LINKING HOUSEHOLD METHODS IN CAMBODIA

Transcription

1 LINKING HOUSEHOLD LEVEL DATA COLLECTION METHODS IN CAMBODIA Presented at the: 9 th Poverty and Economic Policy (PEP) Research Network Policy Conference and General Meeting Siem reap, Cambodia 6 December 2111 Sherif Rushdy, CMDG Advisor, UNDP Cambodia

2 Contents Recent Developments in the Commune Database The Household Form Other household data collection processes A proposal for integration

3 Commune Data Base (CDB) 3 Operating with annual data collection since 2002 Major development in 2006 Major revision in 2011 Village Data Book: 229 questions data points Commune Data Book: 109 questions data points New District Data Book: 49 questions data points New Province Data Book: under consideration

4 Types of data 4 Village Commune District Population by age group Ethnic Minorities School attendance and literacy Occupations Businesses with employment Agricultural and other machinery Transportation equipment Livestock raising i Health Housing, water and sanitation Vulnerable Groups Administration and Security Land Use Government Officials Business support institutions Agriculture yields and production (rice, short term crops, long term crops) Roads Educational institution details Environment and Disasters Administration and Security Government Officials Higher education Vocational education District Revenue Health Services NGOs All gender disaggregated

5 Main Purposes of CDB 5 Support to Sub-national planning processes (through annual commune, district and provincial profiles) Allocation of resources to communes (based on a proxy indicator of poverty) Recently: Poverty estimator and CMDG Scorecards BAT MDG 6 MDG MDG MDG2 MDG 3 MDG MDG 4

6 New Products 6 Economic, Social and Environmental Scorecards Climate vulnerability maps Social Vulnerability maps Refined CMDG scorecards Revised Commune, District and Provincial Profiles Etc

7 Strengths and Weaknesses of CDB 7 Strengths Weaknesses nationwide coverage: 14,000 villages comprehensiveness of data collected annual updating automated system for aggregation full integration into the operation of MoP automated generation of profiles and MDG scorecards Mltil Multiples products consistent operation since 2002 national ownership very low cost: $120,000 ($10/vill - $0.05/HH) cannot provide household level poverty data or targeting does not collect income information (definition of poverty is asset based) not comparable abe with national a estimates reliance on village chiefs, leading to questioning of data validity lacks integration in the NIS framework (legality and technical oversight, integrations ti with data classification schemes CMDG indicators are mostly proxies that do not match national indicators

8 Systematizing data collection 8 1. Family 2. Business 3. Events 4. Village Data Book Data Book Data Book Information Tally Sheets Tally Sheets Tally Sheets Tally Sheets Village Data Book

9 9 Family Data Book (Part 1- individuals) No. Name Date of Birth Year School Primary Occupati on Secondar y Occupati on Choose from: Farming, Fishing, Animal Raising, NTFP, Handicraft, Handic ap Mine/ER W Remark AIDS Head of Household Lower Second. Higher Second. Receive HIV Drugs Business, Repairs, Transportation, Orphan <18 Gender Age Pre-Primary Primary University Vocational Illiterate HIV Can Work Cannot Work Victim Receive Rehab Receive S\E Orphan< Government Employee, Private Sector Employee

10 10 Family Data Book (Part 2- household) TYPE OF FARMING AGRICULTURE EQUIPMENT ENVIRONMENT Rice Farming Tractor for ploughing Affected by heavy drought Chamkar Rice Farming Koyon Affected by heavy flood Long Term Crops Rice transplanting machine Affected by heavy storm Short Term Crops Rice harvest and threshing machine Affected by severe fire Vegetable Growing Rice harvesting machine Living in protected area TYPE OF LAND Corn/bean planting machine Have waste collection Farm Land<1Ha Cassava planting machine Affected by pollution No Farm Land Corn threshing machine Using Chemical fertilizer Rice Land Irrigated Rice husk moveable machine Using chemical pesticide Use Irrigation Well OTHER MACHINERY OTHER HOUSING For construction work Domestic violence Leaf, Thatch roof VEHICLES Use of Drugs Zinc or Fibro roof Local made car < 20 sheets Small truck Tiled roof Heavy truck Cement wall no concrete roof Mini Bus (<12 seats) Flat/apartment Bus (>12 seats) Villa Family car Electricity Network OTHER TRANSPORTATION Other Source of Electricity Motorbike TV Motorbike trailer Own Improved Toilet Motor Tricycle Own Non-Improved Toilet Useable Bicycle SOURCE OF WATER Row boat for fishing Purified water system Row boat for travel/tourism Pump, mixed well Motorboat for fishing Protected Dug Well Motorboat for travel/tourism Unprotected Dug Well Motorboat for Transport <1Ton Water Pond Motorboat for Transport >1Ton Rainwater Storage LIVESTOCK Protected Rainwater Storage Cattle/Buffalo Other source Cattle/Buffalo l/ ffl as drought animals Water less than 150 m Goats Water more than 150 m Pigs (> 3 months) WATER HYGIENE Chicken (>0.8 kg) Filter Water Ducks (>1.4 kg) Chlorinate Water Crocodiles Use Solar Light Fish pond (fish culture) Boil Water Lobster Pond (lobster culture)

11 Other household data collection 11 Census Cambodia Socio- Economic Survey ID-Poor CBMS MoI Family Book ISSUES Largely Similar data Duplication of efforts Duplication of costs Proliferation of tools Confusion Departmental competition Donor fragmentation /lack of harmonization i

12 Strengths and Weaknesses of CBMS 12 Strengths Weaknesses systematization of the household questionnaire e mapping at the village level training and supervision of enumerators standard data verification procedures, indicators with the same definitions as the NIS income information conducted by NIS Can target households for service delivery possible household level research Experience with utilisation of data connection to PEP - transfer of skills and experiences. difficult to scale up Costly by-passes the village chief who is a mine of information not integrated into the normal planning process duplicates much of what is already collected by the CDB

13 Strengths and Weaknesses of ID-Poor 13 Strengths Weaknesses agreed upon definition of poor households o systematization of the household questionnaire Includes events related to poverty training and supervision of enumerators community dialogue for validation results in a clear list of target households costs, difficulty of scaling it up subject to manipulation and local pressure for inclusion of non-poor household (immediate benefit) narrow focus on the identification of poor (opportunity lost for other uses) duplicates some of what is already collected by the CDB Not updated?

14 Proposed Concept 14 One well-organized, well-supervised, well-funded annual data collection system with: common enhanced household questionnaire, mapping procedures derived from CBMS, data collection a trained village data committee including village chief, validation at the community level, supervision from the commune, district and provincial levels technical input from NIS. Combined computing capacity of ID-poor, CDB, CBMS

15 Advantages 15 meet the needs of all users fraction of the total budget now allocated build on strengths and avoid shortcomings increase data quality household poverty and social protection targeting national ownership and sustainable operation credible national level indicators annually for policy formulation Link from data to decision-making support by a credible international network example of donor harmonization and effectiveness

16 Road ahead 16 Compare approaches in detail (questionnaires, processes, resources, budgets, responsibilities) Attempt to formulate a common household tool Engage donors in dialogue Engage MoP(NIS & GDP), MOI, NCDD in dialogue Discuss within TWG-PPR Implement a joint programme within MoP