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Safety Nets Alert Platform: Methodological note on how to simulate the impact of a shock - May 2018

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Manual and Guideline
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Background

The Middle East, North Africa and Central Asia regions face a extraordinary challenges to food and nutrition security. These regions are exceptionally vulnerable to global food price shocks due to the high dependency on food imports. Socioeconomic shocks can result in a disproportionate burden for the most vulnerable, due to imperfect safety nets. Other countries face these issues too. The International Labour Organization’s (ILO) World Social Protection Report 2017-2019 estimates that 4 billion people worldwide are left without social protection. Most developing countries have also limited capacities to anticipate shocks, assess potential impact and provide targeted support. SNAP fills the need of having in place an agile monitoring system that can enhance early warning, risk management and social protection.

Reduced funds in governments to respond to crisis and poor targeting require better organized and properly analyzed data, which is identified as one of the main challenges WFP, partners and governments face when preparing for or responding to a shock. There is a lot of data that is not properly used for evidence-based planning, especially in emergencies when time and resources are limited.

The WFP’s Safety Nets Alert Platform (SNAP) bridges this gap. It translates data into easy-to-read information for decision-makers to take rapid actions and prepare interventions in support of vulnerable populations, based on best available evidences.

Shocks arise from rapid changes in economic, political, market or climatic conditions, affecting different population groups differently. These shocks can have lasting impacts on livelihoods, food security and development progress. A shock impact simulation can be used for estimating ex-ante, current, and ex-post shock impacts to support intervention decisions, contingency planning and wider policy-making. Thanks to the application of SISMod and its integration into SNAP, WFP aims at achieving the goal of Zero Hunger by 2030 and ensuring food and nutrition security for all at all time. It does so through five main comparative advantages:

  • Better and faster analysis and reports. WFP and government technical staff reduce drastically their time and resources dedicated to analysis and reporting thanks to SNAP. The quality of data and reports is also ensured.

  • Emergency preparedness and contingency planning. By knowing in advance possible risks and measured impact, WFP and governments can better prepare, prevent and respond. Beyond the financial benefit, this will allow to assist the affected population with preventive and efficient safety nets, making sure no lives and livelihoods are at risks.

  • Less assessments and more effective planning. Once a shock happens, humanitarian actors go for assessments. With SNAP, costs and time related to an assessment could be eliminated and substituted with simulations.

  • Vulnerable people are better targeted. SNAP uses categorical targeting, which is considered among the most cost-effective targeting methods in developing countries.

  • Stronger partnership with governments to achieve zero hunger. SNAP supports governments renewed commitment in achieving SDGs and achieve zero hunger. SNAP builds national capacity in the field of data and analysis, and advocates for social policies that can contribute to alleviate poverty and reach food security.

Thanks to SNAP, governments can easily monitor their achievements on SDG2.

Introduction

The Vulnerability Analysis and Mapping (VAM) team of the World Food Programme (WFP) and the Global Information and Early Warning System (GIEWS) team of the Food and Agriculture Organization (FAO) initiated a joint project in 2009 and developed the Shock Impact Simulation Model (SISMod) to assess the food security situation in low-income food deficit countries.

The model used to run shock impact simulations is country specific and it is based on baselines derived from national household surveys or, in specific cases, WFP and partner assessments. SISMod is a macroeconomic modelling system that brings new possibilities to allow timely quantitative assessments on the ex-ante and ex-post impact of various types of shocks (market, economic, sociopolitical, climatic, etc.) on household vulnerability. It identifies and profiles the vulnerable groups, and estimates to what extent they are in need. SISMod can help governments anticipate shocks derived from specific policies or externalities and make sure the most vulnerable are protected with the most adequate safety nets. In shock-affected countries, SISMod provides early estimates of the impacts of shocks before field assessments are carried out, informing the initial development of response scenarios. The shock simulation models are designed ad hoc for each country, based on context-specific data and informing on particular output variables of interest.

SISMod is converted from a statistical software model to an online interactive tool integrated into the Safety Nets Alert Platform (SNAP). As part of SNAP, WFP Regional Bureau in Cairo (RBC) developed SISMod models in target countries in partnership with local actors, including hosting governments.

The foundation of SISMod analysis is a set of modules that take into account household income, expenditure and consumption. The model estimates demand, supply and price transmission elasticities based on household data, national food price collection systems, and integrated with other assessments. The process determines the interaction between production and income-generation decisions (income effects) and consumption decisions (price effects), which quantify the impacts of price changes and income changes on household food consumption.

The methodological approach is to incorporate baseline data and shock factors to model the impact of shocks on the food security and vulnerability situation of the country. Therefore, the analytical work starts with secondary data analysis, collection of background information on the history of the country in terms of price changes of food and non-food items and income changes and a review of the impact of past shocks and their impact. This is then used as a basis for identifying the magnitude of shock impacts to measure their effect on food security and other vulnerability indicators relevant to the country context. The methodology of SISMod can be divided into three steps:

  1. Data preparation, where the analyst prepares income, expenditure, and food consumption modules to be entered in the economic models;
  2. Parameter creation, where the analyst creates elasticities for income, expenditure, and food consumption;
  3. Shocking factors, where the analyst simulates possible impacts of shock factors on the household’s food security situation, particularly in terms of expenditure and food consumption behavioral changes after a shock.

The final outcomes of the analysis are specific estimated indicators of vulnerability relevant to the country context. Among the output indicators used in RBC countries, there are, for instance absolute/extreme poverty, depth of hunger, food assistance needed, food deficient population, food gap, etc.

In SNAP, to overcome data availability limitations, the analysis is carried out using the light version of SISMod. SISMod-Light adopts the Agricultural Household Model (AHM) approach developed by Singh et al. (1986). In this model, household consumption decisions are based on household income, which comprises agricultural profits as well as wages, social provisions and any other source of income. Income generation and the allocation of income to expenditure are based on separable decisions, which maximize income and utility in a two-step process. The AHM incorporates both household production and consumption. It integrates price effects – presumed to be exogenous – and takes the relation between them into account.

SISMod was recognized internally at FAO and WFP and externally by other governmental and non-governmental institutions. During 2016-2017 WFP Regional Bureau in Cairo developed four models for Yemen, Lebanon, Kyrgyz Republic and Egypt. Each of these countries has different background, in terms of food security situation and data available.

SISMod is converted from an econometric model to a user-friendly online platform for easy use at country office level. The SNAP online platform (available for RBC and its oversight countries), allows users to run different impact simulations or scenarios for those countries where the model was built, without using any additional software. The model is expected to be expanded to other shock-prone countries in the region and beyond.