11

12. Assumptions Food insecurity conceptualized as the condition of being unable to access food in the desired quantity, quality and continuity The severity of the food insecurity condition is treated as a measurable latent trait – Although it cannot be directly observed, it is revealed by its consequences (coping strategies). – Typical FS experiences used to estimate the probability that each respondent belongs to a specific class of food insecurity severity (e.g. moderate or severe). The prevalence of food insecurity in a population, at a given level of severity, is estimated as the cumulated probability across respondents in a representative sample of the population Mild food insecuritySevere food insecurity Anxiety about ability to procure adequate food Compromising quality & variety of food Reducing quantities, skipping meals Experiencing hunger

13. The FIES Survey Module (individual) During the last 12 MONTHS, was there a time when: 1.You were worried you would run out of food because of a lack of money or other resources? 2.You were unable to eat healthy and nutritious food because of a lack of money or other resources? 3.You ate only a few kinds of foods because of a lack of money or other resources? 4.You had to skip a meal because there was not enough money or other resources to get food? 5.You ate less than you thought you should because of a lack of money or other resources? 6.Your household ran out of food because of a lack of money or other resources? 7.You were hungry but did not eat because there was not enough money or other resources for food? 8.You went without eating for a whole day because of a lack of money or other resources?

14. The Rasch model (G. Rasch, 1960)

15. The Rasch model (continued) The Rasch model implies that the raw score (i.e., simple sum of affirmative responses) is a sufficient statistics to estimate respondents’ severity – Individual measures of severity depend on the total number of positive responses, irrespective of which specific experiences were reported. Unexpected patterns, however, contribute to determine measures of mis- fit, used to test the empirical validity of the model – Use of raw score for classification is only legitimate if data conform to the model’s assumptions (no outliers; absence of multicollinearity among items) Conditional Maximum Likelihood (CML) can be used to estimate parameters: – It imposes no assumption on the shape of the distribution of the latent trait in the population (+) – Provides consistent estimates of standard errors under the Rasch model assumptions (+) – It only uses non-extreme response patterns, as severity parameters for zero or maximum raw score cannot be estimated (large samples are preferable)

16. Definition of a global standard Each survey produces an estimate only of the relative position of items and respondents on the scale of severity As a consequence, raw score based classifications are not directly comparable across countries A global reference scale is identified by comparing the normalized estimated severity of the 8 FIES items in all countries Each country’s scale is then equated to the global reference standard (using mean and the standard deviation of the common items only) The identification of common items requires an iterative process Items whose severity differ from the reference by more than a set tolerance value are treated as unique Unique items are still used for measurement in each country Thresholds are defined on the global reference scale

17. Implementation strategy & Main results Three pronged strategy: – Global data collection including the FIES module using the Gallup World Poll since 2014. For the 1 st time FAO produces indicator through direct data collection – Technical assistance provided to countries to introduce the FIES in national household surveys and eventually take over – Available national data on similar experience-based scales are calibrated against the global FIES and replace the GWP data In 2013 pilot surveys conducted in 4 African countries Since 2014 the FIES module included in all countries covered by the GWP (about 150 countries, covering more than 90% of the world population) March 2016, 47 th session of the UNSC: adoption of the FIES as one of the official indicators to monitor SDG target 2.1 May 2016, publication of the technical report and of the 2014 FIES results July 2016, launch of the FIES results for 2015 (baseline for SDG target 2.1)

