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

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*

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)

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)

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 (2011-2 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

Two-stage sampling The country

Two-stage sampling The country can be divided…

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

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

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

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

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)

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

Topic #1 1. Weather variability and female farming

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!

Temperature

Rainfall

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

Rainfall increasing pattern 2011-2015

Topic #2 2. Cropping patterns and dietary quality

Rice average yield seems to increase

Dietary quality greatly improved!

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

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

Improved in 2015, but again spatial pattern unclear

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

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

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

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

Topic #1 (Division Level)

Topic #1 (Division Level)

Topic #2 (Division Level)

Topic #3 (Division Level)

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”!

Finally, the end!

Data Sources Ahmed, Akhter. 2013. Bangladesh Integrated Household Survey (BIHS) 2011-2012. Washington, DC: International Food Policy Research Institute (IFPRI) [dataset] http://hdl.handle.net/1902.1/21266. Fick, S.E. and R.J. Hijmans, 2017. 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. 2014. Market access. In Atlas of African agriculture research and development: Revealing agriculture's place in Africa. Sebastian, Kate, Ed. Pp. 66-67. Washington, D.C.: International Food Policy Research Institute (IFPRI). http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/128748 http://dx.doi.org/10.2499/9780896298460_28 International Food Policy Research Institute (IFPRI). 2016. Bangladesh Integrated Household Survey (BIHS) 2015. Washington, DC: International Food Policy Research Institute (IFPRI) [dataset] http://dx.doi.org/10.7910/DVN/BXSYEL 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. https://doi.org/10.5067/modis/mod13c2.006 https://doi.org/10.5067/modis/myd13c2.006 You, L., U. Wood-Sichra, S. Fritz, Z. Guo, L. See, and J. Koo. 2014. 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. https://doi.org/10.5067/modis/mod11c3.006