SAMPLING STRATEGIES OF ILSSI BASELINE SURVEYS AND KEY MODULES

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1 SAMPLING STRATEGIES OF ILSSI BASELINE SURVEYS AND KEY MODULES Data were collected from 439 households in Ethiopia, 450 households in Tanzania, and 902 households in Ghana using the following modules: 1) crop and livestock inputs, production and practices; 2) household and women s dietary diversity; 3) child health, diet, feeding and anthropometry; 4) household shocks, assets and credit; and 5) the Women s Empowerment in Agriculture Index (WEAI). In Ghana additional modules were added for credit, food consumption and farmer networks. ILSSI sampling strategy in Ethiopia The baseline survey in Ethiopia was implemented by the Association of Ethiopian Microfinance Associations (AEMFI) during November 14 th - December 26 th 2014, covering the previous production year. The sample for the household survey is drawn from the 4 woredas in which IWMI/ILRI interventions on small-scale irrigation are taking place: Dangila and Bahir-Dar Zuria in Amhara, Lemo in SNNPR, and Adami Tulu in Oromia. For each of these woredas, we obtained a list of kebeles with data on population size (using CSA data) and suitability for irrigation based on the ex-ante suitability analysis conducted for the AWM Solutions project. The methodology for small-scale irrigation analysis is described in Xie et al. (2014); this article describes how the average suitability scores were calculated for all rural kebeles in these 4 woredas (see Figure 1). We selected 15 kebeles from within the chosen woredas. In order to determine the number of kebeles to select per woreda, we first calculated the total population size (number of households) across all the kebeles with a suitability score of 30 or greater in each woreda. We then determined the number of kebeles to select from each woreda based on the population contained in areas with a high suitability score. This resulted in the following breakdown: Dangila 2 Bahir Dar Zuria 7 Adami Tulu 3 Lemo 3 In other words, the number of kebeles selected per woreda depended on the size of the population living in high potential areas within that woreda. Within the woreda, the intervention kebeles, (which were not ) were included the sample. The remaining kebeles were drawn randomly with probability proportional to size. This resulted in the following sample of kebeles: Kebeles Mean suitability score No. of households Adami Tulu (4) 1 Edo Gojola

2 2 Bochesa* Bahir Dar Zuria (9) 1 Yegoma Huletu ,997 2 Robit* ,916 3 Wejir Welda Menta ,166 4 Tis Abay Town ,369 5 Meshenti Town ,101 6 Wegeligo Gomibat Aba Gerima ,235 Dangila (3) 1 Gumbri Abela Akana ,236 2 Ligaba Dangishta*?? Lemo (3) 1 Ajo Teasa Digba Upper Gana* *intervention site Within each of the chosen kebeles, we obtained a list of households from the local extension office with an indication of whether the household uses irrigation or not. We 10 households from the list of irrigators and 10 households from the list of non-irrigators for a total of 20 hhs per kebele. Given that we are sampling 15 kebeles, this gives a sample size of 300 households. We included in the sample all households participating in the intervention within the intervention kebeles (142 households). This brings the total number of households to 442. NOTES: The kebele selected for the IWMI/ILRI intervention in Dangila did not appear on our GIS shape file or in the population data provided by CSA so we do not have these data for this site. Some of the intervention households originally identified by IWMI and partners changed after the baseline survey was conducted. Therefore, some households originally sampled as intervention households ended up not participating in the program.

