This past week I gave a talk to students part of the Hong Kong UST DBA Program regarding implementing behavioral finance initiatives in companies. The talk covered some case studies that varied in different dimensions relative to the degree of integration of science and degree of organizational complexity. I have often emphasized that organizations that want to implement behavioral initiatives need to consider dimensions of Goals, Research, Innovation, and Testing (GRIT) among other behavioral-specific considerations (e.g., choice, information, process, and personalization architecture).
However, one of the most striking parts of the discussion for me surrounded the notion of ethics, which has come up a number of times in my discussion with students.
Although I was only able to touch on two angles in my HKUST talk, for the core classes I teach, I offer at least three different lenses for thinking about behavioral economics and ethics: 1) goal alignment between the company and the end user, 2) nature of behavioral intervention design (e.g., how much control does it exert), and 3) moral foundations and considerations (e.g., care/harm, fairness).
There are clearly other considerations that could come into play (e.g., to what extent comfortable sharing behavioral intervention thinking publicly; legal versus ethical 2×2). However, it is good that students think through ethical considerations. Things aren’t always as black and white as we’d might like, so it’s important to have multiple lenses through which one can evaluate situations.
Yesterday I outlined five primary areas of behavioral architecture that we would cover during the academic semester. Two prominent ones we covered included choice architecture (e.g., how choices are presented, such as with respect to defaults and number of choice options) and information architecture (e.g., how information is presented, such as percent of salary versus pennies for every dollar you earn).
As a third area, I framed thinking architecture as the process by which an architect tries to encourage end users to use more slow, reflective thinking versus fast, intuitive thinking. A classic question that tries to illustrate this is the following:
A bat and ball together cost $1.10. The bat costs $1.00 more than the ball. How much does the ball cost?
It is tempting for many people to think that the ball costs $0.10 (based on fast, intuitive thinking), although the correct answer is $0.05.
One form of thinking architecture could have been to get users to follow a checklist:
Write down your guess for the ball cost (e.g., $0.10).
Add $1 to the ball cost and write that number down as the bat cost (e.g., $1.10).
Add the ball and bat cost (e.g., $1.20)
If the numbers don’t add up to $1.10, repeat step 1.
In my view of thinking architecture, we are essentially trying to slow down both the brain to try to get the mind to follow certain thinking pathways. Whereas neoclassic economics doesn’t account for thinking pathways, path dependency is everything in psychology and affects behavior.
Implementations of thinking architecture space have been less explored. However, the possibilities are endless. Some examples include:
Addressing complexity (e.g., aviation pre-flight checklists for pilots)
Helping to avoid common errors (e.g., blindspots such as forgotten opportunities as to how I might want to use money in retirement or risks of underinsuring myself when younger)
Expanding the thinking (e.g., are there other potential ways of realizing goals during retirement)
Weighing difficult tradeoffs (e.g., should the money be used to save a single life or implement an equipment upgrade)
Thinking architecture requires thoughtful design, and it is not always the easiest to implement. However, the human mind is an amazing wonder. Sometimes we need to really tap into its power.
References: Frederick, Shane. “Cognitive reflection and decision making.” Journal of Economic Perspectives 19, no. 4 (2005): 25-42.
Howard Marks has written a quite a remarkable memo that will be impossible for me to do the proper justice on. However, here are few key highlights from his memo:
He shares perspectives having been in investing for 53 years.
He has seen two major sea changes during that time.
One sea change included the evolution of the bond market in the late 70s and most importantly, a shift in investor mindset to thinking about risk and return (which was not the way investors thought about investments back then).
The second sea change had to do with macroeconomic policy and use of interest rate controls to not only control inflation but also feed a market fueled by declining interest rates (and turbo charged by leverage) resulting in four decades of 10.3% growth when looking at the S&P 500.
