Data Collection Methods for Statistics on Structural Aspects of Agriculture in Zambia
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This document describes data collection methods for agricultural statistics in Zambia. It discusses several surveys conducted in Zambia to collect structural data on agriculture, with a focus on the Post-Harvest Survey (PHS). The PHS uses a two-stage cluster sample to survey 13,600 agricultural households. Enumerators first list and categorize households in selected areas, then systematically sample 20 households per area for surveys. The methodology also includes preparatory activities like questionnaire revision, training, and pretesting before data collection and cleaning. The final reports are generated based on analytical tables and disseminated.
![Preparatory Activities (ctd)
Programming (for trapping some
inconsistencies, extreme values,
etc).[Minimal]
Pretesting qnr and Survey Solutions
programme.
10](https://image.slidesharecdn.com/ts19dzambiapresentation-171114162715/85/Data-Collection-Methods-for-Statistics-on-Structural-Aspects-of-Agriculture-in-Zambia-10-320.jpg)
![Data Cleaning
More rigorous data cleaning syntax
developed in SPSS.
More thorough data cleaning, by running
the SPSS syntax developed
Weights generated
Preliminary tabulations [tables help with
cleaning the data].
12](https://image.slidesharecdn.com/ts19dzambiapresentation-171114162715/85/Data-Collection-Methods-for-Statistics-on-Structural-Aspects-of-Agriculture-in-Zambia-12-320.jpg)
Data Collection Methods for Statistics on Structural Aspects of Agriculture in Zambia
- 1. Regional Roundtable on World Programme for the Census of Agriculture 2020 Nairobi, Kenya, 18-22 September 2017 Data Collection Methods for Statistics on Structural Aspects of Agriculture in Zambia Technical Session 19 1 Name of presenter and/or contact person Title: Mr. Daniel Daka Name of agency: Central Statistical Office (Zambia) E-mail address : mudaala@gmail.com
- 2. Contents Background Methodology Preparatory Activities Data Cleaning Report Writing Sample output 2
- 3. Background In Zambia, data on structural aspects of agriculture is collected through a number of surveys. Key among these are: (i) The Post Harvest Survey (by Central Statistical Office) 3
- 4. Background (ctd) (ii) Rural Agricultural Livelihoods Survey (Indaba Agricultural Policy Research Institute, and CSO) (iii) Living Conditions Monitoring Survey (CSO) 4
- 5. •Methodology The methodology described below applies to the PHS, since it is the main source of structural agricultural data. The Post-Harvest Survey is a large sample survey of 13,600 agricultural households (hholds). It is a stratified two-stage cluster sample. 5
- 6. Methodology (ctd) The fist stage consists of selecting Enumeration Areas to be covered in the survey. Enumeration Areas are selected from the Frame of Agricultural Households (PPS) Measure of Size is No. Of Agric hholds in EA. Frame created from 2010 Census of Population data 6
- 7. Methodology(ctd) At data collection stage, enumerators first list all hholds in a selected EA. Each of the agric hholds in an EA is put in a category using several criteria, such as: (a) total size of the area under crops (b) whether the hhold raises parent stock of chickens 7
- 8. Methodology (ctd) After listing, 20 hholds in each EA are selected using Linear Systematic Sampling. PHS questionnaire administered to the 20 selected hholds 8
- 9. Preparatory Activities (ctd) Questionnaire revised, where necessary. This stage is also training of Master Trainers. Enumerator Manual Also prepared at this stage. Rendering of questionnaire into electronic format, using the software Survey Solutions (CAPI). 9
- 10. Preparatory Activities (ctd) Programming (for trapping some inconsistencies, extreme values, etc).[Minimal] Pretesting qnr and Survey Solutions programme. 10
- 11. Preparatory Activities (ctd) Enumerator Training and Field Work Data Collection Phase Supervisors and Master Trainers do preliminary quality checks in field Each day, enumerators submit to CAPI Supervisors completed qnrs for further quality checks. 11
- 12. Data Cleaning More rigorous data cleaning syntax developed in SPSS. More thorough data cleaning, by running the SPSS syntax developed Weights generated Preliminary tabulations [tables help with cleaning the data]. 12
- 13. Report Writing With clean datasets in place, analytical tables are generated, based on dummy tables prepared before hand The PHS report is written. Staff share chapters to write. Editing of the PHS report Printing of final report. Dissemination of report (hard copies) Soft copies are disseminated via CDs, Flash discs, on website, via data portal. 13
- 14. Sample Outputs 71% 23% 6% Percentage Distribution of Agricultural Households by Total Area Under Crops Area<=2Ha 2Ha<Area=<5Ha Area>5Ha 14
- 15. Thank You 1
Editor's Notes
- #4: The collection of agricultural statistics is provided for in the constitution. No specific mention of Census of Agriculture, but one has been held under the present legislation.
- #5: The Post-Harvest Survey (PHS) is (supposed to be) conducted annually. LCMS is of periodicity 2 years (cross sectional) and 5 years (longitudinal). RALS is supposed to be done every third year. RALS covers only Small and Medium Scale farms, while PHS and LCMS also cover the non-household sectors (Large-Scale farms).
- #6: There are approx. 1,500,000 agric hholds in Zambia.
- #7: Screening qns in Census are: Does any household (hhold) member grow any of (list of crops)? Does any hhold member keep (list of animals)?. EAs in which 30 percent or more of hholds responded in the affirmative to any of these qns considered agric EAs, and constitute frame.
- #8: Large-Scale farms are covered on a 100 percent basis. There are about 2000 such farms.
- #9: About 500 persons involved in data collection an supervision. The bulk of these are regular CSO /Government employees.
- #10: Questionnaires (qnrs) revised to take into consideration current user demands, where necessary.
- #11: The programming at this stage is minimal, to avoid overloading (and thus slowing) the programme.