A post – project impact assessment CARE UK October 2011 Reducing poverty and promoting women empowerment through market development in the southern Andean highlands of Peru A post – project impact assessment CARE UK October 2011

Why did CARE Peru work with rural communities in Puno? Poverty levels: sample of 200 households in 2006 reported: 87% living below the poverty line and 60% below the extreme poverty line. 30% of children under 5 in region suffer chronic malnutrition

Why did CARE Peru engage with the cattle Value Chain? Outreach: Cattle raising is the main economic activity in the area for smallholders (60% of total income in 2005) Economic Potential: Puno produced 19% of the cattle sold in Lima and 53% of the cattle commercialized in Arequipa Market opportunity: unsatisfied national market demand of 8.3% (or 61,700 cattle heads per year), which could be targeted by Puno producers

Puno Beef Cattle Value Chain Organic market Conventional market District Markets and Supermarkets Enabling environment: policies, labour gender division, legislation, physical conditions, climate change adaptation Merchants and cold houses Lima and Arequipa / other Slaughter Houses Import market Private Input providers Cattle raisers’ associations producing fully fattened bulls Farmers in southern Peru who terminate to fatten the animals Transportation services Financial Institutions Interest groups Interest groups Middle men Private vet. services Private Technical Assistance providers Smallholdersc Smallholders Smallholders Smallholders Smallholders selling semi-fattened bulls Women project beneficiaries Association Commercial, relationship

Main VC strengths Bottlenecks Strength: smallholders represent the vast majority of the cattle value chain Weaknesses: Low productivity / poor economic results Access to higher value markets: cattle not fully fattened sold to middlemen making most of the profit taking from 8-12 months to fatten a cow for market. Average family income from beef production in 2005 was around 1,600 new soles per year (around 350 GB£/year or 29.3 GB£/month

Project objectives Increase the income (by 25%) and employment opportunities (143,627 new daily positions) for 2,550 poor families through fattening and commercialization of beef cattle Develop technical and productive capacities for 2,550 families within the beef cattle value chain.

Project components (Fondoempleo 2005 – 2008) Improving productive and Business Management capacities Improving organizational capacity of the producers Creation of a local market for technical assistance providers (PATs) Promotion and facilitation of partnerships with the public sector and private sector Interest groups, federated at higher level, learning exchanges,

Project methodology / gender The semi-intensive bull fattening methodology permitted the involvement of women (close to home) Active promotion of the role of women in economic activities including commercialization, producers associations / public life Work on masculinities Interest groups, federated at higher level, learning exchanges,

The external impact evaluation Objectives: To generate the necessary evidence to validate this specific initiative and its strategy as an effective rural development model for the Peruvian highlands. Use the results of this study as an evidence based advocacy tool with the Peruvian Government General project information: 9 months project, worth approximately US$ 31,500, funded by PPA3, in partnership with the IEP (Institute for Peruvian Studies), coordinated in CARE Peru by Claudia Sanchez, M&E Director.

What kind of evidence were we looking for? (Quantitative) Household composition Total annual cost composition (average) Unsatisfied Basic Needs in the families Per capita annual cost in households Annual Income and expenditures individual and by house holds, by quintiles and deciles Incidence of poverty and extreme poverty, poverty gap, poverty severity (squared poverty gap) Income distribution by quintiles Gini Coefficient % of people with caloric deficiency Agriculture and cattle sales Gross Value of Production Total income per household Composition of production (agriculture, cattle, forestry)

What kind of evidence were we looking for? (Qualitative) Qualitative evidence around individuals (men and women) Empowerment level, happiness, dignity, self confidence The main successful strategy adopted by the project, leading to these impacts Application of CARE’s programmatic principles Project sustainability

Methodology (key elements) Multidimensional approach to poverty measurement (OPHI methodology, IDB methodology) Surveys based on the ENAHO methodology (National Households Survey) in Peru. Interviews with focal groups Baseline for the control group built using secondary information, as it was not included in the baseline In Partnership with the IEP (Institute for Peruvian Studies)

Main Results of the impact assessment The analysis shows a statistically significant increase of net incomes of almost 100% compared with the baseline

Main Results (continues) 64% decrease in poverty incidence from 81% to 29% during the past 5 years (51% difference). The percentage of people able to make savings is significantly larger in the treatment group (27.8%) than in the control group (7.5%) The % of people reporting that they are living well or very well is significantly higher in the treatment group (32.4% vs. 16.7%) Measured on expenditures, according to the national methodology

Most important tool and most relevant impact

Men and Women most important changes Women Important changes Men important chenges Place New skills, education for the children Better family relationships More participation in public spaces Better economic conditions New knowledge Giving value to the cattle raising Huayrapata New learning, education for the children More equality within the family More leadership in the community New incomes generation New knowledge Overcoming poverty Huancané Source: Focal groups CARE / IEP

What is power? How do you define having power? (examples of answers and perceptions obtained during the evaluation) Examples from women: ”She is somebody very clever, well trained. It is good that she has power in order to care for her community, in order for the other women to be well as well (…) They respect her at home, treated by her husband as an equal” Examples from men: in the case of man power is mainly related to having formal power, to be in a power position. A man with power is somebody “who knows how to lead, who is or has been municipal authority or mayor or manager”. Beyond this, somebody who is in a dominant power position at home. Some of them mention that “there is always a chief of the family”, they are the persons who traditionally hold that position and need to do it well.

Women and men empowerment – differences in perceptions Empowerment for men: more power inside the community Empowerment for women: more autonomy and decision power

Other benefits linked to the project Better use of technology in agriculture improving productivity and quality Through the associations, access to tractors and other machines Benefit of associations, formalized associations

Elements of happiness for women More autonomy in the cattle activity Participation in commercialization, questioning the gender division of Labour Refusal of macho attitudes of men who do not value their role in the family New knowledge, skills Capacity of managing part or the totality of new incomes gives more autonomy

Elements of happiness for men Improvement in the economic results from cattle raising Improvement in the results from the direct commercialization Interacting with urban markets in Lima and Arequipa Exchanges of experiences in other countries (Chile and Guatemala)

Suggestions from CARE Peru for future impact evaluations Clearly define the objectives: what we want to measure Importance of the reflexions and learning process generated by the evaluation. It is a tool and not an end in itself Use of rigorous processes and recognized methodologies at national and international level, partnership with well respected research institutions. Think about the responsibility that we have in scaling up models that work rather than risky or failing models as this involve the lives of many people Need to follow up with the institutions responsible for scaling up the successful models in order to be properly implemented. The document is not sufficient in itself