The third sea change he sees is where we are now. While I definitely oversimplify (you need to read the memo), the fuel of declining interest rates are unlikely to be a tailwind at our backs as compared to the prior 40 years. If you believe some of these perspectives, it seems as though many investors will need new investment strategies (e.g., rebalancing of portfolios from equity to credit instruments).
As a behavioral finance person, I see some perils of using fast, autonomous thinking and the need to try to use more slow, reflective thinking. I also see the role of inertia. Like many other people, my portfolio is heavily tilted to equities. How can people both re-think and maneuver? At the same time, how can they leverage behavioral principles and avoid biases of anchoring, such as to the past? Potentially we can use behavioral tools like whiteboard exercises to re-imagine paths to go forward. We can potentially use behavioral tools to address issues associated with forecasting, prediction, and risk. There is also the need for personalized solutions. And if there is a sea change (or if we at least need to prepare for one), there is also a need to think about how to distribute solutions to the masses. There are behavioral implications lurking. How will individual investors manage? How will the finance community and its distribution networks address such behavioral considerations? There are definitely behavioral issues to consider and address, and it will be interesting to participate in the debates and also work on block-and-tackle solutions.
A short update separate from my academic work: I expect to have a somewhat rare opening in 2023-2026 to take on a behavioral economics advisory relationship with a new client in retirement, wealth management, or investment management. Please feel free to contact me to discuss further.
Based on the recent ChatGPT events that have rocked the world, here’s a baseline working draft of an AI notice that I will use in some of my classes at Cornell. It presumes that AI will be used more and more over time and that as teachers we’ll have to figure out how to balance the performance and educational integrity tradeoffs.
“Students may use artificial intelligence (AI) technologies for support purposes with their writing assignments and projects (e.g., fine-tuning language) but not for writing fundamental ideas (e.g., constructing major portions of a paper). Students are required to disclose (in an appendix) use of any artificial intelligence (AI) technologies in their writing assignments and final projects, including enumerating any key steps, substantive queries used, and the purpose of key steps and queries. Students may be subject to disciplinary action if found to have violated this code of conduct.”
The fall semester has really flown by. We’re in the final stretch. Thanks to all of the students in my research methods class. What hasn’t killed you has made you stronger. Lol.
I am already mentally trying to prepare for spring teaching. Here’s a short pitch slide for students considering taking my AEM 6150 course on applied behavioral economics.
A strategic issue that many professors face within the university is how to teach in a world when one is both competing for attention in the Digital Age and also trying to justify value-add over other methods that people can use to educate themselves. For example, people can read books. They can watch videos on TikTok or YouTube. They can take classes remotely or even do self-study using online platforms. At the core when it comes to the classroom, professors compete against other learning resources that scale dramatically and are delivered at lower cost. I am all for further development of those types of resources and educational models, recognizing their benefits, challenges, and limitations. With that as context, I wanted to share some thoughts about how a professor can differentiate themselves when it comes to the traditional classroom and adding the most value.
The digital world doesn’t necessarily scale that well when it comes to compassion and developing interpersonal relationships, so I think a first key differentiator for professors can be to try to foster a good environment that connects real people together. That means focusing on multiple connections. Connect students to one another, perhaps via icebreakers. Encourage higher-level connections by fostering team-building and having people share their wants and desires. Set up a safe environment where people can learn. Invite constructive feedback. This past week I told students that I really “loved” how some of them were really blunt about their dislike for one of the assigned readings. They provided feedback that they weren’t sure how it was relevant, and so I did my best to frame things in the proper light (e.g., some pain is good for them, here are the essentials to take away beyond the classroom). Where students are receptive, I also try to make some time for students to meet me and one another outside of the classroom (e.g., meeting for coffee, drinks, breakfast, potluck dinner).
