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# CSISA GAAP Presentation (2) January 2013

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Presentation given by CSISA at GAAP final technical workshop in Addis Ababa, January 2013

Presentation given by CSISA at GAAP final technical workshop in Addis Ababa, January 2013

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• describe what assets (tangible and intangible) are important to men and women in order to sustain their livelihoods;identify who has access to and control (how assets were acquired, who makes decision on when, how to use/dispose) over these key assets/resources; assess the current or anticipated effects of the technologies/interventions under CSISA project on men and women’s access to and control of these key assets and; examine how women and men respond or adjust due to changes in the assets as a result of project interventions introduced by the CSISA project
• The Mann-Whitney U test is often viewed as the nonparametric equivalent of Student&apos;s t-test. Like the parametric Student&apos;s t-test, the non- parametric Mann-Whitney U test: -- is used to determine if a difference exists between two "groups," however you define "group“ This is the nonparametric equivalent of the unpaired t-test It is applied when there are two independent samples randomly drawn from the population e.g. diabetic patients versus non-diabetics .THe data has to be ordinal i.e. data that can be ranked (put into order from highest to lowest )It is recommended that the data should be >5 and &lt;20 (for larger samples, use formula or statistical packages) The sample size in both population should be equal
• : this would be a lot easier to digest if you did it as a bar graph, where for every asset, you have a stacked bar of owned and rented in baseline, next to a bar for owned and rented in midline. Right now this is too hard to understand.
• 49-54 I would strongly suggest to put % instead of numbers, so that we can mentally compare patterns across slides
• 56-59 again, put into % to make it easier to compare You would have to go through these very quickly

## CSISA GAAP Presentation (2) January 2013 Presentation Transcript

• Gender, Agriculture and Assets Project (GAAP) Evaluating the Impacts ofAgricultural Development Programming on Gender Inequalities, Asset Disparities and Rural Livelihoods Thelma Paris, Val Pede and Joyce Luis With assistance from Abha Singh, Raman Sharma, Donald Villanueva, Jeffrey Estipular and Maria Theresa Castro Thanks to Ruth, Nancy and Agnes Presented at the Final Meeting of GAAP Jan 8-11, 2013, ILRI, Addis Ababa, Ethiopia
• Cereal Systems Initiatives for South Asia (CSISA)• Reduce poverty and improve the well-being of poor farm families in South Asia (income of 60,000 farm households) – Through development and dissemination of technologies • New varieties • Sustainable crop and resource management • Direct seeded rice • Laser land leveler • Zero tillage (rice and wheat) • Crop residues for livestock feed – Policies for economic growth T.Paris/V.Pede 8th Jan 2013
• CSISA hub domains T.Paris/V.Pede 8th Jan 2013
• Fig 4. Sampling scheme HouseholdHub Level District Level Block Level Village Level Level CSISA 18 Households Block 1 Non-CSISA 18 Households CSISA 18 Households Block 2 Non-CSISA 18 Households District 1 CSISA 18 Households Block 3 Non-CSISA 18 Households CSISA 18 Households Block 1 Non-CSISA 18 HouseholdsHub District 2 Block 2 CSISA Non-CSISA 18 Households 18 Households CSISA Block 3 18 Households Non-CSISA 18 Households CSISA 18 Households Block 1 Non-CSISA 18 Households District 3 CSISA 18 Households Block 2 Non-CSISA 18 Households 18 Households CSISA Block 3 18 Households Non-CSISA T.Paris/V.Pede 8th Jan 2013
• CSISA Baseline• Survey – Baseline household survey – September 2010 to May 2011 – 2492 households for all 8 hubs – Selected findings • Adoption of CA technologies still very low • Familiarity with CSISA and the promoted technologies still weak among farmers Zero Tillage Direct Seeded Rice Laser Land LevelingUnfamiliar 64.2 92.6 83.7Heard About 7.1 2.5 1.5Seen 24.7 4.3 12Adopted 4 0.6 2.8
