The Results May Surprise You: Analyzing Sex-Disaggregated Data.

Quisumbing discusses how to conduct a gender analysis if you have a limited data set. Quisumbing argues that there are many different gender analyses that researchers can conduct, even with a limited data set. These include using sex of household head to determine whether women-headed households are more likely to lower food consumption in the instance of an unexpected negative event, or ‰ÛÏshock.‰Û She also describes how you can analyze data that is a bit more extensive, including examining the differential impact of parental characteristics by child gender. Quisumbing's article includes a number of different examples of these types of data analysis. Overall, her main point suggests that, if possible, researchers should collect the best sex-disaggregated data that they can; however, even if their sex-disaggregated data is not perfect, they still may be able to conduct some basic yet interesting analysis. While not a how-to-guide, the piece provides gender analysis examples and ideas on what to do with quantitative data on gender (or data that does not directly address gender).

Quisumbing, A. 2014. The Results May Surprise You: Analyzing Sex-Disaggregated Data. Washington, D.C.: IFRPI.
Media Type: 
Working Paper
Geographic Focus: 

Latest Updates