3 Figure 1: Location of the Ethiopia ILSSI baseline survey

4 ILSSI sampling strategy in Tanzania The baseline survey in Ethiopia was implemented by Sokoine University during June 24 th July 11 th, 2015, covering the previous production year. The sample for the household survey is drawn from the 2 districts in which IWMI interventions on smallscale irrigation take place: Kilosa and Mvomero districts in Morogoro region. For each of these districts, we obtained a list of villages with data on population size (using the 2012 Population census data from Tanzania National Bureau of Statistics) and suitability for irrigation (at the ward level) based on the exante suitability analysis conducted for the AWM Solutions project (Xie et al. 2014) and later refined for Cervigni and Morris (2015). In addition to the 2 intervention villages (one in each district), we 12 additional villages from within the 2 districts in the following way: We first determined the number of wards in the district with an average irrigation suitability score of 30 or greater. We then calculated the total population size living within high irrigation potential wards in each district. We determined the number of villages to sample from each district based on the proportion of households living in areas with a high suitability score. This resulted in the following breakdown: Comment [RC(1]: Was ETH also refined through the WB drylands study? If yes, we need to mention this here. -And in the end, only one method could have been used, either AWM OR WB drylands.., unlikely that a mix of two were used. Comment [BE(2]: I sent a separate attachment describing the methodology District No. of villages Total number of villages Kilosa 7 8 Mvomero 5 6 Total In other words, the number of villages selected per district depended on the size of the population living in high potential areas within that district. Within the district, the selected number of villages was drawn randomly with probability proportional to population size, with the exception of villages in which the IWMI/ILRI interventions take place. The intervention sites were not selected at random but based on scoping work done by IWMI/ILRI. Adding the two intervention sites brings the total number of villages in the sample to 14. This resulted in the following sample of villages: Districts/villages Suitability score Number of households Kilosa (8) Chanzulu ,617 Idete ,735 Kimamba 'A' ,076 Kibaoni ,218 Kondoa ,564 Madudumizi ,882

5 Zombolumbo ,068 Rudewa Mbuyuni* ,627 Mvomero (6) Magali ,263 Mangae ,543 Changarawe ,271 Lubungo 'B' ,969 Tangeni ,386 Mkindo* *intervention site Within each of these villages, we obtained a list of households from the local extension office with an indication of whether the household uses irrigation or not. We 14 households from the list of irrigators and 14 households from the list of non-irrigators for a total of 28 hhs per village. In each of the 2 intervention villages we have a considerable number of households identified (selection not random but pre-determined) to participate in the program. In these villages all intervention households are identified as the irrigators and we interviewed an additional 15 non irrigating households (selected randomly) per village. This results in the following breakdown of households: District Ward Village Number of hhs Breakdown of Households Kilosa Chanzuru Chanzulu 28 Kilosa Chanzuru Idete 28 Kilosa Kimamba 'A' Kimamba 'A' 28 Kilosa Mabwerebwere Kibaoni 28 Kilosa Mabwerebwere Kondoa 28 Kilosa Zombo Madudumizi 28 Kilosa Zombo Zombolumbo 28 Kilosa Rudewa Rudewa Mbuyuni* intervention households (see list), 15 non-irrigators () Mvomero Melela Magali 28

6 Mvomero Melela Mangae 28 Mvomero Mzumbe Changarawe 28 Mvomero Mzumbe Lubungo 'B' 28 Mvomero Mzumbe Tangeni 28 Mvomero Hembeti Mkindo* intervention households (see list), 15 non-irrigators () Figure 2: Location of the Tanzania ILSSI baseline survey

7 ILSSI sampling strategy in Ghana The baseline survey in northern Ghana was conducted by the University for Development Studies (UDS), Tamale, Ghana from early November of 2015 to early February, UDS researchers and enumerators worked closely with an IFPRI representative and survey consultant, Mr. Jacob Thompson in the field data collection exercise in November 2015 to implement the household baseline survey including questionnaires for household survey, women empowerment in agriculture index (WEAI), time allocation and community questionnaire in 12 communities in Savelugu Nanton District in the Northern Region, Kassena Nankana East, Garu Tempane and Nabdam Districts in the Upper East Region. The total number of respondents interviewed in 12 communities was 902. Comment [RC(3]: The sampling strategy is not clear. The ILSSI baseline survey was carried out in four districts in the Northern part of Ghana. Out of these four districts, communities with irrigation projects (dams) were the main focus of the research, with three districts (Savelugu Nanton, Kassena Nankana East, Garu Tempane and Nabdam) being ILSSI communities whereas Garu-Tempane District was an ide intervention area. The ILSSI intervention communities are Bihinayelli in the Savelugu District, Zanlerigu in the Nabdam District, and Dimbasinia/Nyangua in the Kasena Nankana East District. Nine additional communities were surveyed from the Garu Tempane District: Gbenterago Alemgbek, Akara, Bugri Natinga, Binpiala, Denegu, Zule, Mognoori, Yidigu and Asikiri. Table 1: Project communities and number of respondents surveyed COMMUNITY NAME COMMUNITY ID NUMBER OF RESPONDENTS INTERVIEWED GBENTERAGO ALEMGBEK AKARA BUGRI NATINGA 4 35 BINPIALA 3 21 DENEGU 7 39 ZULE 5 20 MOGNOORI YIDIGU 8 52 ASIKIRI ZANLERIGU DIMBASINIA/NYANGUA 9 40 BIHINAYELLI TOTAL The sampling frame in Ghana is somewhat different than in Ethiopia and Tanzania because of the inclusion of an additional intervention involving a collaboration between IFPRI and ide. We therefore surveyed all ILSSI intervention households as well as households participating in an IFPRI-iDE