• Highlights and gaps in CSISA baseline• Highlights – Women contribute 32 to 49% to total labor use in cereal production – Women from small and marginal farm households spent more time in animal husbandry, collection of fuel and animal fodder and graze animals than men – Gender inequalities in access to and control of key assets and resources persist – Women are generally excluded in project activities – Labor –saving technologies will have gender- differentiated impacts on men and women• Gaps – Limited information on access to and control of key assets and resources by gender and social groups
• Specific objectives of GAAP under CSISA• describe what assets are important to men and women in order to sustain their livelihoods;• identify who has access to and control over these key assets/resources;• assess the current or anticipated effects of the technologies under CSISA project on men and women’s access to and control of these key assets and;• examine how women and men respond or adjust due to changes in the assets as a result of project interventions introduced by the CSISA project T.Paris/V.Pede 8th Jan 2013
• MethodologyPart 1 – Problem identification• Documented gender disparities in asset access to and control using qualitative methods as well as strengthening methods for measuring men’s and women’s access to and control over assets.Part 2 - Impact assessment• Assessed current or anticipated effects of the technologies under CSISA project on men and women’ access to and control of the identified key assets using midline surveys with gender asset questions.• Assessed how men and women respond or adjust due to changes in the assets as a result of project interventions T.Paris/V.Pede 8th Jan 2013
• Part 1• Selection of study sites - Three districts in Maharajganj, Deoria, and East Champaran in Bihar, India and 18 villages in Eastern Uttar Pradesh, India• Focus group discussions - In each district, two villages (one CSISA village and one non-CSISA village) with separate groups of men and women from the upper and lower castes were included in the FGDS. – Each group was asked to identify what assets are commonly owned by typical farming households. – A pre-tested form, developed by the IRRI team of social scientists, was used to ask asset-related questions. – Pictures of specific assets in India were developed• In-depth interviews - 120 respondents (60 principal males and 60 principal females) to rank perceived importance of assets by gender and social class• Used of pictures of assets as defined by respondents. Pictures were used to complement the associated questions. T.Paris/V.Pede 8th Jan 2013
• Natural and Physical assets Rotavator Rice mill Irrigation canalFarm land ThresherDraft animals Water pump Mechanical thresher TractorDairy animals Small animals Combine T.Paris/V.Pede 8th Jan 2013
• Physical assetsKatcha house Silver jewelry Expensive clothing Bicycle Pucca house Gold jewelry Television Motorcycle Radio/Cassette Mobile phones T.Paris/V.Pede 8th Jan 2013
• Human, Social and Financial Farmer’s association NREGA membership Trainings Social Women’s group Human Micro-finance Diploma Informal groups FinancialMoney lend to others Savings in bank Cash on hand T.Paris/V.Pede 8th Jan 2013
• COMPARISON OF IMPORTANCE OF ASSETS - MANN WHITNEY U-TEST “Do men and women rank assets differently?”The test determined if there were significantdifferences between the importance rating (ordinalvariable) of assets in two independent groups(men and women): -Physical -Human -Social -Financial T.Paris/V.Pede 8th Jan 2013
• Table 1a. Gendered differences on importance of assets , EUP, India Male Female ASSETS p-value n mean rank n mean rank Agricultural Farm land 59 1.10 59 1.86 0.000 Dairy animals 34 3.62 35 4.23 0.095 Small livestock 10 6.30 12 3.75 0.009 Non-Agricultural Water pump 22 4.23 20 4.85 0.468 Katcha house (mud) 9 4.11 7 3.86 0.667 Pucca house (bricks) 54 2.70 53 2.38 0.082 Television 18 7.94 23 8.00 0.695 Radio/Tape-recorder 5 7.20 9 4.22 0.450 Mobile phone 49 6.24 46 7.04 0.009 Expensive clothing 35 7.26 46 7.22 0.264 Gold Jewelry 37 6.65 57 3.63 0.000 Silver Jewelry 33 6.88 58 5.91 0.002 Bicycle 46 6.24 35 7.69 0.001 Motorcycle 21 5.76 12 8.42 0.003 Legend: 1 – most important; T.Paris/V.Pede 8th Jan 2013
