I am starting a new monthly post where I share what I have been working on what I am hoping to work on shortly. This is the first edition. If you see something you think is interesting, don’t hesitate to email me.
I posted a copy of a working paper I did as a term paper for Economics of Science. The paper looks at the Pentagon’s research budget over the past twenty years, and how it has moved money between basic and applied science. One really interesting facet of the budget data is just how large of an impact presidential initiatives have on this budget (one example: the Bush missile shield). This was sort of a side project, but I think the data is interesting, and there are lots of opportunities for follow ups if anyone is interested.
I am doing a historical study of the rise of public policy schools and their curriculums. One example of this research is a post I wrote two weeks ago about how economics became the center of public policy due to its perceived legitimacy within Harvard. I am really interested in epistemology in public policy, and why we continue to use a narrow set of tools rather than a richer one.
My larger research project looks at the creation, dissemination, and growth of rankings and other ordinal measures of performance. As quantification becomes increasingly popular in everything from business to politics, I believe there needs to be increasing skepticism and critical analysis of precisely how these measures get created and used. This is part of a long discourse on power and knowledge. One great new book on this is The Quiet Power of Indicators which discusses how indicators like Freedom House’s came into being and how they are used today.
A smaller project off of rankings is looking at how machine learning may be used in public policy, and what assumptions are built into specific algorithms. I am also considering novel uses of ML algorithms for policy, such as in immigration.
I am teaching an undergraduate class on startups and entrepreneurship next month. I’ll place the syllabus and materials once they are fully fleshed out.
As always, I continue to write a lot for TechCrunch. Some highlights include the challenge of analyzing truth on the internet these days and how algorithms are reshaping politics. My most popular posts were on millennials and banking as well as a piece on why the university is still here.
This month, I am hoping to do some stories on machine learning in politics, as well as new securitization models and other innovations (or lack thereof) in fintech.
I am preparing my reading lists for economic sociology, tournament models in labor economics, quantification studies, among other topics. Would love to see some more recent papers in these fields that people find interesting.
I continue to spend time learning Korean. A few resources I have recently found to be quite helpful. One is Talk To Me In Korean’s “News in Korean” subscription, which sends three short articles a week in Korean along with audio readings of them. Two books that have been helpful are the Common Sense Dictionary of Global Economy and the Common Sense Dictionary of Politics. Excellent resources and practice for learning political and economic vocabulary.
I am going to co-edit the Harvard Kennedy School’s student newspaper next year.
Image by Ryan McKnight used under Creative Commons