Context Integrating Population and Housing Censuses with Agricultural Censuses

1. ContextIntegrating Population and Housing Censuses with Agricultural Censuses

2. Outline • International recommendations on linked censuses. • Why have an integrated census programme. • Modalities of linking censuses and the Integrated Statistical System

3. Current Recommendations • UNSD Principles and Recommendations for Population and Housing Censuses, Rev 2 2007 • UNECE Conference of European Statistician Recommendations for the 2010 Censuses of Population and Housing 2006 • FAO Recommendations World Census of Agriculture 2010 • UNECA 2010 Africa Round of Population and Housing Censuses 2008 • Important to understand the change in emphasis between the current round of censuses and previous rounds. • Previous rounds did not encourage joint activities for 2 main reasons – different enumeration units (household and holding) and overloading questionnaire

4. FAO recommendations • Use of common concepts, definitions and classifications • Collecting a greater level of agricultural data in the population and housing census • Sharing field materials • Using the data for a frame for agricultural censuses and surveys • Linking data from separately conducted population and housing censuses and agricultural censuses • Conducting the two censuses as a joint field operation

5. UNSD Recommendations • Collecting additional agricultural information in the population census (non-core items) • For preparation of frame of agricultural holdings (family farm) for the agricultural census • Data collected during pre census listing or additional items in population census questionnaire • Self-employed agricultural production • Censuses carried out close together • Use of demographic data from population census reduces size of agriculture census questionnaire • Joint field operation with separate questionnaires also possible

6. UNECE Recommendations • Most relevant for countries with the bulk of agricultural activities in the household sector • Use of common definitions • Shared materials: common EAs, preparation of sample frame and sample design • Collecting agricultural information as part of the population census questionnaire (non-core items) • Combined field operations with separate questionnaires • One time collection of demographic and activity status information

7. UNECA Recommendations • Shared equipment and personnel • Shared equipment – maps and field personnel • Including agriculture questions in the population census • Using data from population census in the frame for the agricultural census

8. Why have an integrated census programme? Current agricultural data in population census • Some agriculture data routinely collected but not sufficient • Items collected as part of population census • Main occupation, industry of main occupation and employment status in main occupation • Not broad enough in scope • no auxiliary information for sample design • Many countries don’t follow ILO standard classification • Difficult to identify agriculture households • Example of regional classification • Underestimates number of farm households • usually based on short reference period which does not capture seasonality • Criteria for main job may exclude households with several activities, e.g. fishing • Existing data insufficient: need for specific consideration of agriculture data and inclusion of limited number of items

9. Why have an integrated census programme? • Advantages for the National Statistics System • Reducing the total cost of the two censuses • Enriching data analysis • Ensuring regular agricultural census operations • Building a reliable sample frame and optimizing the sample design for the agricultural census • Better defining the agricultural census coverage – identifying non-agricultural households and minor agricultural households.

10. Why have an integrated census progarmme? • Broader scope for agriculture statistics • Cost effectiveness • More efficient sample design and better quality sample frame

11. Broader Scope for Agriculture: Integrated Statistical System • Traditionally focused on the structure of agriculture and agricultural production. • Support to national accounts • Provide data on SNA economic production units: enterprises and establishments • ISIC classification of agriculture • Under Global Strategy recognition of new data demands: structure, production, farm management, food security, household income and expenditure, labour force and prices

12. Broader Scope for Agriculture: Emerging needs for integrated data Food Security • Can we feed our citizens? • Impact on farmers and agricultural households of the food price spikes? Poverty Reduction • How to improve household income from sales of crops and livestock? • What is the relationship between increased productivity of smallholder farmers and economic growth? • How does small holder farming, animal husbandry, employment in new high value agriculture and rural non farm economy lead to poverty reduction? Gender • Which agricultural activities involve women? • What is their economic contribution?