• Table 1b. Gendered differences on importance of assets , EUP, India Male Female ASSETS p-value n mean rank n mean rank Education/Degree 7 4.57 5 5.33 0.330 MNREGA member 12 3.75 11 5.64 0.079 Savings 34 6.53 34 6.00 0.282 Cash on hand 50 4.70 45 5.53 0.124 Money lent to others 18 6.50 16 7.25 0.225 T.Paris/V.Pede 8th Jan 2013
• Methods of data collection for adoption of labor saving technologies Table 4. Distribution of households per village and per district by classification, EUP, India, 2011. District Village All • Study sitesGorakhpur Aurangabad Indrapur 25 20 • Number of villages and Kheria 20 households (Table 4) Kotwa 20 • Focus group discussionKushinagar Mukundpur 20 • Case storiesMaharajganj Agya 20 Pokharbhinda 20Siddharth Nagar Babhni 21 Basalatpur 20 Biharipur 20 Dhusuri-Laghu 19 Mahdeia 15 Mohnajot 20 Pokharbhinda 21 Saha 20 Sirwat 20 Total 321 T.Paris/V.Pede 8th Jan 2013
• Adoption of labor saving technologies by caste groupsTable 5. Percentage of farmers who are using specific machines by caste, EUP, India, 2011. Caste Machine Upper Other Backward Scheduled Others (n=56) (n=186) (n=59) (n=20) Combine 89 53 27 70 Rotavator 50 29 8 25 Laser Leveler 2 3 2 Rice thresher 1 Reaper 7 4 2 Transplanter 5 1 2 Zero till machine 9 5 3 10 Source: Thelma Paris, Val Pede, Joyce Luis, Abha Singh and Donald Villanueva. 2011. Assessing the effects of labor saving technologies on employment of men and women agricultural workers in selected villages of Eastern Uttar Pradesh (on-going project) T.Paris/V.Pede 8th Jan 2013
• Adoption of labor saving technologies by farm size groupsTable 6. Percentage of farmers who are using specific machines by size of landholdings, EUP,India, 2011. Farm category Machine Marginal (<1ha) Small (1-2 ha) Medium and Large (>2 ha) (n=248) (n=49) (n=24) Combine 45 94 92 Rotavator 21 51 67 Laser Leveler 2 2 4 Rice thresher 4 Reaper 2 6 17 Transplanter 2 2 4 Zero till machine 2 12 29 Source: Thelma Paris, Val Pede, Joyce Luis, Abha Singh and Donald Villanueva. 2011. Assessing the effects of labor saving technologies on employment of men and women agricultural workers in selected villages of Eastern Uttar Pradesh (on-going project) T.Paris/V.Pede 8th Jan 2013
• Fig. 1 Labor reduction in harvesting and post-harvest activities by using combine machine 30.00 Non-user (n=142) 25.00 User (n=179) Labor (days/ha) 20.00 15.00 10.00 5.00 0.00 Male Female Male Female Family Hired Type and source of laborNote: Figures represent the labor used for harvesting and post-harvest activities in rice production. T.Paris/V.Pede 8th Jan 2013
• Other farm and non-farm activities of womenCleaning Winnowing Making cow dung cake Grazing of goat Knitting cloth Washing cloths Making of basket Taking care of children T.Paris/V.Pede 8th Jan 2013
• Effects of combine on female workers Effects Before AfterLoss of access to non- 20-25 days (rice harvesting); 30-35 No more employmentfarm employment days wheat harvesting (only 5 to 8 days of work within the village); Only 20-25 days in transplantingFood (cereal) insecurity 2-3 months food (share from Reduced food share from wages); 1-2 quintals per season harvesting; only from (costs Rs1000-1500) transplantingLoss of income Rs 1000-1500 from rice harvesting Rs 500 to 800 from rice per season; Rs 1500 -1800 from harvesting per season (earlier wheat harvesting per season wages were lower only Rs 40- 50per day and now Rs100-120 per day); No income from wheat harvestingLabor displacement Assured employment of 30-35 Assured employment only in days during rice harvesting and transplanting 20-25 days during wheat harvestingEconomic dependency Men and women both work as More dependent on MNREGA, hired labor in farming activities non farm income, and during rice and wheat season and remittances from migrant most are dependent on off farm husband as to pay for rental fee labor wages and selling of of machines, animal products T.Paris/V.Pede 8th Jan 2013
