1. DATATHON 10 AM - 5 PM November 9, 2017 OPEN DATA  INSIGHTS
AGRICULTURAL POLICY SUPPORT UNIT
22, Sech Bhaban - 4th Floor
Manik Mia Avenue
Sher-e-Bangla Nagar
Dhaka 1207

2. FTF Datasets
Population Based Surveys for 11 FTF countries publicly available on the USAID Development Data Library:
Bangladesh*
Ethiopia
Ghana
Malawi*
Mozambique
Nepal*
*Baseline and follow-up available
Kenya
Rwanda*
Tajikistan
Uganda*
Zambia*

3. Bangladesh
Among the three countries most affected by extreme weather events (Anemülle et al., 2006; UNDP, 2004)
Climate variability accounts for 41%, 45% and 49% of yield variability in dry, terrace and coastal ecosystems, respectively (Rahman et al., 2017)
Increase in female share of the agricultural labour force, especially in post- harvest activities, in recent decades (> 50%) (FAO, 2011; Thompson and Sanabria, 2010)
Reduced gender disparities associated with higher levels of plot-level technical efficiency (Seymour, 2017)

4. Feed the Future Zone of Influence (FtF ZoI)
27.4 million people (~17% of total population)
Poverty headcount ratio:
National = 31% (World Bank, 2010)
FtF ZoI = 34% (USAID, 2014)
Under-five stunting:
National = 36% (DHS, 2014)
FtF ZoI = 32% (USAID, 2014)

5. Data: Bangladesh Integrated Household Survey (BIHS)
Funded by USAID
Bangladesh Policy Research and Strategy Support Program (PRSSP), IFPRI, and Data Analysis and Technical Assistance (DATA)
Representative of rural divisions and FtF ZoI in south-western Bangladesh
Two rounds of panel data ( and 2015), with a two-stage stratified sampling (villages and households)
Their roles are as follows:- PRSSP designed the tool, IFPRI oversaw it, and DATA was the local survey firm

6. Two-stage sampling
The country

7. Two-stage sampling
The country can be divided…

8. Two-stage sampling
…into small Primary Sampling Units (PSUs) (and strata)

9. Two-stage sampling
The country is divided into small Primary Sampling Units (PSUs)
In the first stage, PSUs are selected

10. Two-stage sampling
The country is divided into small Primary Sampling Units (PSUs) (and strata)
In the first stage, PSUs are selected
In the second stage, households are chosen within the selected PSUs

11. Data: Bangladesh Integrated Household Survey (BIHS)
Under-five children
Division
2011
2015
Barisal†
700
716
Chittagong
960
990
Dhaka†
1,980
2,027
Khulna†
1,020
1,056
Rajshahi
580
605
Rangpur
543
572
Sylhet
720
749
Total
6,503
6,715
Division
2011
2015
Barisal
164
160
Chittagong
460
452
Dhaka
763
691
Khulna
168
Rajshahi
229
192
Rangpur
232
204
Sylhet
386
415
Total
2,402
2,282
Type
2015 households
FtF original
1025 (15%)
FtF additional†
1071 (16%)
Nationally representative
4619 (69%)
† To allow for a more robust disaggregated analysis

12. Data: Bangladesh Integrated Household Survey (BIHS)
Detailed data on:
Plot-level agricultural production and practices (male module)
Dietary intake of household members (female module)
Anthropometric measurements (height and weight) of all members
Women’s empowerment in agriculture index (WEAI) (male and female modules)

13. Topics/issues 1. Weather variability and female farming
2. Cropping patterns and dietary quality
3. Women’s empowerment in agriculture and nutritional outcomes

14. Topic #1
1. Weather variability and female farming

15. STOP! Can you do it yourself?
Topic #1
STOP! Can you do it yourself?
Please use datafiles:
-2. Bangladesh_1950_2015_rainfall
-3. Bangladesh_1950_2015_temperature
to produce two different graphs with annual distribution of [rainfall, temperature] over time (possibly with smoothed line), in any software you like!

16. Temperature

17. Rainfall

18. Shares look much higher over time
Temperature indeed looks generally a bit lower in 2015

19. Rainfall increasing pattern 2011-2015

20. Topic #2
2. Cropping patterns and dietary quality

21. Rice average yield seems to increase

22. Dietary quality greatly improved!

23. Topic #3
3. Women’s empowerment in agriculture and nutritional outcomes

24. Somehow improved in 2015, but spatial pattern unclear
Much improved in 2015

25. Improved in 2015, but again spatial pattern unclear

26. Finally, the end!? No, please delete the previous maps!

27. BIHS Sample Sizes by Division
Households
Children
Division
2011
2015
Barisal
700
716
Chittagong
960
990
Dhaka
1,980
2,027
Khulna
1,020
1,056
Rajshahi
580
605
Rangpur
543
572
Sylhet
720
749
Total
6,503
6,715
Division
2011
2015
Barisal
164
160
Chittagong
460
452
Dhaka
763
691
Khulna
168
Rajshahi
229
192
Rangpur
232
204
Sylhet
386
415
Total
2,402
2,282

