More than 30 years ago, the late development economist Mahbub Ul-Haq summarized progress on global women’s issues as a story of ‘expanding capabilities and restricted opportunities.’ This motto still applies today, with one very important difference: major advancements in research now provide the evidence to do something about it. And this something may not be as daunting a task or require as many resources as previously thought. The assumption has been that targeted investments increase women’s capabilities and then women change the world. While increasing women’s capabilities is still paramount, especially in situations where there are glaring gender gaps, novel and oftentimes minor changes in working and living environments can unlock opportunities for women—and with far fewer demands placed on them.

This emphasis is reflected in the ‘smart design’ that we advocate in our new report, Revisiting What Works: Women, Economic Empowerment and Smart Design. The report builds upon previous work done by the UN Foundation and the ExxonMobil Foundation on what works to promote women’s economic empowerment for whom, and how to effectively measure impact.

Here are some of our key takeaways—the good, the bad, and the way forward:

The Good:

  • A lot of rigorous new evidence: The amount of evidence on interventions with the potential to empower women economically has grown exponentially; to the original Roadmap database of 136 studies, we added 96 studies published since 2013 alone. New evidence has made findings on what works—and what doesn’t—increasingly generalizable, so we can feel more confident about where we should make investments to improve women’s economic outcomes.
  • Uncovering the ‘how’: This new evidence also allows us to say more about how particular interventions result in economic benefits, by providing insight into the direct, intermediate, and final outcomes they lead to. One example is access to individual (private) secure savings accounts, which allows women entrepreneurs to better accumulate savings for business investments, increase their economic self-reliance, and in turn increase their business sales and profits.
A casual chain for savings


The Bad:

  • Gender-biased productive services: While it may not be immediately obvious (and so goes unrecognized), the evidence shows that service provision in the productive sectors is often biased against women. From agricultural extension services “better attuned to the needs of male farmers,” to companies—when legally mandated to provide childcare—penalizing female employees by paying them lower wages, to training providers, who favor young male trainees over young female trainees, it’s clear that we will have to acknowledge and correct  gender-biases in order to level the playing field for women in the workforce.
  • Gender-blind analysis—still: While women and young women are main protagonists in most of the evaluation studies we reviewed, researchers focused on determining what works to advance economic outcomes of the poor often stay at the level of the household and fail to acknowledge that gender may be an important variable influencing results. Findings that may be explainable by the clients’ gender, such as savings having greater benefits for those who are less empowered or more socially exposed to outside pressures (guess who?), are sometimes ignored as gender-related findings in studies where the majority of those in the sample are female.

    Unfortunately, we often felt like we were playing the ‘gender lens’ detective when reviewing studies while this should no longer be the case for otherwise high quality, sound research. We had a similar problem determining what the term ‘female head of household’ meant in a number of studies. The term was often ambiguously defined and sometimes seemed to refer to the primary adult woman in the household, rather than the more accepted definition of that person who other members in the household identify as the head.

The Way Forward:

  • One size does not fit all: From both an implementation and a research standpoint, we have to stop assuming that there is a ‘standard’ or ‘neutral’ beneficiary to target. Interventions need to be tailored to meet women’s specific needs, which means taking into account gender-specific constraints on time and mobility, women’s higher share of unpaid domestic and care work, and a system of productive services that may often be gender-biased.
  • Women are not all the same, and the very poor need more: Women of different income levels, ages, geographic contexts, and in different sectors require interventions relevant to their circumstances—for example, a very poor woman farmer is unlikely to benefit from a cash grant (even large) in isolation, whereas the same grant may be all that’s required to jumpstart a non-poor urban entrepreneur’s business.
  • Acknowledge and correct gender bias through smart design: The good news going forward is that many aspects of ‘smart design,’ which take into account and mitigate gender constraints and biases, should be fairly low-cost and easy to implement. Simply adjusting program schedules and providing stipends for travel and child care can increase’s women’s participation significantly, while nudges, mental labels, commitment devices and peer support can all play a role in fostering women’s economic self-reliance. There is also some evidence that small incentives to service providers—for instance, agricultural extension agents—helps to overcome their gender biases affecting service provision, and implementers should think creatively about these types of scalable ‘smart design’ approaches.
  • Pay attention to subjective dimensions of economic empowerment. The new evidence points to the importance of subjective dimensions of economic empowerment—from economic self-reliance and self-confidence to greater risk-taking—for lasting economic gains. In a forthcoming blog post, we will discuss how these subjective outcomes of interest can be accurately defined and measured.

We’ve learned that what seems neutral is often biased: when trainings take place far from a village or during the day, women are less likely to attend, due to increased constraints on their time and mobility as primary caretakers. When access to capital requires proof of ID and collateral, women are less likely to be able to take out loans to grow their businesses. Changing women is not the only way forward; we have to think about changing the biases women encounter in working environments. This should ‘level the playing field’ and help to unlock economic opportunities for women.

Check out our ratings of a range of interventions capable (to varying degrees) of overcoming gender-specific constraints below, and for a full analysis, read the report.

Roadmap Ratings