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Survey Methods Guide for Bangladesh Aquaculture Value Chains
1. Photo Credit Goes Here
INTRODUCTION TO SURVEY METHODS
Ricardo Hernandez (Alliance of Bioversity and CIAT)
Ben Belton (Michigan State University)
M. Mahfujul Haque (Bangladesh Agricultural University)
Ali Hazrat (WorldFish)
Photo: Google Earth
August 4–8, 2022
2. INTRODUCTION
• Stacked value chain surveys of farmers, traders, hatcheries, and
input providers
• It relies on revisiting 2014 USAID funded, and IFPRI-MSU led
stacked survey of VC segments (input providers, feed mills, farmers,
traders, and retailers) and meso-level survey
• 2014 survey covered 20 districts in the East, North, Southwest, and
Southcenter
• 2020 survey focuses on 7 districts in South and Southwest
3. 2014 SURVEY ACTIVITIES
• Micro level survey sample was drawn with a purposive stratified random sampling
method.
– Fish farming is concentrated in certain districts;
– Focus on the main dynamics of the sector which were visible in the main clusters
• Using 2008 agricultural census, we identified 6 clusters of production, after trimming
areas with negligible production, we retained 102 upazilas (UZ) that cover 86% of
production.
• Using PPS, we randomly selected 32 UZ. Then we listed all mouzas (MZ), and
trimmed MZ with less than 20 farmers.
• Using PPS we randomly selected 77 MZ. In each selected MZ we did a rapid census
of farmers, then randomly selected 25 (20 for sample + 5 replacement)
• Final farm household sample was 1,540 farmers, distributed in 20 districts, 32 UZ,
and 77 MZ. (PSU)
4. DISTRIBUTION OF TOTAL POND AREA, NUMBER OF UPAZILAS AND SELECTED
PRIMARY SAMPLE UNITS BY CLUSTER AREA IN BANGLADESH.
Source: 2008 Agricultural Census
Cluster
Total Pond
Area
(decimals)
Selected Pond
Area
(decimals)
Total
Upazilas
Selected
Upazilas
Share of Cluster
Area over Total
Pond Areas
Assigned
PSUs in each
Cluster
Area 1 1,723,253 1,548,929 51 25 56% 42
Area 2 625,225 508,222 59 32 20% 15
Area 3 45,312 36,768 8 5 1% 1
Area 4 143,298 118,066 18 12 5% 4
Area 5 301,028 243,482 31 15 10% 7
Area 6 264,999 213,354 22 13 9% 6
TOTAL 3,103,115 2,668,821 189 102 100% 75
86% 54%
5. • Hatcheries, traders, input (mainly feed) dealers, were selected at the UZ level (not
MZ)
• In each UZ we conducted a rapid enumeration of hatcheries, traders, and feed dealers
based on the farmer sample distribution.
• Around 3000 actors (farmers, hatcheries, rural output and input traders, feed
mills, and rural retailers) from four main clusters (zones) that included 20
districts. February to June 2014
• Survey questionnaires included 4 broad categories:
– demographic and business characteristics such as assets holdings;
– intermediate input and factor (land, labor, capital, including variable and quasi-fixed inputs) procurement;
– production technology and value addition;
– marketing of outputs
6. • South and South central zone of Bangladesh
• Updated panel (resurvey of 2014 survey
respondents + randomly selected replacements
• 7 districts under Khulna, Barisal and Dhaka
Divisions
• FGDs were conducted in 36 communities and
32 markets for farmers & traders survey,
respectively.
• Developed a census of 3700 fish/shrimp
farmers – randomly surveyed 720 farmers
• Developed a census of 1200 traders –
randomly surveyed 329 (retailers, wholesalers,
arotders, foria, depots and commission agents)
• Developed a census of 250 input traders –
randomly surveyed 79 traders
2020 SURVEY ACTIVITIES
8. PREPARATION, TRANSLATION AND PRE-TESTING OF QUESTIONNAIRE
• Farm household questionnaire was very comprehensive, it included
24 modules.
Initial pre-testing at the household level Initial pre-testing on the pond side Initial pre-testing for details inputs data
9. DIGITAL PRE-TESTING OF QUESTIONNAIRE USING TABLET
• After transformation of the questionnaire,
uploaded on the KoBo Toolbox, free open-
source tool for mobile data collection.
• Repeated pre-testing of the questionnaire
was conducted to avoid possible errors
• Doing this and discussing among the
researchers and research assistants the
digital version was finalised
10. DATA COLLECTION USING TABLET
• Rigorous process was observed to ensure enumerator training during 2 weeks, in-
house and field-based trials to fine tune survey instrument, and data collection
process
11. DATA COLLECTION USING TABLET
Data collection for ground-truthing
• Another set of data was collected for ground
truthing
• Over >1800 GPS coordinates according to 6
categories of farms/water bodies were collected
• This is for machine learning techniques to
automate extraction of data of pond/gher from
satellite images to estimate pond area and fish
production
1 Commercial pond = Pond actively managed to produce
fish for profit, with no other uses except fish culture.
2 Homestead pond = Small pond, usually close to house,
used for growing fish (stocking, some fertilization or
feeding) as well as other domestic uses.
3 Gher with rice = Gher which produces a rice crop in at
least 1 season.
4 Gher, no rice = Gher in which no rice crop is grown.
5 Derelict pond = Pond that is abandoned or is not
managed actively to produce fish (no stocking, no
feeding).
6 Non-aquaculture waterbody = waterbody that has not
used for aquaculture in any way (e.g. canal, beel)
12. DATA COLLECTION USING TABLET
• Data collection for ground-truthing applying Google form