The Women's Empowerment in Agriculture Index (WEAI) is a new survey-based index designed to measure the empowerment, agency, and inclusion of women in the agricultural sector. The WEAI was initially developed as a tool to reflect women's empowerment that may result from the United States government's Feed the Future Initiative, which commissioned the development of the WEAI. The WEAI can also be used more generally to assess the state of empowerment and gender parity in agriculture, to identify key areas in which empowerment needs to be strengthened, and to track progress over time. The WEAI is an aggregate index, reported at the country or regional level, based on individual-level data collected by interviewing men and women within the same households. The WEAI comprises two subindexes. The first assesses the degree to which women are empowered in five domains of empowerment (5DE) in agriculture. It reflects the percentage of women who are empowered and, among those who are not, the percentage of domains in which women enjoy adequate achievements. These domains are (1) decisions about agricultural production, (2) access to and decisionmaking power about productive resources, (3) control of use of income, (4) leadership in the community, and (5) time allocation. The second subindex (the Gender Parity Index [GPI]) measures gender parity. The GPI reflects the percentage of women who are empowered or whose achievements are at least as high as the men in their households. For those households that have not achieved gender Alkire, Meinzen-Dick, Peterman, Quisumbing, Seymour and Vaz The Women's Empowerment in Agriculture Index parity, the GPI shows the empowerment gap that needs to be closed for women to reach the same level of empowerment as men. This technical paper documents the development of the WEAI and presents pilot data from Bangladesh, Guatemala, and Uganda, so that researchers and practitioners seeking to use the index in their own work would understand how the survey questionnaires were developed and piloted, how the qualitative case studies were undertaken, how the index was constructed, how various indicators were validated, and how it can be used in other settings. of the Oxford Poverty and Human Development Initiative for their valuable input to design, fieldwork, and administrative and communication components of the Women's Empowerment in Agriculture Index. In addition, we would like to thank the participants of the initial and final methods workshops as well as others who have provided helpful feedback and guidance in developing and refining results, including Michelle
Higher consumption and increased import requirements for the South Asian Association for Regional Cooperation (SAARC) region can be catered through neighboring trade partners if resources are optimally utilized. The purpose of this research is to analyze the connection between regional trade of SAARC countries and the food security challenges faced by the region. The study uses data from 1990–2018 for Pakistan, India, Sri Lanka, and Bangladesh to econometrically analyze the determinants of the volume of food trade. The results show that the gross domestic product of importing or exporting countries and foreign direct investment (FDI) have positive impact on regional trade. The bilateral exchange rate between trading partners has a negative impact on the trade volume. The results also showed the absence of a long-run relationship between volume of trade and food security using Johansen’s cointegration test. Our analysis suggests that policy makers should focus on the means for creating favorable environment in Pakistan and India to not only meet the increasing global demands for food but also increasing their competitiveness for high-quality and low-quality priced products in major exports markets.
Purpose The purpose of this paper is to measure the unidimensional and multidimensional inequality in the case of Pakistan and compare their results at the provincial as well as regional (urban and rural areas) level. The authors collected data from Pakistan Social and Living Standard Measurement and Household Integrated Economic Survey for fiscal years of 1998–1999 and 2013–2014. Design/methodology/approach The authors used Gini coefficient for unidimensional inequality and multidimensional indexing approach of Araar (2009) for multidimensional inequality. Findings The findings predicted that unidimensional inequality is relatively high in the urban area due to uneven dissemination of income, but multidimensional inequality is quite high in rural areas because of higher disparities among all dimensions. At the provincial level, Punjab has relatively high-income inequality followed by Sindh, KPK and Baluchistan. Originality/value This study is a pioneering effort to compare two time periods to explore unidimensional and multidimensional inequality in all provinces of Pakistan and their representative rural-urban regions by applying Araar and Duclos’s (2009) approach. Further, this study opens some new insights for policy makers.
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