Measuring Household Resilience to Food Insecurity

Transcription

1 ERD Accra, May 2009 Measuring Household Resilience to Food Insecurity An Application to Palestinian Households Luca Alinovi, ESAF Erdgin Mane, ESAF Donato Romano, University of Florence

2 Research questions Vulnerability vs. resilience: related but different concepts Objectives: - clarify the meaning of resilience as applied to food systems - discuss the relationship between vulnerability and resilience - develop a conceptual framework for defining HH resilience to food insecurity - apply the proposed methodology to the 11th Palestinian Public Perception Survey 2007.

3 Outline Concepts - resilience: ecological vs. engineering - HHs as (sub)systems within the broader food system From concepts to measurement - conceptual framework - modeling Empirical application - methodological approaches - estimation - validation Implications - policy implications - management implications

4 The concept of resilience Definition - engineering: ability to return to the steady state - ecological: ability to absorb disturbances before changing state - economic? Economic definition of resilience The ability of the household to keep with a certain level of well-being (e.g. food security) withstanding shocks and stresses, depending on: - the options available to the household to make a living - its ability to handle risks

5 Definition of Food Security Food security exists when all people, at all times, have physical and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life (FAO, 1996 World Food Summit)

6 Households as (sub)systems Decision unit - entry point for food security analysis - relationships with the broader food system System definition (Spedding, 1988) A group of interacting components, operating together for a common purpose, capable of reacting as a whole to external stimuli: it is affected directly by its own outputs and has a specified boundary based on the inclusion of all significant feedback. - complex adaptive systems: HH survival depends less on stability of its individual components than on its ability to maintain its selforganization in face of stress or shocks Resilience

7 Analytical framework vulnerability - output-based: asset-income-wellbeing (Dercon, 2001) - V = f (exposure to risk, resilience) risks faced by the HH option available to the HH ability to handle risks resilience - risk reduction and mitigation (ex-ante actions) - coping strategies (ex-post actions) - short term vs. long term We focus only on resilience

8 Resilience Conceptual Framework T 0 T 1 Stability Social Safety Nets Access to Public Services Assets Income and Food Access Endogenous Shocks Exogenous Shocks Household Response Mechanisms Programme Policy Support Stability Social Safety Nets Access to Public Services Assets Income and Food Access Adaptivity Adaptivity i ( IFA, APS, A, SSN, S AC ) R = f, i i i i i i

9 Resilience Path Diagram R IFA SSN APS A AC S V 1 V V 28 Observed variables Unobserved (latent) variables

10 Methodological Approaches Multi-Stage Approach The measurement of each latent variable is done separately using different multivariate techniques (factor analysis, principal components, optimal scaling etc...) Structural Equation Models (Not treated in this paper) This method estimates the model as a whole and allows for testing procedures on the interactions among components. But, it is less flexible and, computationally, more difficult to estimate. Mostly, based on normality condition. (Polichoric correlations, MIMIC)

11 Data Set Palestinian Public Perception survey (2007) Sample Size: 2087 Content: The Roster (household s demographics, employment and education) Security/Mobility Labour Market Economic Situation (includes the food security module) Assistance/Assistance Priorities Infrastructure Coping Strategies Health/Children/Women Politics/Peace/Managing Security/Religion

12 Empirical Strategy Identification and processing of the variables relevant to each component of the resilience framework Application of multivariate methods (factor analysis, principal components analysis, optimal scaling etc.) to estimate an indicator for each component Application of the Classification and Regression Trees (CART) methodology to build precise decision rules based on the regression tree for a better understanding of the whole process and to easily transfer it to new data sets Link with Vulnerability to Food Insecurity

13 Income and Food Access Average per person daily income (NIS/person/day) Household food insecurity access score (HFIAS) Dietary diversity and food frequency score (DD)

14 Access to Public Services The public services considered in the analysis are the following: Physical Access to Health Service (ordinal, 1 to 3) Quality score of Health Service Quality of Educational System (ordinal, 1 to 6) Perception of Security (ordinal, 1 to 4) Mobility and Transport Constraints (ordinal, 1 to 3) Water, Electricity and Phone networks (count)