28. BIHS Sample Sizes by District, Households
2011
2015
Bagerhat
140
146
Bandarbon 20 21
Barisal
200
204
Bhola
120
124
Bogra
122
Borgona
100
102
Brahmanbaria
101
Chandpur
129
Chittagong
160
174
Choua Danga 80 84
Comilla
Cox's Bazar
Dhaka 60
Dinajpur
110
Faridpur
180
187
Feni 61
District
2011
2015
Gaibanda
100
102
Gazipur 80 81
Gopalgonj
120
123
Hobiganj
180
186
Jaipurhat 40
Jamalpur
Jessore
184
Jhalakati 60 63
Jhenaidah
130
Khagrachari 20
Khulna
121
Kishoreganj
160
143
Kurigram 83
Kustia
Lakshmipur
Lalmonirhat 46
District
2011
2015
Madaripur
100
Magura 80 84
Manikgonj 81
Meherpur 40 41
Moulvibazar
160
167
Munshigonj
Naogaon
106
Narail 60
Naray Angonj 66
Narshingdi
120
Nasirabad
260
263
Natore 65
Nawabganj
Netrakona
143
Nilphamari 63
Noakhali
District
2011
2015
Pabna 80 89
Panchagarh 20
Parbattya Chattagram
Patuakhali
120
122
Pirojpur
100
101
Rajbari 60 63
Rajshahi 61
Rongpur
103
105
Shariatpur
102
Shatkhira
140
143
Sherpur
104
Sirajgonj 82
Sun Amgonj
180
185
Sylhet
200
211
Tangail
187
Thakurgaon 40 43

29. BIHS Sample Sizes by District, Children
2011
2015
Bagerhat 27 35
Bandarbon 16 15
Barisal 43 42
Bhola 41 47
Bogra 44
Borgona 25
Brahmanbaria 68 51
Chandpur 55 63
Chittagong 74 87
Choua Danga 17 13
Comilla 95
100
Cox's Bazar 36 34
Dhaka 18 23
Dinajpur 45 32
Faridpur
Feni 21 20
District
2011
2015
Gaibanda 47 34
Gazipur 27 35
Gopalgonj 25 29
Hobiganj
103
102
Jaipurhat 19 10
Jamalpur 44 38
Jessore 28
Jhalakati 11
Jhenaidah 20 23
Khagrachari 8
Khulna 12 16
Kishoreganj 98 73
Kurigram 36
Kustia 13
Lakshmipur
Lalmonirhat 18
District
2011
2015
Madaripur 24 22
Magura 10 9
Manikgonj 32 30
Meherpur 6
Moulvibazar 74 94
Munshigonj 19
Naogaon 31 29
Narail 18
Naray Angonj
Narshingdi 55 39
Nasirabad
113
102
Natore 23 21
Nawabganj 16 15
Netrakona 71 73
Nilphamari 20
Noakhali 43 35
District
2011
2015
Pabna 25 32
Panchagarh 7 8
Parbattya Chattagram 12 10
Patuakhali 26 27
Pirojpur 18
Rajbari 15 9
Rajshahi 23
Rongpur 36
Shariatpur 31 30
Shatkhira 22
Sherpur 54 39
Sirajgonj 48
Sun Amgonj
113
116
Sylhet 96
103
Tangail 69 64
Thakurgaon 19 20

30. Topic #1
(Division Level)

31. Topic #1
(Division Level)

32. Topic #2
(Division Level)

33. Topic #3
(Division Level)

34. Conclusions Please use the FtF data: they are a free public good!
Under certain conditions, data exploration and mining is fine, but…
…know what you are doing, i.e. read the documentation beforehand
…always double-check, validate, triangulate your findings with external data sources and references
…beware that correlation (also spatial) is not causation!
…causation can be detected with some sophisticated techniques, although always remember the “traffic misconception”!

35. Finally, the end!

36. Data Sources
Ahmed, Akhter Bangladesh Integrated Household Survey (BIHS) Washington, DC: International Food Policy Research Institute (IFPRI) [dataset]
Fick, S.E. and R.J. Hijmans, Worldclim 2: New 1-km spatial resolution climate surfaces for global land area. International Journal of climatology
Funk, Chris, Pete Peterson, Martin Landsfeld, Diego Pedreros, James Verdin, Shraddhanand Shukla, Gregory Husak, James Rowland, Laura Harrison, Andrew Hoell & Joel Michaelsen. Monthly rainfall data for 2011 and 2015
Global Agro-ecological Assessment for Agriculture in the 21st Century (GAEZ v 2.0), FAO/IIASA, 2002
Guo, Zhe; Cox, Cindy M Market access. In Atlas of African agriculture research and development: Revealing agriculture's place in Africa. Sebastian, Kate, Ed. Pp Washington, D.C.: International Food Policy Research Institute (IFPRI).
International Food Policy Research Institute (IFPRI) Bangladesh Integrated Household Survey (BIHS) Washington, DC: International Food Policy Research Institute (IFPRI) [dataset]
ISRIC - World Soil Information
K. Didan. (2015). MOD13C2/MYD13C2 MODIS/Terra Vegetation Indices Monthly L3 Global 0.05Deg CMG V006. NASA EOSDIS Land Processes DAAC.
You, L., U. Wood-Sichra, S. Fritz, Z. Guo, L. See, and J. Koo Spatial Production Allocation Model (SPAM) 2005 v2.0, accessed online
Z. Wan, S. H. (2015). MOD11C3 MODIS/Terra Land Surface Temperature/Emissivity Monthly L3 Global 0.05Deg CMG V006. NASA EOSDIS Land Processes DAAC.