Bilateral Aid in support of Gender Equality and Women’s Empowerment in South Asia
Sanna Bedi
I will be taking 2nd module
Background: According to the International Labour Organisation, ‘gender equality is considered a critical element in achieving decent work for all women and men, in order to effect social and institutional change that leads to sustainable development with equity and growth. Gender equality refers to equal rights, responsibilities and opportunities that all persons should enjoy, regardless of whether one is born male or female.(1)
The South Asia region comprises eight countries, including Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka. Critical of the development of the region are the women who hold more than 50 percent of total population. However, women and girls in South Asia are severely suffering from rampant gender based violence, and discrimination in education, nutrition, health and employment paralysing their empowerment and disrupting gender equality. Gender equality is an essential indicator for advancing development and reducing poverty. In order to achieve sustainable development, issues of women’s empowerment and gender equality need to be addressed urgent.
Over the past few decades there is a greater recognition of such issue. Official development aid focused on gender equality has tripled from USD 8 billion in 2002 to USD 24 billion in 2012.(2) An analysis of the past two decades reveals the crucial role of the Millennium Development Goals in channelising foreign aid towards issues like women’s education and health. Goal 5 of the Sustainable Development Goals is aimed at achieving Gender Equality and Women’s Empowerment for all women and girls and all other goals have gender sensitive features.
Given the prevailing conditions, an understanding of the key countries providing development aid for specific gender related issues to South Asia will be of immense value. Further, a comparison of the foreign aid received and the gender inequality index can provide a context for optimum allocation of aid.
Primary Guiding Question: Which countries are most likely to invest in specific gender projects in the South Asian Region?
Secondary Questions: Which countries provide maximum aid for gender equality and women’s empowerment to each of the South Asian countries? And which sectors within gender equality and women’s empowerment receives the maximum aid w.r.t. to each of the South Asian countries?
What is the co-relation between the gender-inequality index and the aid-recipient country?
Hypothesis: There are specific countries that are more likely to provide aid to the South Asian region. I believe that different countries provide aid for different sector specific issues within gender equality and women’s empowerment. Some countries are more likely to provide aid for more controversial issues like women’s abortion rights. Sector specific aid could provide a context of policies affecting donor decisions. Furthermore, I predict that certain countries in South Asia receive more than others ranked lower the gender inequality index, simply because of their bilateral relationships.
Data and Methodology: The research will begin by constructing a dataset of all countries that provide development aid to South Asian counties. The aid provided will be classified at three levels to include 1) aid that was not targeted to gender related issues, 2) aid that has a significant target to gender related issues, and 3) principal target of aid was to address gender related issues. Aid provided between 2010-2015 will be assessed. The data is readily available from public reports by donor countries and international organisation tracking development aid.
The attribute dataset can be expanded to include specific sectors within gender equality and women’s empowerment, scale of the aid provided and the duration of the project. The two-mode dataset of aid-recipients and aid-provider can be further analysed as one-mode matrices. Then, a review of the sector specific aid provided to each of the countries can be studied. Analysing the aid provided over a period of five years can indicate a change in sectors to which aid is provided.
Finally, the use of a second data set of the gender inequality index can be added to increase the scope of analysis. This will help develop co-relations with the countries that need most aid versus those that actually receive more aid. At this stage, a deeper dive on the duration of aid provided to a country can help understand the sustainability of the aid being received.
Centrality measures will be important to assess countries receiving sector specific aid. Any formation of cliques based on issues will reveal the most crucial issues that receive aid in the region and can be compared to critical issues actually effecting each country. Cohesion measures could be helpful in revealing information of the likelihood of donors providing aid to a country to belong to the same region or countries competing to forge stronger relations with or influence on the aid-recipient.
Conclusions: The social network analysis will help in creating a go-to list to know which countries are most likely to invest in specific gender projects in the South Asian Region. Trends can be observed about factors that influence a countries likelihood to provide aid to a specific country.
Sources: Previous SNA work on this question was not identified.
(1) ILO, ABC of Women Worker’s Rights and Gender Equality. 2000.
(2)https://europa.eu/eyd2015/en/eu-european-parliament/posts/economic-and-political-discrimination-undermines-womens-opportunity
1 comment:
The concept is really interesting and worthwhile, however, there is still some work to be done to make it a doable SNA project. First, you need to be clearer about how an SNA will help identify the countries that are “most likely” to invest in gender projects. Using the data you present, which SNA measures are the ones that you will use to answer the Question? Second, I’m not sure whether you’re talking about network effects or simply correlation between providers and recipients, by type. For instance, you could use SNA to find things like countries that are co-donors to recipients, based on the different types. And, even if you do, I’d need to be convinced as to how this would provide indicators of likeliness to invest in gender projects.
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