I have been fortunate to attend a couple of conferences and meetings recently and to present work in progress as well as to meet with people in diverse fields – outside of economics – to hear about what other folks are doing in teaching quantitative courses, data analysis, and research reproducibility.
The Conference for Teaching and Research in Economic Education (CTREE) was held in St. Louis Missouri. I presented in two sessions and also served as a discussant.
- Presentation 1: Behavioral Economics in the Classroom
- Presentation 2: Teaching Social Preferences
- Presentation 3 (co-author presented): Does Economics make you selfish?
With respect to my presentations, for the first presentation, I was participating in a panel organized by Mark Maier of Glendale Community College relating to a new PBS Series “Hacking Your Mind” produced by Carl Byker. Carl presented some clips from the upcoming series and three of us presented some ideas about what we teach in behavioral economics classes at different places: me at Smith College, Marcelo Clerici-Arias at Stanford, and Sheryl Ball at Virginia Tech. My main argument is that, these days, behavioral economics is truly economics and we should view it as such. Furthermore, we also need to be clear about what we mean when we talk about the propositions of behavioral economics as many otherwise well-known people sometimes present a straw man of conventional economics that we should not buy into. I don’t have a specific paper relating this presentation just yet, but I hope to write something in the future along the lines of the argument I made.
My second presentation was about a set of models I teach in intermediate microeconomics to teach social preferences or other-regarding preferences: altruism, difference aversion, reciprocity, trust, and so on. These types of preferences are often left out of conventional courses because they are thought of as being too ‘hard’ to teach. Using standard tools, I show that altruism and inequality aversion can be taught using standard methods of constrained optimization. I also demonstrate how a model of externalities with altruism and social punishment can implement a Pareto-improvement (or even a Pareto-efficient outcome) over the Pareto-inefficient Nash equilibrium. Lastly, I presented a model of exchange in an Edgeworth box with altruism in which the contract curve (Pareto-efficient curve) is shortened as a consequence of the fellow-feeling the traders feel for each other (along the lines of a variety of historical and contemporary examples where people who might others treat their counterparts very poorly, instead leave something on the table for their fellow traders – consider, for example, the silent trade involving the Carthaginians as a historical example of this).
The third presentation was done by my co-author, Sai Mamunuru (PhD candidate at UMass, Amherst). She, Sam Bowles, Daniele Girardi and I ran an experiment using an incentivized survey with students in three different intermediate microeconomics classes at UMass as well as with a nutrition class. We conducted triple dictator games (with one of three charities) and trust games (randomly ordered) with the subjects and we surveyed them for their policy opinions. We repeated the same incentivized survey later in the semester as a way to see whether peoples’ behavior changed over time and this allows us to do a difference-in-differences analysis to deal with selection effects into economics classes which might otherwise explain selfish behavior by students. We find that economics students are not, on average, more selfish than the control nutrition and dietary science students (most of whom were women). This result contradicts some other research suggesting that economics students are more selfish than others. We are continuing to analyze the data and the paper will be submitted later this year.
I served as a discussant for a paper by Becky LaFrancois and Scott Houser (both at the Colorado School of Mines) who are doing some really great work looking at how we can include ethical micro-insertions into economics teaching to make students think about the ethical implications of the economic models they learn and apply to real-world problems. Given recent considerations in economics about unethical behavior, this is timely and important work. I wish their project the best and look forward to seeing how it develops.
TIER Executive Meeting and Fellows Meeting
I am on the executive board for Project TIER (Teaching Integrity in Empirical Research) based at Haverford College in Philadelphia, PA and founded by Richard Ball and Norm Medeiros (see Ball and Medeiros (2012)). I was previously a TIER Faculty Fellow and, because of my continued commitment to teaching reproducibility and integrity in research, I wanted to remain involved with the project. We submitted an NSF grant toward the end of last fall (the first time we were doing so) and the grant was rejected – not surprising as this is standard from what I understand. We learned a lot from that initial submission and are planning on working on new aspects of the grant before re-applying to the NSF or other funders. The executive board met for a day to strategize about the application process and the future of Project TIER, which was followed by the faculty fellows meeting. On my second day in Philadelphia, we met with the outgoing TIER fellows (2018-19) as well as the incoming fellows (2019-20). They are all impressive folks and I learned important ideas from each of them. Here are a few points from the presentations (I provide my slides and so on first).