8 intervention and controls. All ILSSI intervention households that IWMI, ILRI, and NCA&T are working with Savelugu Nanton District in the Northern Region, Kassena Nankana East, Nabdam Districts in the Upper East Region are included in the sample irrespective of how these households were selected to be part of the intervention. These are 102 households across the three districts. In Garu Tempane district, IFPRI collaborated with ide-ghana to introduce water extraction technologies (motor pumps) in 9 selected villages in Northern Ghana identified by ide-ghana. The sampling frame involves an experimental design in order to identify the impacts of the introduction of motor on nutrition and health. The intervention is phased in over time so that 4 villages received the intervention in 2015 (early treatment villages) and 5 villages will receive the intervention in 2017 (late treatment villages). All villages selected meet the following criteria: 1) they are located within the Feed the Future zone of influence, 2) they are near ide areas of ongoing operation, and 3) they show significant potential for irrigation based on the irrigation suitability score. Following an introduction of the program to village leaders and then the community at large by ide, farmers were asked to self-organize into groups for the purpose of receiving a group loan from a microfinance institute. Farmers were first organized into confidence groups of 20 farmers in order to receive group loans from a micro-finance institute. The confidence groups are further broken down into smaller trust groups of approximately 5 farmers each. In total 158 trust groups formed which included a total of 800 farmers. These groups received training from ide on group dynamics and micro-finance. ide then linked farmers with a local micro-finance institute (MFI) or credit union to provide credit for the purchase agricultural inputs, such as fertilizer and seeds. IFPRI (through ide) offered an additional loan to purchase a motor pump at a favorable interest rate to a random sub-sample of groups. Comment [BE(4]: Maybe again link to methodology The identification of early and late treatment villages was not known at the outset of the project when ide first contacted the communities to form groups. Because the size of the villages and number of groups formed in each village were not uniform across all 9 communities, IFPRI communities using probability proportional to size until the number of farmer groups were roughly equal between early and late treatment villages. Within the early treatment villages, a sub-sample of trust groups received an additional preferential credit incentive to purchase a motor pump through a random lottery. Given the liquidity constraints that micro-finance institutions in Ghana face, IFPRI provided guaranteed loan access using supplementary funding provided by the Water, Land, and Ecosystems Research Program of the CGIAR (WLE), and the loans were managed by ide. These loans were to be used for the purchase a motor pump and were conditional on the understanding that the pump would be shared amongst members of the trust group in a predetermined schedule that is agreeable by all the group members. Groups that randomly receive the loan offer through the lottery could decide not to purchase a pump and still apply for a loan for other inputs through the micro-finance institute. On the other hand, the control group of farmers who didn t get the loan offer could still purchase pumps from the market either using their own money or getting the loan from the MFI or any other financial institution. Farmer groups are expected to repay the full cost of the pump to ide at a preferential interest rate of 20%. The repaid loans will be used to extent the loan offer to: (i) groups that did not win the lottery in

9 round 1 in the early treatment villages and (ii) a random subset of groups in the late treatment villages in Groups that did not win the lottery in round 2 in the late treatment villages would receive the loan offer in 2018 at the end of the project. This design allows a comparison between those in the early treatment villages who won the lottery and those in late treatment villages, as well as between those who are in the early treatment villages but didn t win the lottery and those who are in the late treatment villages. The first comparison allows us to capture the direct effect of improved access to irrigation technology on those who got the technology, while the second comparison enables identification of any spill-over effects of living in a community where some people have access to irrigation technology. Farmers that did not receive preferential loans for the purchase of motor pumps in both the early and late treatment communities involved in the ide experiment can also be used as controls for the ILSSI intervention farmers. Because these farmers already expressed interest in irrigation and improving agricultural production practices in general, this minimizes the selection bias due to fact that ILSSI households self-selected into the ILSSI intervention. All the communities sampled in Ghana are shown in Figure 3, distinguished by their classification as an ILSSI intervention community, ide early treatment community, or ide late treatment community.