15 Social Safety Nets Amount of Cash and In-kind Assistance (continuous, NIS/person/day) Goodness of Assistance (ordinal scale, 4 classes) Job Assistance (dummy, yes/no) Monetary value of 1st and 2nd type of assistance (continuous, NIS/person/day) Evaluation of the main type of assistance (ordinal scale, 4 classes) Frequency of assistance (count, number of assistance received in the last 6 months) Overall opinion on targeting (categorical; assistance targeted to the needy, even to some not needy; and targeted without distinction)

16 Adaptive Capacity The adaptive capacity is measured through the following indicators: Diversity of income sources (count, 0 to 6) Available Coping Strategies (count, 0 to 18) Capacity to keep up in the future (ordinal, 1 to 5) Correlation of AC with transformed variables : Transformed Variable Diversity of Income Sources Coping Strategy Index Capacity to keep up in future AC

17 Stability The variables used for the measurement of stability are the following: Professional Skills (continuous) Educational Level (continuous) Employment Ratio (ratio, from 0 to 1) Number of HH members that have lost their job (count) Income Stability (ordinal; increased, the same, decreased) Assistance Dependency (ratio, from 0 to 1) Assistance Stability (ordinal; increased, the same, decreased) Health Stability (count, 0 to 8) Education System Stability (ordinal; increased, the same, decreased)

18 Estimation of Resilience Index Iterated Principal Factor Method (normally distributed variables) Eigenvalues and σ 2 explained Factor Loadings Eigenvalue % Variance Factor 1 Factor 2 Factor 3 Factor IFA Factor AC Factor S Factor APS Factor SSN Resilience = 0.71*Factor *Factor *Factor3

19 Discussion of Results The Kernel Distribution of Resilience in the 5 Palestinian sub-regions. Kernel Density Estimation of Resilience Density Resilience Index kernel = epanechnikov, bandwidth =.13 North West Bank Middle West Bank East Jerusalem South West Bank Gaza Strip

20 Parametric Estimates Mean and standard deviation of resilience and its components Freq Resilience IFA APS SSN AC S Regions N Mean S.D. Mean S.D. Mean S.D. Mean S.D. Mean S.D. Mean S.D. North WB Middle WB Jerusalem South WB Gaza Strip Total The Matrix of t-statistics for the Comparison between Means North WB Middle WB Jerusalem South WB Gaza Strip North WB 0 Middle WB Jerusalem South WB * Gaza Strip * 0 * Not significant at 95%, but significant at 90%

21 ...discussing results Components of Resilience IFA SSN -1-2 APS AC S North WB Middle WB Jerusalem South WB Gaza Strip

22 The components in the 5 macro-regions North WB R = Middle WB R = East Jerusalem R = IFA IFA IFA SSN -0.5 APS SSN -0.5 APS SSN -0.5 APS AC S AC S AC S South WB R = IFA Gaza Strip R = IFA SSN -0.5 APS SSN -0.5 APS AC S AC S

23 Process Validation with CART The Upper part of the Regression Tree (281 terminal nodes) Predictors = 28 Approximated R-squared = 1 - resubstitution error = = 0.981

24 Variable Importance Code Description Import. Code Description Import. IFA1 Income 100 SSN4 Monet. value of 1 st and 2 nd type IFA3 HFIAS APS3 Educational System IFA2 Dietary Diversity SSN2 Goodness of assistance AC2 Coping Strategies S6 Assistance Dependency AC3 Capacity to keep up in future S9 Educational System Stability S3E Employment Ratio APS4 Perception of Security S2 Educational level S7 Assistance Stability SSN5 Evaluation Main Assistance APS1 Physical access to health S1W Professional Skills SSN6 Frequency of assistance APS2 Health Service quality APS5 Mobility Constraints AC1 Diversity of Income Sources S5 Income Stability SSN1 Cash and In kind assistance SSN7 Opinion on targeting S8 Health Stability S4 # HH members have lost work APS7 Water, electricity & phone SSN3 Employment Assistance 0.070

