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Gender agriculture & climate change. What we need to know
 

Gender agriculture & climate change. What we need to know

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  • WEAI index developed by IFPRI gender researchers; we’re in process of reviewing to adapt to climate changeIn any analysis involving gender, basic information: resources (assets + others), who makes decisions, who provides labor all of these impacted by climate change, whether shock, or more long termWe want to be in a position to analyze impact of CCAFS interventions on adaptation (bottom part of graph is l-t) -crucial impact to choosing intervention: preferences by gender; these shaped by resources, decision-making, labor + other other factorsShort term: upper part of graph – shocks, coping strategies, also lead to lt adaptationAssume both lead to changes in position of men & women Key analitical question: what does our summary stat look like?Policy in a little box: could impact each pt. of process: impact on initial distribution of resources, impact on choice of interventions, also effect outcomes
  • Beans: CIAT mandate; healthy food item (source of protein), ecologically bening (fix nitrates) Water issues impt. both to production and consumption (need to soak beans adequately & to cook), links HH needs to production Source of fuel crucial to cooking
  • See fairly broad range, from low 8% Guatemala to high of 30% in Chile in 2000sFew have data for 2 pts. in time – time trend not consistent Chile, marked increase, slight increase in Guatemala; Decreases in DR, PeruProblem: changes in definition of landholderColombia has not published disaggregated data (if collect); keep eye on Ecuador, since will be interrogating
  • Most useful measure: parcels level so can consider joint ownership.Besides LSMS, include Ecuador and results of Household Asset Survey, where we were very careful to seek out joint owners - here jt. ownership includes by couple, by 2 HH members, by a HH member with someone elseJoint ownership could be a major source of under-estimation of women’s property ownership Among the many reasons important to go beyond HH head
  • 5 countries, here if a jt. Owner, distribute to men & women de un 13% en Honduras a 32% en Mexico
  • All comparative slides from GAG project are for Rural, some differences (Uganda not tech part of project, not natl. representative) (Ecuador, urban more egalitarian than rural)Here we break out joint, to highlight jt. ownership by couple vs. other forms of jt. (all in the family)Strong male bias in India, GhanaUganda, jt. ownership reported more frequently than Ecuador
  • Incidence tells us much about landlessnessHere compare reported owners with whose name appears on documents
  • Regression results; * levels of significance
  • Hay diferencias de generobienimportantessegun el tipo de activo.No essuficientepreguntarsobre “los animales” en forma generica
  • Africa: meaning of ownership – bundle of property rights
  • Problems: Ask about ownership of parcels at individual level; but decisions at level of household (male HH heads) Would conclude on basis of this data that women not involved in decision over own parcels - erroneous
  • Asked husband and wifely separatelyFocus on wives’ responsesReferred to the last 12 monthsCould report up to 2 peopleAlso asked:Who in the household works on the plot?Who makes the sale?
  • Garcia Rovira crops: tobacco, cornCajamarca: potatoes, corn, wheat, barley
  • See variation depending on task
  • Rural hours worked for women always higher, and female/male gap is larger
  • Important to consider how Land Acquired
  • Reducing vulnerability is matter of risk management; women’s greater aversion to risk = increased willingness to take costly measure to minimize climate risksCC ckt by high uncertainty; if can envision wider range of potential outcomes, can adopt adaptation strategy more robust to occurences of extreme eventsMust go beyond personal experience; need to listen to advice to apply scientific info successfullyReducing vulnerability requires adaptive mgt, experiementing, learning from successes and failure; more successfully if can change in response to new information.