13. Broader Scope for Agriculture: Global Strategy • Global Strategy extends to economic, social and environmental dimensions • Economic: Agricultural production, markets, farm and nonfarm income and survey data • Social: Reducing risk and vulnerability, food security, gender • Environmental sustainability, climate change adaptation, biofuels, land cover and land use

14. Broader Scope for Agriculture: WCA 2010 • Modular Approach: Core and Supplementary modules • WCA 2010 flexible – core data and inclusion of themes relevant to countries • Integration with population and housing census is part of this new approach • Enables integration with the national statistical system • Flexibility to include broader range of data • Enables inclusion of minimal producers

15. The agricultural census in the framework of an integrated system of censuses and surveys

16. Broader Scope for Agriculture: WCA 2010 (2) • Core data should cover: • Key items for agricultural policy making and planning • Data for items needed at small administrative units: districts or villages • Rare events: unusual crops or livestock • Data needed to create sampling frames • Data needed to make international comparisons

17. Efficiency and Quality: Sample Design and Sample Frame • Up to date listing for the sample frame – more reliable data • Additional information to optimize the sample design • e.g. Types of crops, farm size for stratification • Better defined agricultural census coverage • Complete listing of agricultural households: no cut-offs • Preliminary information identifies need for specialized surveys e.g. bee keeping

18. Tools and methodology for integration

19. Linkage – reducing the total cost of the two censuses • 50 % reduction in some countries • Coordinated approach rather than two separate collections reduces costs • Shared infrastructure, logistics, personnel and equipment can be used for both censuses • Particularly census cartography • Smaller agricultural census possible by including basic agricultural questions in population and housing census • Common master sample frame • Reduces costs of separate listing to produce frame

20. Cost Effectiveness • Context of an integrated statistical system • Common sample frame • Integrated surveys Integration of agriculture into national statistics system (NSS) Methodology to Integrate Agriculture Master Sampling Frame Integrated Data Base Integrated Survey Framework

21. Modalities for Linking Additional Items Joint Agriculture and Population Censuses • Choice of modality is part of the programme of data collection in country • Must be seen in the context of an integrated statistical system Full Agricultural Module

22. Context of the Integrated Statistical System • Integrated censuses are part of an integrated statistical system • Based on a master sample frame with common samples • Advantages of integration • Avoids duplication of effort • Prevents release of conflicting statistics • More efficient use of resources

23. Integrated Statistical SystemWhat does it look like? • Coordinated data collection • Timely, accurate, coherent and comparable data • Requires coordination among sectoral producers and NSO • Elements include: • Common concepts, definitions and classification • Coherent results among producers removes duplication of effort • Integrated database – data integrated across various surveys allows cross – tabulations and in depth analysis

24. Tools for Development of the Integrated Statistical System – NSDS Issues • Paris21 Review - 10% of International Development Association (IDA) countrieshad included agriculture more-or-less appropriately in the NSDS process (1999) • NSDS coverage of agriculture is generally poor - including vital areas such as food security • In many countries the first generation NSDS was NSO-centric • Agriculture activities often part of informal economy • Not well covered by statistics reporting systems

25. Tools for Development of the Integrated Statistical System NSDS Advantages of Mainstreaming Mainstreaming agriculture into NSDS address issues of: • Statistical legislation not always covering the whole statistical system • Lack of coordination between NSOs and MoAs or deficient intra-sector coordination • Low profile of statisticians in agriculture ministries • Disorganized statistical functions

26. Tools for Development of the Integrated Statistical System NSDS • Paris21 – capacitydevelopmentfor National Strategy for Development of Statistics • NSDS develops a framework for a common programme and integration of agriculture into the NSS • Overall vision for development of NSS • Based on identified statistical needs of policy users. E.g. development of indicatorsneeded to monitor progress of policy implementation • Institutional development – appropriate legal framework • Organisational development including coordinating unit • Human Resource Development – skilled staff • Infrastructure Development • Includes statistical work programme and planned data collections • Mobilization of resources within country and externally • Advocacy for use of statistics in policy making