Many agricultural programs aim at reducing gender inequalities in the use and control of resources. To measure the impact of the programs and to identify the gender gaps, researchers and practitioners are currently using a myriad of different measurements and indicators. Policy and guidance on the choice of simple and robust indicators is highly needed, and in this blog, economist Smriti Rao discusses her work on this topic.
As a feminist economist who researches gender inequality in developing countries, I have spent my career torn between the recognition that quantitative measures can be useful and informative, and disappointment with the loss of nuance and complexity when quantitative measures are the only source of data used.
Writing a paper that recommends a list of quantitative indicators to measure gender gaps in agricultural resources brought out all of these contradictions. Suggesting indicators that are insightful without being reductive, or too resource intensive to construct, can seem like an impossible task. Even if the balance is right, the indicators can be misused by agencies under pressure to generate and use a single number.
After the completion of the paper, I am still not certain each and every recommended indicator gets that balance exactly right. The paper reflects this uncertainty by being self-critical about the indicators and providing a table of possible weaknesses of the recommended indicators. And some part of me remains skeptical about whether such indicators can ever be complex enough to do more good than harm. For me personally, the most rewarding aspect was coming up with a set of conceptual criteria to guide the choice of indicators. The paper is explicit about the tradeoffs involved in picking one criterion over another. Readers can thus take their own positions on the criteria and critique not just the particular recommended indicators, which leads to a somewhat limited discussion, but rather their conceptual bases and the assumptions embedded in them. It would be interesting to engage in such a discussion with readers of this blog.
One of the criteria I am most confident about, however, is also one that many development agencies may find especially inconvenient to adopt. The paper urges that we move away from data based on household ‘heads’, and critiques research that treats the comparison of ‘male-headed’ households with ‘female-headed’ households as an adequate gender analysis. I am quite convinced that focusing on female-headed households a) covers only a tiny fraction of women, given that the vast majority of women live in non-female headed household and b) confuses households with single men (divorced, widowed or otherwise) with those that include a principal couple and is thus conceptually unclear. In fact, most households are ‘dual-headed’, with only a small percentage being single-headed and thus either male or female headed. As an accommodation to the resource intensity of trying to survey both members of the principal couple in a household, the paper suggests a model where only one person from each household is interviewed, but the sample design ensures the inclusion of female as well as male respondents. This is a compromise, but one that allows to move towards a richer understanding gender gaps in resource use and control.
Of course, measuring a gender gap does not by itself help us understand why the gender gaps exist, or the extent to which a change in the gender gap is linked to the particular agricultural innovation project. Knowing that there is a gender gap in the planting of trees requires an additional research project to understand why such a gap exists. On the other hand, without someone noticing this gap and documenting it, such follow up research is unlikely to emerge.
An important goal of the paper was also to recommend indicators that could be measured at the national level and thus feasibly constructed for international comparisons. However, sex-disaggregated data at the national level is largely missing because much of the current research is conducted at the household level. International indicators also make the field researcher in me anxious – as we move away from the specificity of local contexts how useful can our measures be? The paper acknowledges the issue of context-specificity by pointing out the weaknesses of some indicators in this regard. However, the advantage of having widely available international data on gender gaps may give rise to better informed additional research. This is simply because a comparison of trends in different countries often helps to point out places where gender gaps do not exist. Without this kind of data, our ability to understand the effectiveness of agricultural projects in reducing gender inequality will remain limited.
Smriti Rao is Associate Professor of Economics and Global Studies at Assumption College, MA and Resident Scholar at the Women’s Studies Research Center, Brandeis University, MA. She is a development economist who studies the causes and consequences of gender and economic inequality in labor and credit markets. She has a particular interest in rural, agrarian economies, with a regional focus on India, where she has conducted fieldwork. She teaches courses on Development, International Trade and Finance, and the Economic Systems of China and India. She received her Master’s and PhD in economics from the University of Massachusetts, Amherst. She received her bachelor’s degree from the Birla Institute of Technology and Science, Pilani, India.
Rao, S. 2016. Indicators of gendered control over agricultural resources: A guide for agricultural policy and research. Working Paper No. 1. CGIAR Gender and Agriculture Research Network, CGIAR Consortium Office and International Center for Tropical Agriculture (CIAT). Cali, Colombia. 74 p