I presented briefly on using TIER-related ideas in my teaching at Smith College and the affiliated work I have done as an executive board member and former fellow. You can see my slides here. I highlighted work I did that involved TIER such as Dvorak et al. (2019), Halliday (2019b), and Halliday (2019a), while speaking about the ways I’ve tried to implement TIER in these class and hope to change my practice in the future.
Morton Ann Gernsbacher (U Wisconsin, Madison) - Morton is a professor of psychology and neuroscience and has recently written several papers (see Gernsbacher (2018b), Gernsbacher (2018a), and Gernsbacher (2018c) all available here) on open science in her disciplines. She presented a convincing case for pre-registration, arguing that even more exploratory work can be pre-registered and that pre-registration (even done privately) acts as a commitment device to constrain yourself in ways that are beneficial to you as a researcher and to the discipline as a whole. I was convinced and think I need to investigate this more in the future, though I may not be able to do this with student Honors work. In case you need convincing about the benefits of pre-registration take a look at this figure from Schäfer and Schwarz (2019):
Nicole Janz (U. Nottingham) presented on work she’s been doing to promote reproducbility in the classroom and in research. As motivation, she shared email correspondence she’s had with researchers asking for data and code, in the majority of cases researchers promise the data and code but never send it. Nicole also spoke about work she’s co-authored with fellow political scientists to work on reproducibility and transparency in the discipline, see, for example, Gleditsch and Janz (2016) and Janz (2016). She also has forthcoming work with other TIER-related folks. Nicole is also a BITSS catalyst.
Michael O’Hara (St. Lawrence University) - Michael is a co-author of mine on a recent piece for J. Econ Ed (Dvorak et al. (2019), see here). He presented on his experiences teaching reproducibility at Hamilton, Colgate and St. Lawrence in econometrics classes. He’s a champion for making student work reproducible and you should check out what he’s managed to do with his students on the Harvard Dataverse.
David Vera (Cal State, Fresno) - David presented on his experience reforming his statistics and econometrics class at CSF. He had previously taught the class using SPSS and didn’t like the outcomes. A few years ago he shifted to using R and R Markdown in his classes and he’s seen incredible improvements in student outcomes and students do not feel that learning R impedes their understanidng (the opposite is true).
Megan Becker (USC) - Megan teaches IR and works on conflict. She has done a variety of work on replication and runs a lab (the SPEC lab) at USC with 65+ students who are now working on replication activities. She explained one project with students where they looked at at famous paper by Ross (2004) on the resource curse and they documented a replication process (also involving Ross himself so the students could ask questions and engage with him). It sounds like an eminently fruitful activity from which she and her students benefit greatly. She has some great ideas about mentoring undergraduate students in ongoing research and setting up a lab in political science research.
Chris Conway (Fordham U, previously William & Mary) - Chris is a psychologist who works in mental health and he is very interested in the replication crisis psychology and what kinds of plans we as researchers can develop to ensure that our research work more broadly – not just data analysis but the broader aspects of reseach practice – are more transparent.
Sam Harper (McGill University) - Sam has done some great work already on replicating published research in public health and epidemiology. He explained a few of his projects and highlighted the ways in which different researchers can produce better or worse methods sections in their papers to make replication more or less feasible. He demonstrated this with a couple of his own papers, highlighting one paper on whether medical marijuana laws increase marijuana use (Harper, Strumpf, and Kaufman (2012)) and another on whether 4/20 Day affects traffic accidents (Harper and Palayew (2019)). Sam’s work is available on the Harvard Dataverse here. He has also developed a course on reproducible research for medical professionals and is engaged in thinking about what better reproducibility would look like in medical research.
Ben Marwick (Washington U) - Ben is an archaeologist with a strong interest in research transparency in anthropology and archaeology (who knew this was a thing?). He has done some pretty phenomenal work on authoring his own work in R Markdown, writing packages for papers he’s written, and collaborating with folks to put together the
rrtoolspackage that helps to make research reproducible (see Marwick (2019), Marwick, Boettiger, and Mullen (2018)). I would advise you to read a piece he wrote for The Conversation a few years ago, “How computers broke science”. I hope to employ the language he highlights about papers being the “advertisement” for scholarship, but the scholarship itself is what goes on in the process of producing that advertisement. Do also consider taking a look at the University of Washington’s page on reproducibility.