Getting to the root of the problem: how statistics can hide women’s work


Apologies for the slight delay in getting this next post out folks… a series of holiday mishaps kept me busy for longer than expected!

In the last post we discussed the vital importance of agricultural particularly for women living in rural areas as well as the stark inequalities that women in agriculture face around the globe. These include unequal access to and use of productive assets and resources such as technology, education, improved seeds and fertiliser, and credit to invest in their land. All of this results in women’s agricultural land being on average less productive than men’s.

Another issue relates to whether or not we recognise women’s managerial capacity on the land. The above map is taken from the UNFAO’s Gender and Land Rights Database (link underneath) and shows the percentage of women that are agricultural holders in the countries for which there is data. The internationally agreed definition of an agricultural holder is “the civil or juridical person who makes the major decisions regarding resource use and exercises management control over the agricultural holding. The agricultural holder has technical and economic responsibility for the holding.”


Interpreting this map according to this definition we see that some African countries, some parts of the Middle East, and Southern Asia have the lowest percentages of female agricultural holders while parts of North America and Europe perform better.

Given that we know that agriculture is an important source of employment for women in developing countries, these numbers seem confusing… where are all the women?

The difficulty with using this indicator is that, like so many statistics, it inadvertently hides women’s work. For example, if a husband and wife manage an agricultural holding together usually the husband will be identified as the holder, regardless of the fact that his wife is also performing managerial duties.

Another challenge is the way that holdings are defined. This data is usually collected by each country through their national agricultural census. In some countries, there is a cut off point for the size of agricultural holdings that are included in the census. Because women tend to have smaller plots of land than men, this choice can disproportionately impact women. In short, it fails to count the women managing small plots as agricultural holders, it misses them altogether.

This indicator is a great example of why we should be so careful about statistics, particularly when it comes to how they represent women. It is vital to understand the exact definition of what you are looking at and to ask yourself the question “who/what is being included and who/what is being left out?”

If you follow the link above (and I highly recommend that you do!) you will also see that there are other indicators you can choose from including land ownership. A quick glance will tell you one thing… the lack of data is stark! The more I look for gender disaggregated statistics the more I am realising just how lacking they are. In the evidence based World that we are increasingly living in, the old adage What gets measured gets done, is becoming writ. If we are to create a more equal World, we have to first be able to accurately measure and understand the challenge we are up against. Currently the statistical community is neglecting to collect the most basic sex disaggregated data and continues to use gender insensitive indicators. Both are simply no longer fit for purpose or acceptable.

A ray of hope is presenting itself in the form of the Sustainable Development Goals (SDGs). The successors to the Millennium Development Goals, the SDGs set ambitious targets for countries to reach in everything from tackling climate change to creating gender equality. Importantly, they are also calling on countries to collect sex disaggregated data in all areas of their endeavours and work is underway to develop more gender sensitive indicators. This step in the right direction must be accompanied now by real action from national governments, international organisations supporting their work, and from data users who can drive demand for the data we want and need.

If you would like to read more about the importance of taking gender into account in SDG indicators, there is a great collection of resources here





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