Overview
Course Outline
Part 1: The Women's Empowerment in Agriculture Index
This course will provide participants with an introduction to the Women’s Empowerment in Agriculture Index (WEAI), the first comprehensive and standardized measure to directly measure women’s empowerment and inclusion in the agricultural sector. The course will cover the conceptual underpinnings of the WEAI, including its relevance in value chains analyses as a tool for measuring and tracking both the intended and unintended impacts of interventions on women’s empowerment. Special emphasis will be placed on practical issues including: best practices around survey design and implementation, basic construction and manipulation of WEAI data, constructing standard WEAI tables and charts, using WEAI results as a diagnostic, and communicating WEAI results to a broader audience.
At the end of this course, the participant will be able to
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Understand how and why gender issues and women’s empowerment matter for value chains analysis
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Understand how the WEAI can be used to diagnose areas of disempowerment, and monitor intended and unintended impacts of agricultural development programs on women’s empowerment
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Understand how the WEAI data is collected, and be familiar with best practices on survey implementation
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Use sample data to construct and manipulate WEAI indicators and indexes, and produce standard WEAI tables and reports
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Analyze WEAI results to improve project impacts
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Communicate findings and recommendations obtained from analysis of the WEAI data
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Relevance of gender and women’s empowerment in value chains
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Basic Stata review
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Development and timeline
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Which WEAI to use: Original WEAI, Abbreviated WEAI (A-WEAI), Project WEAI (pro-WEAI)
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Pro-WEAI for value chains projects
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Questionnaire
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Sampling
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Implementation issues and best practices
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Alkire-Foster basics
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Stata exercises
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Construct indices
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Decomposition
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Output tables and charts
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Analysis of WEAI output
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Diagnostics
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Associations between WEAI and other project objectives
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Making valid comparisons between WEAI and A-WEAI
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Communicating findings and recommendations
Part 2: Introduction to the Participatory Market Chain Approach
The Participatory Market Chain Approach (PMCA) is a flexible R&D approach that engages small farmers, market agents, researchers, and other service providers in a facilitated collective action that aims at identifying and exploiting potential business opportunities that benefit small-scale producers and other chain actors. The approach was developed by the International Potato Center (CIP) and first applied in the Andes before spreading to SSA, Asia and other parts of the world. The PMCA offers a practical way to conduct R&D that supports pro-poor innovation in agricultural market chains. The approach brings the key stakeholders in an innovation process – including farmers, market agents, researchers, and other service providers – together to jointly identify, assess and exploit new business opportunities. Through this interaction, the PMCA triggers innovation processes. Experience indicates that the PMCA is most effective when implemented as part of a multi-pronged gender responsive initiative that includes support for farmer organizations, business development, policy change, and public awareness. When the PMCA is applied with appropriate complementary measures, it can assist smallholders improve their participation in dynamic markets and improve their livelihoods.
- Understand the basic goals and principles of the PMCA
- Assess the potential value of the PMCA
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Theory and practice
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Gender mainstreaming in PMCA
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Structure and key concepts
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Previous applications and results
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Structure and key concepts
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Useful tools
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PMCA SWOT Analysis I: Assess 2 or 3 market chains of interest
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SWOT Analysis II: Assess Potential impact of PMCA
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Creating an enabling framework for gender responsive PMCA application
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Developing Action Plans
Pre-Requisites
Knowledge of Stata is required. Participants should have a background in quantitative analysis, and a familiarity with gender issues in agriculture is preferred.
APPLICATION
In order to apply for this course, AGRODEP members must complete the following by February 25, 2016:
If you would like to practice using Stata before taking the proficiency test, please review the modules below. Information included covers Stata use for beginners, linear regressions, bivariate regressions, and panel data. You will need to know this information to successfully complete the test.