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“A new Approach to Improving Sample Design for Crop Forecast and Post – Harvest Estimates in Zambia” A Contributed Paper Session Presented at the International Conference on Agricultural Statistics (ICAS III), Westin Regina Hotel, Cancun, Q.R. Mexico 2nd-4th November 2004 By John Kalumbi

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“A new Approach to Improving Sample Design for Crop Forecast and Post – Harvest Estimates in Zambia”

A Contributed Paper Session Presented at the International Conference on Agricultural Statistics (ICAS III), Westin Regina Hotel, Cancun, Q.R. Mexico

2nd-4th November 2004

By

John Kalumbi

Deputy Director – Agriculture & Environment Division

Central Statistical Office (CSO)

Lusaka, Zambia


I introduction and institutional arrangement
I. INTRODUCTION AND INSTITUTIONAL ARRANGEMENT Forecast and Post – Harvest Estimates in Zambia”

Production of Agricultural Statistics

  • Responsibility of the CSO (Agric. & Environment Division)

  • Collection of data is done in conjunction with the Ministry of Agriculture and Cooperatives (MACO) through the Early Warning and Data Base Management Unit.

    Agriculture & Environment Division

  • Agriculture Branch

    • Small & Medium Scale Farm Section

    • Large Scale Farm Section


    • Environment Branch Forecast and Post – Harvest Estimates in Zambia”

      • Land degradation

      • Air pollution

      • Water Sanitation

      • Forestry

      • Wildlife

      • Fisheries

        Evolution of Agricultural Surveys in Zambia

    • The 1970/71 Census of Agriculture marked the beginning of annual agricultural surveys in Zambia.

      • Crop Forecast Survey (CFS)

      • Post Harvest Survey (PHS)

      • Area Measurement and Crop-Cutting Survey (AMCC) – has since been discontinued


    Ii methodology used
    II. METHODOLOGY USED Forecast and Post – Harvest Estimates in Zambia”

    • Survey sampling for both CFS and PHS for Small & Medium Scale agricultural holdings

    • Complete enumeration for Large-Scale Agric. Holdings

      Sample Design

    • Cartographic census field operation defines Census Supervisory Areas (CSAs), which are further subdivided into Standard Enumeration Areas (SEAs)

    • An SEA is the unit of data collection point at district level


    Previous cfs phs sample design
    Previous CFS/PHS Sample Design Forecast and Post – Harvest Estimates in Zambia”

    • Based on 1990 census data

    • Only rural districts were covered

    • A stratified three stage sample design was used

      • CSAs Primary Sampling Units (PSUs) selected at first stage with PPS

      • SEAs selected at second stage, with one SEA selected with PPS within each sample CSA

      • Measure of size in both cases is number households as listed in the 1990 census of population and Housing.

      • A total sample of 405 SEAs was drawn out of 9,000 rural SEAs

      • No provision of replacement of both sample SEAs and sample households.

      • Sample households were selected at third stage from the listing stratified by farm size category using Linear Systematic Sampling (LSS) procedure with random start.


    New cfs phs sample design
    New CFS/PHS Sample Design Forecast and Post – Harvest Estimates in Zambia”

    • Based on 2000 census data

    • A stratified two-stage sample design is now being used

      • SEAs are the Primary Sampling Units (PSUs) selected at first stage with PPS

      • Measure of size is number of agricultural households as listed in the 2000 census of population and housing

      • A total sample of 410 SEAs were drawn out of the 12,788 agricultural SEAs as defined for the 2000 Zambia Census

      • Sample households are selected at the second stage from the listing stratified by farm size category (land area, number of animals, special crops criteria)


    Other features of new cfs phs sample design
    Other Features of New CFS /PHS Sample Design Forecast and Post – Harvest Estimates in Zambia”

    • Includes a small fraction (5%) of urban SEAs, i.e, urban SEAs in which 70 percent or more households are agricultural according to the 2000 Zambia census data (about 586 urban SEAs in total)

    • Has provision for the replacement of any sample SEAs that may not be enumerated for one reason or another in order to maintain the effective sample size.

    • Eight (8) crops were identified to receive special treatment at second sampling stage in order to improve the precision of survey estimates of crop area and production (i.e., these are crops with limited geographical concentration whose CVs previously were relatively high due to the smaller number of observations – sorghum, rice, cotton, burley tobacco, Virginia tobacco, sunflower, soybeans, and paprika)


    Iii stratification of households
    III. Forecast and Post – Harvest Estimates in Zambia”STRATIFICATION OF HOUSEHOLDS

    Previous sample design

    • Included households listed in sample SEAs by two farm size categories:

      • Category A: 0 – 4.99 hectares

      • Category B: 5.0 – 19.99 hectares

        New sample design

    • Stratification of households listed in sample SEAs is based on

      • Farm size (land area) category

      • Number of livestock or poultry raised criteria

      • Growing of special crops criteria


    Stratification of households by farm size land area
    Stratification of households by farm size (land area) Forecast and Post – Harvest Estimates in Zambia”

    • Category A: 0 – 1.99 hectares

    • Category B: 2.00 – 4.99 hectares

    • Category C: 5.00 – 19.99 hectares

      In both the previous and new sample design, households with farm size category of 20 or more hectares were/are included in the special frame for large-scale farmers and are enumerated separately.


    Stratification of households by number of livestock or poultry raised criteria
    Stratification of households by number of livestock or poultry raised criteria

    • Based on the number of livestock or poultry raised, households are added to category C if the following minimum number are being raised:

      • Cattle – 50

      • Pigs – 20

      • Goats – 30

      • Poultry – 50


    Stratification of households by growing of special crops criteria
    Stratification of households by growing of special crops criteria

    • Households may be added to category B and C based on the special crops treatment criteria

      • If the sample SEA only has 1 or 2 households with any of these special crops, these households will be asigned to category C ( in case they do not qualify based on land area and animals)

      • If the sample SEA has only 3 to 5 households with any of these special crops, such households are assigned to category B (if they were previously assigned to category A based on land area and livestock)


    Iv sample households selection in sample seas
    IV. SAMPLE HOUSEHOLDS SELECTION IN SAMPLE SEAs criteria

    • Total sample size for each SEA – 20 households

    • Distribution of sample households to each category:

      • Category C – 10

      • Category B – 5

      • Category A – 5

    • If there are shortfall in category C, the difference from 20 will be allocated equally to categories B and A or category B will have one more sample households than category A, if the difference cannot be allocated equally.

    • Where there is no household in category C and less than 10 in category B, the difference from twenty will be met from category A.

    • If all listed households fall in category A, then all 20 sample households will come from category A.

      • For each category in the sample SEA, selection of sample households is done using Linear Systematic Sampling (LSS) Procedure with random start.


    V estimation
    V. ESTIMATION criteria

    Estimating for the total involves the weighing of variables before additions are made at district, provincial and national levels. The basic sampling weight is obtained as inverse of the probabilities of selecting the SEAs and households by category size.

    The formula for estimating the survey estimates of a total is as follows:

    ^

    Y =  Wshi Yshij

    h i s j

    Where:

    • Yshij = value of variable y for the j-th sample household in category s within the i-th sample SEA in district h

    • Wshi = basic weight for the sample households in category s within the i-th sample SEA in district h.



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