Gender agriculture & climate change. What we need to know Gender agriculture & climate change. What we need to know Presentation Transcript

  • GENDER, AGRICULTURE& CLIMATE CHANGE:WHAT WE NEED TOKNOWCarmen Diana DeereUniversity of FloridaPresentation at CIAT/CCAFS, Cali, September 3, 2012
  • Basic Propositions1. Men & women may have different exposure and vulnerability to climate change2. Have different capabilities to deal with climate change, hence, different needs and perspectives3. Different factors may affect men‟s and women‟s levels of participation in adaptation and mitigation strategies4. Alternative policy instruments/interventions can have different gender impacts
  • Strategic Gender Research Key Question: How does climate change and/or climate change interventions impact women‟s empowerment in agriculture (WEAI) Climate Shock/ Coping  Adaptation Variability New WEAIBaseline WEAI CCAFS • Resources• Resources Intervention(s) • Decisions• Decisions • Gender division of• Gender division of labor labor Climate Planned ---- Adaptation Change Qualitative research on Policy preferences by gender Change in WEAI = New WEAI – Baseline WEAI
  • Gender & Climate Change InterventionsFrom Basic Principle: “Do no harm” • i.e., avoid interventions that exacerbate gender & social inequalities, deepen povertyTo End Goal: transformative change = genderjustice • Utilize both men and women‟s knowledge & agency • May be precondition for resilience
  • PresentationData requirements: what we need to know 1. Distribution of ownership & control over resources 2. How decisions are made & by whom 3. Gender division of labor (production & reproduction)Illustrate with examples from: • Latin America • Agricultural censuses • LSMS surveys • Gender Asset Gap project (Ecuador, Ghana & India) • Representative household surveys at national/state levelMain point: • Resources, decisions, gender division of labor are variables • Socially constructed; vary in time and place
  • Gender disaggregated data provide thebuilding blocks to assess:• Who affected by climate change? • Who made worse/better off• The needs/priorities of men and women, given gender roles• The changes implied by adaptation strategies • Responsibilities, work loads, participation
  • Resources• Land*• Inputs• Ag equipment*• Livestock*• Water• Credit• Education• Information• Organization (groups, networks)
  • 1. Distribution of Land by Sexin Latin AmericaAgricultural Censuses• Don‟t ask who owns the land• Focus is on „landholder‟ or main agriculturalist• Too often end up with household head• Doesn‟t take into account that farm management might be shared by husband & wife, or that they might manage different agricultural activities (crops vs. livestock)
  • Distribution of Landholders by Sex, Agricultural Censuses for Latin AmericaCountry Year % Women % Men TotalArgentina 2002 18.2 81.8 100%Brazil 2006 12.7 87.3 100%Chile 1997 21.9 78.3 100% 2007 29.9 70.1 100%Dominican 1960 11.4 88.6 100%Rep. 1998 10.2 89.8 100%Ecuador 2000 25.4 74.6 100%Guatemala 1979 6.6 93.4 100% 2003 7.8 92.2 100%Nicaragua 2001 18.1 81.9 100%Paraguay 1991 9.4 90.6 100%Panama 2001 29.3 70.7 100%Peru 1972 13.3 86.7 100% 1998 10.2 89.8 100%Uruguay 2000 18.1 81.9 100% Source: Deere 2010
  • Advances2010 round of Agricultural Censuses • Will now allow for joint landholders and sub-holders • Still don‟t ask about land ownershipMain benefit: • Sometimes can get disaggregated information (department/province/municipality) • Notwithstanding shortcomings of data, relevant to consider for CCAFS baseline sites
  • SurveysLiving Standard Measurement Studies (LSMS) • A few have begun to ask: Who owns the land? • Useful in comparing countriesProblems:• Can not always disaggregate beyond rural/urban or departmental/provincial level• Comparability: • Some surveys only ask about titled land (*), not all owned parcels • Not all ask about joint ownership of land