18. Estimated prevalence of food insecurity in the adult population in 2015 18 Region / Country Grouping Moderate or Severe F.I. Severe F.I. World20.5 (±0.7)7.7 (±0.7) Developing regions Northern Africa18.6 (±1.5)6.4 (±0.9) Sub-Saharan Africa57.2 (±1.0)26.1 (±0.8) Latin America and the Caribbean Caribbeann.a. Latin America25.7 (±0.6)4.9 (±0.3) Eastern Asia6.3 (±1.1)0.9 (±0.3) Eastern Asia excluding China6.0 (±0.8)0.8 (±0.3) Southern Asia24.3 (±2.3)11.6 (±1.6) Southern Asia excluding India36.3 (±2.0)13.1 (±1.4) South-Eastern Asia21.1 (±2.3)5.7 (±1.2) Western Asia33.0 (±1.3)10.0 (±0.8) Oceanian.a. Caucasus and Central Asia11.4 (±0.8)1.7 (±0.3) Developed regions8.1 (±0.3)1.5 (±0.1) Least Developed Countries (LDCs)47.6 (±1.1)20.8 (±0.8) Landlocked Developing Countries (LLDCs)43.8 (±0.9)18.1 (±0.6) Small Island Developing States (SIDS)n.a.

19. 19 Rank correlation between FIES & selected development indicators IndicatorPeriodNFI mod+ FI sev Under-5 mortality rate20131380.846**0.781** Sanitation facilities (% with access)2012132-0.840**-0.765** Human Development Index2013138-0.831**-0.741** Adolescent fertility rate (women 15-19)20121400.817**0.759** Fertility rate20121410.815**0.795** Water source (% with access)2012135-0.806**-0.718** Gross National Income per capita2011-2013139-0.800**-0.700** Poverty headcount ratio at $1.25 a day2010-2013800.792**0.762** Life expectancy at birth2013138-0.783**-0.695** Poverty headcount ratio at $1.25 a day2011960.766**0.725** Prevalence of undernourishment20141370.759**0.684** Youth (15-24 years) literacy rate (%)2015115-0.749**-0.720** Adult literacy rate (%) projection2015115-0.732**-0.733** Multidimensional Poverty Index2009-2013470.712**0.601** Children aged 0-59 months Stunting2009-20131050.669**0.632** Gender-related development index (GDI)2013123-0.619**-0.655** Rural population (% )2011-20131400.614**0.517** Children aged 0-59 months Underweight2009-20131050.602**0.570** GINI index2009-2013960.468**0.499** Children aged 0-59 months Wasting2009-20131040.363**0.354** Children aged 0-59 months Overweight2009-201392-0.355**-0.334** (** 2-tail test P-value less than 0.01 )

20. Conclusions FAO mandated by member countries to monitor Food Security. Its measurement tools progressively improved over time PoU indicator is methodologically sound and makes best use of available data: recent criticisms often miss the point The hunger metrics mirage is based on wrong assumptions and makes impractical proposals Stronger role for Food Security and Nutrition in the 2030 Agenda for Sustainable Development (SDG2 with 5 targets and 3 MoI) UNSC adopted PoU and FIES as official indicators for monitoring target 2.1 For the 1 st time FAO direct data collection to produce a global indicator: FIES estimates now available in 150 countries for 2014 and 2015 Establishment of a global standard to ensure data harmonization & comparability across countries and regions. Long-term vision: FIES included in national HH survey in every country Need to collect food consumption & nutritional data to better understand the consequences of food insecurity and help addressing its causes 20

21. Thank you for your attention We welcome your comments and suggestions www.fao.org/economic/ess/ess-fs/voices/en

22. Discussion points Focusing on adults’ experiences in the FIES is not a limitation – Although some scales also include questions related to children conditions, these are still aimed at capturing the household food insecurity condition Provided additional questions related to children conform to the theoretical requirement of the Rasch model and contribute to measure the unidimensional latent trait, they can be freely added to the questionnaire, without prejudice for the comparability of the measures – Care should be taken in calibrating measures obtained in households with children with those obtained in households without children, as these will be on two different scales – The food security status of small children is determined by the condition of their households or of those who have child rearing responsibility Disaggregation can be obtained by analyzing household with and without small children separately FIES is not based on subjective assessments – People are asked to report on factual experiences, not on subjective perceptions or judgments – Experiences related to the inability to access food are universal FIES does not provide measures of the quality or quantity of actual food consumption or of the nutrition status of people – Collection of food security data along with food consumption and/or nutritional status may help to better understand the consequences of food insecurity in terms of malnutrition and help addressing their causes