A second idea for differentiation is related to personalization (which is something I teach in my applied behavioral economics course). While professors often have responsibilities to follow specific instruction plans, I think there may be increased opportunities for students to be able to personalize (portions) the type of instruction they would like to receive. I recently held a class that allowed students to choose one of four doors that they could open, and then I led the class discussion in a direction based on what door they voted to open. I have heard through the grapevine (i.e., in this case Reddit) about other professors creating “liquid syllabi” where students can completely edit and provide suggestions to a syllabus via Google Docs and the like. I am not sure how workable that type of approach would be in reality. However, there seems to be value to customization and personalization of instruction, which is something else that digital platforms may not be able to do as well. I also think that being able to provide feedback to students on their work is a point where professors can differentiate themselves. However, given the size of classes, number of assignments, types of assignments, etc. there can be limitations on scaling this.
A third idea is around just-in-time education and providing bite-sized snippets of education (TikTok excels at bite-sized snippets). There is so much out there for students to learn. As professors learn where students’ interests lie, what their aspirations are, and where they are having trouble, it may be possible for professors to provide mini content or crash courses on material. As an example, I have often told students that they will likely see Scrum/Agile project management methods when they go into the working world. Perhaps one of the most brilliant books I have seen is the format of the book, Scrum: a Breathtakingly Brief and Agile Introduction by Chris Sims and Hillary Louise Johnson. The book is about 50-pages long with simple to-the-point language, a lot of cartoon-style drawings. It can be read in 20 minutes. For a classroom setting, I’ve even digested down this book further into a 2-4 minute crash intro to be delivered at the point when I sense students might need or want such information. While it may be harder for professors to compete against the digital world when it comes to delivering bite-sized, engaging information, perhaps there are opportunities to combine approaches from the digital world into the classroom (e.g., more use of Cameo, TikTok, YouTube, digital exercises/games).
A fourth area of potential differentiation is to provide students with opportunities to connect with the outside world. This could be by having guest speakers, offering unique case studies, facilitating access to projects in industry, or helping students develop new skills that can be used when they leave school (e.g., learning tools like R or Python). On the flip side to this, universities appreciate when alumni and companies can help to enrich the student classroom. Possible ways to help include donating money, sponsoring/hosting student projects, guest speaking, and offering to provide materials that can be used in the classroom. I am very thankful to people at companies like Acorns, Personal Capital, Telefonica, Vitality, Voya, and others for helping both me and my students with their learning journeys.
One of my aspirations in life is to give back to students and enrich their lives in some way. I am evolving my thinking on the best ways to teach in the classroom, so I welcome ideas and feedback. At some point, I also hope to think about how to extend teaching beyond the traditional classroom. Perhaps a topic for a future post.
Last month I chatted with Tony Roth, Chief Investment Officer at Wilmington Trust, N.A., a subsidiary of M&T Bank (NYSE: MTB) as part of his podcast series, Capital Conversations. For me, it was an interesting conversation to have had for a number of reasons, and three perspectives really captured the direction of my thinking.
The first perspective was that as a society we have really been under a lot of stress for the past two years, a type of stress that I have not seen in my lifetime. So while investment markets are not currently very volatile, it is a good time for many people to get a fresh start and re-assess their situations.
The third perspective is that people are really different, and sometimes it can matter a lot. We understand some of these differences better than others (such as innumeracy and its impacts). There are other differences (like capability and confidence mismatches relative to new technologies, like cryptocurrency) that are less understood. As another example, the younger generation thinks about finance and life very differently than older generations. How to better address individual behavioral differences and situations will be an ongoing opportunity where people will need help.
The second perspective was that there are so many different behavioral elements at play when we think about different people, the interplay of fast, automatic thinking versus slow, reflective thinking; the digital world, and the numerous challenges of finance. It is unlikely that we can find one silver bullet, behavioral solution to fully address all problems. That said, we can put in place processes to help ensure that we make the best decisions we can for the things that really matter, while also avoiding some of the major obstacles that happen on a regular basis, such as overconfidence, natural biases in forecasting the future, thinking in narrow frames, and others.
Thanks to Tony Roth and the Wilmington Trust team for hosting me for the podcast.