• Fig 3. Effects of labor saving technologyadoption on women from farming households Better-off farming households (Landlords, Medium to Large land holders) Effects of laborsaving technology adoption on women Poor, landless and marginal faming households (off-farm workers, marginal to small land holders) T.Paris/V.Pede 8th Jan 2013
• Empowering womenas entrepreneurs in transplanting riceTamil Nadu, India CSISA project
• Part 2Midline Surveys with Gendered Asset Access Information T.Paris/V.Pede 8th Jan 2013
• Midline survey• Survey – Period: June to August 2012 – 324 households were re-surveyed in EUP – More gender-disaggregated data than baseline • Detailed asset information – Who has “access to” and “control” • Income sources • Decision making • Labor participation in crop production • Access to credit and training • Household composition
• Location of households in EUP T.Paris/V.Pede 8th Jan 2013
• Table 9. Owning and Renting Machines Baseline (n=324) Midline (n=318) Machines own rent-in own Rent-in Electric submersible pump 3 11 2 2 Diesel pump 95 223 85 214 4-wheel tractor 7 110 20 229 2-wheel tractor 7 110 1 1 Tine cultivator 13 297 19 282 Disc harrow 7 75 1 42 Rotavator 1 20 4 72 Seed drill 0 3 3 2 Mechanical transplanter 0 0 0 1 Mechanical pesticide sprayer 1 1 0 2 Knapsack sprayer 29 129 45 108 Thresher (power) 20 224 15 185 Thresher (pedal) 1 0 1 34 Combine harvester 2 82 2 85 Fodder chopper 166 0 84 8 T.Paris/V.Pede 8th Jan 2013
• Table 10. Percentage of households who have access to asset Upper Lower Type of assets * Baseline (77) Midline (77) Baseline (247) Midline (241) Agricultural Farm Land 98.7 98.7 93.1 95.4 Dairy Animals 48.1 50.6 41.3 45.2 Small livestock 10.4 11.7 11.3 16.2 Tractor 15.6 15.6 2.4 2.5 Cultivator 15.6 15.6 2.4 2.1 Rotavator 2.6 2.6 0.4 0.0 Combine 5.2 5.2 0.0 0.0 Thresher 9.1 9.1 0.8 0.8 Rice mill/huller 2.6 2.6 1.2 1.2 Water pump 28.6 29.9 23.9 24.5 Non-Agricultural House with thatched roof 39.0 39.0 36.8 36.1 House with concrete floor 79.2 83.1 74.9 78.0 Mobile phone 39.0 42.9 32.8 33.2 Television 10.4 10.4 11.3 10.8 Radio tape-recorder 72.7 83.1 65.2 80.1 Expensive clothing 53.2 59.7 27.1 33.2 Gold Jewelry 87.0 87.0 75.7 77.2 Silver Jewelry 87.0 88.3 79.4 80.5 Bicycle 75.3 85.7 74.5 80.1 Motorcycle 40.3 48.1 16.6 19.1 Own shop 9.1 10.4 7.3 8.3
• Table 12. Number of lower caste household farmers who owns assets Baseline (n=247) Midline 2012 (n=241) Assets Husband Wife Both Husband Wife Both Agricultural Farm land 147 5 78 147 5 78 Dairy animals 55 6 41 56 7 46 Small livestock 6 7 15 11 9 19 Tractor 6 0 0 6 0 0 Cultivator 5 0 0 6 0 0 Combine 0 0 0 0 0 0 Thresher 2 0 0 2 0 0 Rice mill/ huller 3 0 0 3 0 0 Water pump 52 0 7 51 0 7 Non-Agricultural House with thatched roof 37 3 51 35 3 49 house with concrete floor 101 3 81 101 3 84 TV 48 5 28 47 5 28 Radio/tape 18 1 9 16 1 9 Mobile phones 121 4 36 138 6 49 Expensive clothes 5 35 27 7 36 37 Gold jewelry 6 166 15 6 165 15 Silver jewelry 7 176 13 7 174 13 Bicycle 172 5 6 181 5 6 Motorcycle 38 0 3 44 0 2 Shop 13 1 4 15 1 4 T.Paris/V.Pede 8th Jan 2013
• Table 3.2 Number of lower caste household farmers who uses assets Baseline (n=247) Midline 2012 (n=241) Assets Husband Wife Both Husband Wife Both Agricultural Farm land 50 6 174 49 6 175 Dairy animals 20 1 81 20 2 87 Small livestock 1 7 20 3 9 27 Tractor 5 0 1 5 0 1 Cultivator 6 0 0 0 0 0 Thresher 2 0 0 2 0 0 Combine 0 0 0 0 0 0 Rice mill/ huller 3 0 0 3 0 0 Water pump 46 0 12 45 0 13 Non-Agricultural House with thatched roof 10 2 79 9 2 76 house with concrete floor 27 3 155 27 3 158 TV 10 4 67 10 4 66 Radio/tape 4 1 23 4 1 21 Mobile phones 60 4 97 70 6 117 Expensive clothes 2 34 31 4 35 41 Gold jewelry 4 165 18 4 164 18 Silver jewelry 6 174 16 6 172 16 Bicycle 165 6 12 174 6 12 Motorcycle 37 0 4 43 0 3 Shop 11 1 6 13 1 6 T.Paris/V.Pede 8th Jan 2013
• Formula for WEI n xj j 1 WEI _ all dWhere:WEI_all = women empowerment index for all decisions per respondentx = value of decision makerj = code for the specific decision matterd = total number of decisions replied by the respondentN = number of decisions T.Paris/V.Pede 8th Jan 2013
