My Findings

Going into my research I had relatively little understanding of the economic realities of the Andes. As time progressed I made more and more hypotheses about the alto-Andean economy that I was itching to test, with all of them centered on the weaving industry that remains so central to rural Andean life and the women who perform the weaving. Among them were the following:

  • Women living closer to a weaving center could earn more money
  • Women with high Spanish-speaking abilities (as opposed to Quechua) would make more money
  • Children take up time and, therefore, lower a woman’s earnings

As always in economics, the realities were far more complex. In fact, there was absolutely NO evidence whatsoever that any of those hypotheses—the ones I most expected to be true—were valid, statistically speaking. What I did find, however, was that there is vast economic inequality within the part of the weaving industry where Awamaki (the nonprofit I was working with) works.

It’s impossible to view the weaving industry of the Ollantaytambo area purely in a vacuum. Other activities like farming and tourism certainly take place in the communities of Kelkanka, Patacancha, Huilloc, Puente Inca, and Rumira. When it comes to measuring the wealth of the families benefiting from Awamaki’s work, it would be naïve to insist that weaving is the only relevant economic activity.

With that in mind, there was one finding rather startled me. There was striking wealth inequality (around a .43 GINI coefficient) within the poor, rural communities where the weaving cooperatives were located. What’s more, the nonprofit’s records show that those women whose families were identified as being the wealthiest also made the highest revenues from the nonprofit, a fact that was found to be statistically significant under further review. There are myriad reasons why this may be—which I will certainly go into in my final paper—but the gist is this: women with more money may be more likely to have more support from their husbands or to relate better to wealthy tourists who are willing to pay high premiums for the high-quality hand-made goods the women in the cooperatives make.

This was the main finding of my research, but there are several smaller facts that relate to this one. I’ll talk about these quantitative measures as well as qualitative ones in my final paper.


  1. Matthew Bondy says:


    It seems like your research had a lot of overlaps with the project I was working on. I was in Tanzania doing research on how mobile phone technology affect’s women’s empowerment, specifically women entrepreneurs.

    We haven’t quite crunched all the numbers yet, but it looks like some of the hypotheses that we had originally had about how cell phones might help women earn more income, have a better domestic situation, etc., might not be confirmed.

    On one hand, this can seem disappointing. It would be nice to be able to show that a specific program (in this case, providing cell phones) is an effective policy tool, but we aren’t able to do that. But on the other hand, it’s important to know what doesn’t work. It’s important to know what causal relationships aren’t true so that researchers and policymakers can devote their energy to something else instead.

    It sounds to me like you still made some really interesting findings, though, especially on the qualitative side. Good luck with the paper!