  • Distribution of Parcels by Formof Ownership, Latin America Country Year % Women % Men % Joint Total Honduras 2004 12.0 87.2 0.8 100%* 280,088 Mexico 2002 19.8 66.3 13.9 100% 4.9 m. Nicaragua 2005 16.8 79.2 4.0 100%* 269,231 Peru 2000 12.6 74.8 12.6 100%* 2.9 m. * Titled land only Source: Deere, Alvarado & Twyman 2012
  • Distribution of Landowners by Sex, Latin America 100 90 80 70 60% 50 40 Men 30 Women 20 10 0 Haiti Honduras Mexico Nicaragua Paraguay 2001 2004* 2002a 2005* 2000* *Includes only land that is titled/registered Source: Deere, Alvarado & Twyman, 2012
  • Distribution of Parcels by Form of Ownership, Rural 80% 71% 69% 70% 60% 52% 50% 40% 40% 30% 26% 25% 26% 25% 20% 18% 14% 12% 9% 10% 4% 4% 2% 2% 0% INDIA GHANA ECUADOR UGANDA Individual Male Individual Female Principle Couple Other Source: Household Asset Surveys, in Doss et al 2012
  • Incidence of Ownership of AgriculturalParcels, Reported vs. Documented ownership (rural)45%40%35%30%25%20% Male Female15%10%5%0% India Ghana Ecuador Uganda India Ghana Ecuador Uganda Agricultural Land Agricultural Land, with documents
  • What data on land ownership tells us:• Degree of gender inequality• Women‟s security of tenure o Vulnerability in the face of adversity• Whether women will be able to use land as collateral to get credit o Might be required to adopt climate resistant varieties• Whether women are treated as „serious farmers‟ by state agentsWomen‟s ownership of land may also affect theirhousehold‟s well-being
  • Impact of Different Gender Variables onHousehold Wellbeing Honduras NicaraguaFood ExpenditureFemale land ownership pos*** pos***Female headship neg*** neg***Female income pos*** negChildren’s Schooling AttainmentFemale land ownership pos*** pos***Female headship neg*** neg*** Source: Katz & Chamorro (2003)
  • Incidence of Ownership of SmallAgricultural Equipment (rural)90%80%70%60%50%40% Male Female30%20%10%0% INDIA GHANA ECUADOR UGANDA AG EQUIP, SMALL
  • Who in the Household Owns the Livestock? Nicaragua 2001 90 80 70 60 50 Men% 40 Women Couples 30 20 10 0 Cattle Work animals Pigs Poultry Source: Deere, Alvarado & Twyman (2012)
  • 2. Ownership and Control over LandEffective land rights: • Legal rights (ability to use, impede others from using without permission, ability to transfer rights to others) • Social recognition of these rightsControl: • Capacity to decide on how to use land • Ability to decide how products/income generated are to be utilized
  • Distribution of Owners and Decision Makers amongLand-owning Households Variable % Women % Men % Joint Total HONDURAS Owners 12.1 86.3 1.6 100% 227,769 Decision 8.7 91.3 - 100% Makers NICARAGUA Owners 16.9 79.0 4.1 100% 160,084 Decision 8.8 91.2 - 100% Makers Source: Deere, Alvarado & Twyman (2012)
  • Implications1. Comparison problematic: different units of analysis • Asked about ownership at parcel level • But asked about decision-making at level of farm/household (likely to reflect household head) • Didn‟t ask about joint decision-making2. Can‟t assume the owner makes the decisions regarding the asset3. Decision-making (or landholder) not necessarily a good proxy for ownership**Importance of collecting data on both ownership & decision-making at parcel level**
  • Ecuador 2010 Assets Survey:Agricultural Decision Questions• Minimum questions to • Who in the household made the decision on what to ask landowners cultivate?• Decisions on own • Who made the decision on what inputs to use? plots which are • If some of the harvest was currently cultivated by sold, who made the decision the household (last 12 on how much to sell? • Who decided how to spend months) the money generated from the• Women‟s responses sale?
