Friday, June 24, 2016


Academically I have learned a lot in the past couple weeks. To mention just the largest, I've learned about the mechanics of a hedonic price model, the theory behind contingent valuation, and a lot about data collection. Perhaps most interesting and valuable is the one that seems initially simplest—data collection.

I think it is easy to look at a dataset and not necessarily think about where the numbers come from. I don't mean not to think about the source of the data or the mechanics of how it is collected, rather it's easy to fail to consider the people, the attitudes, and the contexts that underlie any given data point. I've thought about this a lot recently for two reasons.

Partially because designing surveys forces you to consider the context behind the issue that you are interested in in a way that working with already formed data does not. In order to write a good question you really have to consider all the different people that might be answering it and all the different ways they could interpret the question. I think I will be able to get so much more from the data when we get it back because of all the consideration we put into designing the questions and everything we had to understand about the communities we are studying to design it effectively.

The other aspect of the REU that has been making me really think about the data points separately is the interdisciplinarity of the project. Presenting to different disciplines, and listening to the presentations of the other projects allowed me to consider which methods or concepts complement our economics projects. I think especially the data collected by the anthropology team could greatly inform the our results from our coming survey.

I am looking forward to learning more economic methods and continuing to learn new perspectives on economics research though working interdisciplinarily.

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