How to Lie With Statistics, Women and Child Care Edition

By , 3 August, 2012, No Comment

My latest post is up at Forbes, highlighting two research papers that look at the impact women’s earnings and the cost of child care have on women’s decisions on whether to have children and whether (or how much) to work. They are good papers, but they both make a critical error:

Both papers assume that men commit full-time to the labor force, and that the choices families are about the balance of women’s working hours and caring hours. It’s one of the most infuriating aspects of the work-life debates that the choice is so often framed that way. The reality is that in addition to earning potential and cost of child care, the degree to which male partners share in child care duties is a major factor driving women’s career and family choices.

Leaving working fathers out of the choice equation tarnishes the studies’ results, and can have a dangerous effect, if policymakers feel that the solution suggested by papers like these is to expand the choices available to women without expanding choices for men. Framing the work-life conundrum as a women’s issue only makes it more likely that it will remain women’s burden. The research error becomes self-fulfilling.

This case is a perfect example of the problem outlined by Darrell Huff in his classic book, How to Lie With Statistics. I’m a great advocate for inserting more data into debates about work and family, but it’s equally important to be skeptical of the data presented to us. Ask not just, ‘Does this data answer the question we’re asking?’ but also, ‘Are we asking the right questions?’ At the moment, I’m not convinced we are.

Read it all here.

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