  • Decisions by Partnered WomenLandowners over Own Parcels (%)How Cultivation Inputs Sales SpendingMade:Alone 18 23 15 23Jointly 60 48 61 71Not 22 29 24 6involved 100 100 100 100 (n=228) (n=164) (n=115) (n=115) Source: Deere & Twyman (2012)
  • Main conclusions of Ecuador study• Majority of women landowners in Ecuador are farm managers: participate in the agricultural decisions regarding their own plots• Husbands‟ and wives‟ perceptions of women‟s role in ag decision-making differs• Women‟s participation in decision-making highly correlated with their participation in ag fieldwork, alone or with husbands• Participation in decision-making highly associated with women landowners also owning agricultural equipment jointly with husbands (Sources: Deere & Twyman (2012), Twyman (2012)
  • 3. Gender Division of LaborType of gender disaggregated information thatwould be useful: • Data on agricultural field work by task and crop and on animal raising activities • Data on domestic labor, particularly, on hours spent collecting water, fuel & fodder • Data on all productive & reproductive activities (total workload)
  • Share of Smallholder Households whereat least One Woman ParticipatesActivity García Rovira, Cajamarca, Peru ColombiaAg field work 18% 85%Ag processing 53% 100%Ag services 95% 61%Animal care 88% 95%Marketing 24% 88%Weighted average 40% (n=114) 86% (n=92) Source: Deere & León (1982)
  • Participation rates in agricultural fieldtasks by sex (13 yrs.+) Task García Cajamarca Rovira Women Men Women Men Field prep. 10% 89% 24% 74% Seedling prep. 29% 91% Na Na Planting 30% 93% 48% 74% Transplanting 7% 93% Na Na Weeding 4% 93% 47% 80% Cultivating 4% 93% 24% 79% Harvesting 46% 94% 62% 81% Threshing Na Na 66% 83% All activities 25% 93% 45% 78% (weighted) Source: Deere & León (1982)
  • Who in the Household is Responsible?Smallholders in Cajamarca, PeruTask % Wife % Husband % Joint Total nSeed 59 7 34 100% 104selectionCollects 13 54 33 100% 92manure &fertilizesPurchases 3 53 44 100% 34seed orfertilizerDecides 15 47 38 100% 104where, whatand when toplantGets non- 7 79 14 100% 94householdlaborCoordinates 6 49 45 100% 98field workDecides how 56 7 37 100% 93harvest to beusedDecides on 36 16 48 100% 77crop salesDecides on 39 11 41 100% 86animal sales Source: Deere & León (1982)
  • Total Workloads by Sex (hrs. per week) Colombia (2008) Ecuador (2007) Women Men Women MenUnpaid 60.8 33.0 Unpaid 67.1 39.1Paid 42.4 50.4 Paid 40.3 48.1Total 103.2 83.4 Total 107.5 87.2 Source: ECLAC (2010), based on national surveys
  • Other Crucial Questions: Food security,water and energy• Need to know about water access: rainfed/irrigation and how water secured for domestic use - potential differences by gender for agriculture, livestock, household use• Need to know about energy sources: access to electricity, sources of fuel• Need to know about animal feed/fodder
  • What this type of information allows:Assess whether women more vulnerable toclimate change • Whether workloads will increase • More likely to lose access to resources • Less likely to be able to mobilize resources under conditions of adversityProvides means to evaluate potential impact ofdifferent interventions on current gender roles
  • Factors that Affect Participation of Men &Women in Adaptive Strategies• Access to information• Degree of organization• Gender roles • Women have less mobility than men • Lower rates of participation in groups/community • Women more time constrainedEvidence from behavioral studies: • High pay-off from organizing women as well as men to identify & carry out adaptive/mitigation strategies
  • In Conclusion• Involving both men and women potentially a win- win proposition for adaptation strategies• Challenge of making sure adaptation strategies also a win-win proposition for women• To be able to assess these propositions: • Need gender disaggregated data
  • Incidence of Ownership of Livestock, rural70%60%50%40%30% Male Female20%10%0% INDIA INDIA INDIA GHANA UGANDA GHANA UGANDA GHANA UGANDA ECUADOR ECUADOR ECUADOR LIVESTOCK, LARGE LIVESTOCK, SMALL POULTRY
  • Distribution of Modes of Acquisition of Agricultural Land, by sex, rural100.0%90.0%80.0%70.0%60.0%50.0% Inheritance/gift40.0% Market purchase Other30.0%20.0%10.0% 0.0% men women men women men women men women INDIA GHANA ECUADOR UGANDA Source: Doss et al 2012
  • Adaptive BehaviorPropositions from behavioral studies1. Women more risk averse than men2. Women less overconfident than men3. Women seek out help and listen to advice4. Women change their strategies in response to new information (Source: Patt, Dazé, Suarez 2009)