25 Forecasting resilience R = α + β IFA + β IFA2 + β IFA3 + β AC2 + β AC3+ β S3+ β 2 + ε S OLS estimates: Resilience Income Dietary Diversity HFIAS Coping Strategies Capacity to keep up in the future (expectation) Employment ratio Educational level Constant Coefficients (0.000)* (0.000)* (0.000)* (0.000)* (0.000)* (0.000)* (0.000)* (0.000)* Observations R-squared Breusch-Pagan Test for Heteroskedasticity (p-value) * p-value: significant at 1%

26 Role of resilience on vulnerability to food security LogToTFC = α + β1r + β 2HSize + β 3MWB + β 4 J1+ β 5SWB + β 6GS + β 6Gender + ε OLS estimates: Log Total food consumption (MV) Resilience Household Size Middle West Bank (dummy) East Jerusalem (dummy) South West Bank (dummy) Gaza Strip (dummy) Gender Household Head (dummy; female=1) Constant Coefficients (0.000)** (0.000)** (0.001)** (0.000)** (0.199) (0.000)** (0.037)* (0.000)** Observations R-squared Breusch-Pagan Test for Heteroskedasticity (p-value) Robust p-values in parentheses: * significant at 5%; ** significant at 1%

27 Policy implications How policies should be designed? - adaptively monitor key variables - provide and sustain diversity (ecological, economic, cultural) - provide and sustain natural, social and cultural capital - seek integrative (system-wide) understanding From policies that aspire to control change in a system assumed as stable to managing the capacity of socio-economic system to cope with, adapt and shape change

28 Twin Track Approach

29 Linking Information to Action A workshop was organized by MAS-Palestine Economic Policy Research Institute in Ramallah with MoSA, PCBS, WFP and local experts. Main feedbacks: - model capacity to provide a systemic vision of the socio-economic situation in Palestine - reliability of results and faithful representation of the reality - the tool has direct implications for policy makers The resilience framework has been embedded by the Social Protection Working Group for West Bank & Gaza Strip

30 Kenya Integrated Household Budget Survey Survey (13,430 hhs) in 4 questionnaires : 1,343 randomly selected clusters (861 rural and 482 urban) 10 hhs/cluster (1) A 21 module household questionnaire; (2) 14-day household expenditure diaries to record consumption and purchases; (3) A market price questionnaire and, (4) A community questionnaire.

31 Urban/Rural Resilience Kernel Density Density Resilience Index kernel = epanechnikov, bandwidth = Resilience Urban Resilience Rural

32 Kenya Key Provinces Density Resilience in Kenyan Provinces Resilience Index kernel = epanechnikov, bandwidth = Resilience Nairobi Resilience Central Resilience Coast Resilience North Eastern Resilience Western

33 Components of Resilience (Nairobi included) Components of Resilience IFA S 1.00 A Kenya 0.00 Nairobi Central Coast Eastern AC APS Western SSN

34 Components of Resilience (Nairobi excluded) Components of Resilience IFA S A Kenya Central Coast Eastern Western AC APS SSN

35 Central S IFA A AC APS SSN Central

36 Western S IFA A AC APS SSN Western

37 Unsolved Questions & Next Steps Model validity in African countries needs to be tested Application to Kenya Integrated Household Budget Survey 2005/06 Ex-Post validation using longitudinal data should be conducted Application to Nicaragua 1998 & 2001 Household Panel Data The effects of shocks and policies on household resilience should be investigated better Analysis of the effects of Mitch and relief interventions in Nicaragua using treatment evaluation methods More information on risk sharing mechanisms and social safety nets is needed for a better understanding of the household system Technical support to countries on the design of survey instruments

38 Conclusions The analysis of household resilience monitoring each component has direct policy implications The analysis of resilience in time and the comparison across countries requires further work The use of Structural Equation Models may improve the estimates and will allow for more rigorous testing procedures