1. ISI Satellite Conference on Agricultural Statistics, Maputo, 13-14 August 2009 Integrated survey framework Using Household Expenditure Surveys for Food Security Assessment

2. 1.Integrated data collection programme of a NSS a.Designation of responsibilities b.Efficient use of different data sources (no duplication, no data gaps, linkages between sources) 2.Integrated survey framework as a component of the Integrated data collection programme a.Comprehensive suite of surveys b.Multipurpose surveys 3.National level (NSDS, Statistical Master Plan) 4.International level a.IHSN: integration of internationally sponsored surveys Integrated data collection and survey framework

3. 1.Methodological integration = increased data comparability across surveys 1.Minimum = common definitions and classifications, same statistical units 2.Greater level of integration: master sample, survey design, questionnaire formulation, data processing 2.Thematic integration => linking data domains a.Separate surveys => statistical matching of different but similar units across surveys b.Multipurpose surveys: inclusion of additional modules in the core questionnaire (same units are surveyed) Methodological & Thematic Integration

4. 1.Collection of agricultural production statistics at the household level (Focus on rural development, diversification of sources of income) 2.The problem: sub-sample of farming households is not likely to properly represent agriculture as an industry: bias towards small production units 3.Use of different surveys with different frames for obtaining a complete picture of agriculture as an industry 1.Area frame of households-based farms 2.Business register of commercial farms Methodological Integration: Multiple frames

5. PROS 1.Methodological and thematic integration: Source of multiple, policy-relevant measures 2.Identification of target groups (demographic characteristics) 3.Causal analysis and policy evaluation (panel) 4.Direct measurement of target variables 5.Cost savings CONS 1.Same design for different objective => Inefficient sampling, under coverage and sampling bias 2.Same data collection arrangements for different variables => Measurement errors: non uniform data quality 3.Very large questionnaire: considerable response burden 1.across surveys Thematic Integration: Multipurpose surveys

6. 1.Case by case choice 2.Many factors have to be taken into account: 1.Level of development of the statistical system 2.Compatibility of survey designs 3.Compatibility of data collection arrangements 1.across surveys Using Multipurpose surveys: when?

7. MAIN OBJECTIVES OF HIES/LSMS 1.Measurement of consumption expenditure 2.Measurement of the distribution of living standards, poverty and inequality 3.Estimation of weights for the compilation of the Consumer Price index 4.Provision of estimates for National Accounts MAIN OBJECTIVE OF FOOD SECURITY MODULE 1.Measurement of Undernourishment, Intensity of food inadequacy, Diet composition 2.MDG Indicator 1.9: Halve the proportion of hungry people by 2015 (population below minimum level of dietary energy consumption)  =>Joint POVERTY and FOOD SECURITY assessment Example of thematic integration: inclusion of a food security module in the HIES/LSMS

8. 1.HIES/LSMS survey expenditures on all goods and services that contribute to people's standard of living 2.In most HIES/LSMS only expenditure is surveyed, not physical quantity. Even when surveyed, it is not processed 3.Food security module: collection of data on food acquisition, both in physical quantity and monetary values 1.Acquisition includes: (1) food purchases; (2) gifts or in-kind payment for work; (3) home production 2.Specification of food items not commodity groups 3.Standardization of the unit of measurement 4.Standard conversion tables are then used to convert quantities into a count of the number of calories contained in the food purchased household food energy deficiency Food security module in the HIES/LSMS

9. 1.Sufficient coverage of rural areas and specific population groupings 2.Problem of periodicity of expenditures on different food items: reporting period should be in line with buying cycle/income period of each country (fortnight/monthly) 3.Data collection spread over a twelve month basis for seasonality assessment and usual consumption concept 4.Food data collected in household expenditure surveys reflect the quantity of food "acquired" by a household rather than that "consumed" by its members Methodological issues

11.  HIES/LSMS can become a major sources of information for deriving food security statistics that can help in taking informed policies on food security and food vulnerability  FAO Statistics is available to collaborate with national and international partners to include a FOOD SECURITY MODULE in HIES/LSMS for deriving food security indicators at national and sub national levels  NSOs should be trained to process and analyze food security statistics and indicators, jointly with users, for the purpose of assessing and monitoring food insecurity at national and sub- national levels CONCLUSIONS

12. THANK YOU OBRIGADO