• Table 17a. Involvement of upper caste women in decisions making and activities, EUP Midline Activities Husband only H>W Both W>H Wife only Choice of Crop What crop to grow What variety to use Crop Management When to apply fertilizer Amount to fertilizer use When to apply pesticide/insecticide to use Amount of pesticide/insecticide to use When to irrigate crops When to weed When to hire laborer When to harvest When to thresh rice Post harvest operations Which seeds/variety should be grown next season Amount of rice to store When to sell rice or other crops T.Paris/V.Pede 8th Jan 2013
• Table 17b. Participation of husband and wife in decision making activities Midline Activities Husband only H>W Both W>H Wife only Livestock/poultry rearing Number of large animals to raise When to sell animals Investments How much money to spend on farm inputs How much money to spend on food How much money to spend on capital investments Whether to buy livestock Whether to buy land Expenditure on children’s education House construction Allocation of remittances Politics Who decides whom you should vote for T.Paris/V.Pede 8th Jan 2013
• Table 19. Women Empowerment Index by caste Midline 2012 Activities for decision making Upper (n=77) Lower (n=241) Choice of Crop 1.91 2.07 Crop Management 1.90 2.10 Post harvest operations 2.01 2.41 Livestock/poultry rearing 2.12 2.55 Investments 2.32 2.51 Politics 2.35 2.40 Overall 2.08 2.30 H 1 H>W 2 H=W 3 W>H 4 W 5 T.Paris/V.Pede 8th Jan 2013
• Lessons learnto Individual level data on assets is essential to capture intrahousehold asset gaps.• Access to asset may mean “ownership” or renting. Rather than asking “which of the assets you own or possess?” it will be better also ask the question “if you do not own or possess this asset, do you have access to this asset?”o Asset ownership and acquisition depends on whether the household is a nuclear or extended/joint family with more number of family members.o There are conceptual issues not only in sorting out who owns property within married couples, but also in an individual’s perceptions of ownership within marriage and social norms which may not conform to legal norms..o It is also important to ask when the asset was acquired – whether before or after marriage.o The direct benefits from the point of view of the male and female respondents) of collecting detailed personal information on asset ownership and control is difficult to justify to the respondents.o CSISA require more strategic planning. It is crucial that the leaders of CSISA objectives are responsive to gender issues.o More resources from the CSISA project should be provided to reduce the gender gaps in assets
• How CSISA interventions can impact gender inequality and empower women• Targeting women with development interventions, improving their involvement in farmer participatory experiments on crop and livestock, and post-harvest technologies.• Post harvest technologies for rice, wheat and other crops will reduce post harvest losses and provide women with income opportunities.• Promoting and validating technologies that enhance crop-livestock interactions e.g production of dual purpose crops for food and animal fodder will directly benefit women who take care of crop production and dairy animals.• Providing women with new knowledge and skills in production techniques e.g. raising nursery rice seedlings for paddy mechanical transplanter through “hands- on” training can be an opportunity for income generating activities for poor women displaced by labor-saving technologies.• Increasing women’s access to seeds of improved varieties of non-rice crops to increase cropping intensity and cropping diversification should be given more attention.• Thus, seed distribution for distribution trials and participatory experiments should include women farmers and not only give to male heads of households.• To provide women access to agricultural machinery, NGOs can help tap existing Self Help Groups to organize themselves run a microenterprise e.g. providing custom services for post harvest and processing crops or renting out an agricultural equipment or machinery. T.Paris/V.Pede th 8 Jan 2013