10 Figure 3: Location of the Ghana ILSSI baseline survey KEY MODULES FOR THE ILSSI BASELINE SURVEY Intra-household surveys: Irrigation and women s empowerment ILSSI is using the Women s Empowerment in Agriculture Index (WEAI) to measure the relationship between women s empowerment and irrigation and how women s empowerment influences nutrition outcomes. The WEAI is a survey-based tool, asked of both the main male and female decisionmakers in a household used to determine inclusion of women in domains important to the agricultural sector. It takes about 40 minutes to complete. There are multiple domains of empowerment. Whereas previous measurements were only able to measure individual domains, the WEAI has the advantage of measuring five domains that are important in the agricultural sector. The five domains of empowerment in the agricultural sector measured in the WEAI include: Production: decisions about agricultural production, including sole or joint decisionmaking power over food or cash-crop farming, livestock, and fisheries, as well as autonomy in agricultural production

11 Resources: access to and decisionmaking power over productive resources, including ownership of, access to, and decisionmaking power over productive resources such as land, livestock, agricultural equipment, consumer durables, and credit Income: sole or joint control over income and expenditures Leadership: Leadership in the community, including membership in economic or social groups and being comfortable with speaking in public Time: allocation of time to productive and domestic tasks and satisfaction with the time available for leisure activities These are measured through 10 individual indicators in the survey based tool, and weighted using the weighting scheme listed on the right in Table 1. In addition to the domains, the WEAI calculated score also includes the Gender Parity Index. This reflects the percentage of women who are as empowered as the men in their household. This component takes into account the male counterpart s responses to the 10 indicators and calculates a how many women achieve parity with their husband, and for those who do not, how great is the gap of inadequacy. Specifically, ILSSI is using a modified WEAI to better capture linkages between irrigation and gender. In some cases, questions were added to distinguish between irrigated and rainfed production, e.g. in the case of decisionmaking roles and autonomy in decisionmaking. In addition, response codes or categories were added to capture specifics about irrigation. For example, the module on productive capital includes categories for irrigation equipment and water storage. Similarly, the time allocation module adds a category for time spent irrigating or working with irrigation equipment. Other modifications to the WEAI include additional modules or questions on credit, savings, and group membership. Anthropometric Measurements In taking the anthropometric measurements, the specific eligibility criteria for respondents to be measured were emphasized to enumerators both during the pre-survey training and in the field. The criteria are restated follows: Children less than five years old (i.e. up to 59 months) were eligible for height, weight, head circumference and mid arm-upper circumference (MUAC) measurements. It also included Oedema assessment. Women within their reproductive age (between 18 and 50 years) were also eligible for weights and heights measurements. Community Interviews The survey also included a community questionnaire which was conducted through interviews with key informants comprising of village chief, village chairmen, community elders, opinion leaders and other

12 important personalities in the community. The community survey was carried out to provide a comprehensive and in-depth understanding of information relative to community physical infrastructure and endowments such as schools, hospitals, clinics, markets, lorry parks, means of transport, water sources for domestic and agricultural uses, crop grown, animals reared, irrigation practices, diseases, illnesses, as well as agricultural and health support services among others at the village level. One community survey was administered in each community, thus, 12 community surveys for the 12 ILSSI project communities.

13 REFERENCES Cervigni, R. and M. Morris (eds.) Confronting Drought in Africa s Drylands: Opportunities for Enhancing Resilience. Africa Development Forum series. Washington, DC: World Bank. License: Creative Commons Attribution CC BY 3.0 IGO. Xie, H., L. You, B. Wielgosz and C. Ringler Estimating the potential for expanding smallholder irrigation in Sub-Saharan Africa. Agricultural Water Management /j.agwat (1):