Even since before starting this blog I have a received a lot of questions regarding the education I have had in the field of Behavioural Economics. One of the most frequently asked questions is related to my first master’s degree, the MSc in Behavioural and Economic Sciences. In this article I will review that master, as to give you a better idea of its content, purpose and implications.
General MSc The degree has two streams of training. One is called the science track, the second is called the economics track. The difference is that the economics track starts before term 1. They follow additional courses in mathematics and statistics. In their term 1 they have one course in econometrics and one in economic analysis. This is different from the science track, who has only one additional course in term 1: Behavioural Microeconomics. As I was a science track student, which was more research focussed, I am only able to expand on the science track part of the MSc.
Term 1 In term 1 there were three courses for the science track: Behavioural Microeconomics, Methods and Analysis in Behavioural Science and Issues in Psychological Science. I will discuss them in turn.
Behavioural Microeconomics As most students enrolled in the science track had no training in economics, this course was meant to get acquainted and proficient in the topic of microeconomics, but always with a behavioural background as context. This course was the one that took up the most time in the first term, due to the amount of work it was. Mind you, I did have training in economics, and it was still a lot of work. However, it was also a great course. Jointly taught by Andrea Isoni and Graham Loomes, the course dealt with a variety of topics, from both economics and behavioural science. I thoroughly enjoyed it, despite the amount of work.
Methods and Analysis in Behavioural Science As sweet and innocent as it sounds, MABS was pretty much just an introduction to R. And although that doesn’t sound too bad, the word introduction is supposed to be taken very lightly. This course was a punch in the stomach for those who had no background in statistics, programming or both….. But it was a good course. In my cohort it was taught by Neil Stewart. A man who truly breathes R, and can inspire enthusiasm for it, which is impressive to say the least. The course is incredibly fast-paced. Not showing up to a lecture or a coding workshop was a disastrous idea. Not doing the “homework” exercises was an even worse idea. Ultimately, you could get away with doing the bare minimum, but it would reflect in the assignment grade. Moreover, it would reflect in on your grades in term 2, as the other courses assumed knowledge of R to be even able to fulfil the basic criteria of the assignments. Slacking of in this course was going to have massive spill over effects. So I would recommend buckling down over any type of coding course. It takes hours and hours to learn a single command properly. But for anything involving data science that is the only way to go.
Issues in Psychological Science This course could have been renamed Introduction to Psychology. It was mainly taught by Gordon Brown in my cohort. Topics discussed were identity, vision, clinical psychology, neuroscience, basic decision-making, heredity and other basic topics. As I had had training in psychology as well, this course did nothing for me. But I can imagine that for the economics track, this course was still quite intense, as they had to quickly learn a wide array of different topics. Term 1 ended with two papers for IiPS (2500 words), three coding assignments for MABS and 5000 word paper for BME. In January there was also the BME Exam, so most of the Christmas break was spent studying and writing.
Term 2 In term 2 there were six courses for the science track. As compensation for their increased upfront workload, the economics track could pick five out of these six courses. They could choose from: Behavioural Economics, Experimental Economics, Neuroeconomics, Psychological Models of Choice, Behavioural Science: Implications and Applications, and lastly Principles of Cognition. I will discuss them in turn.
Behavioural Economics To me, this course was a waste of time. It was organised by the economics department. In its ten lectures, the first five were a bad repetition of BME. The last five were Behavioural Macroeconomics, in which I have no interest. It did not help that the lectures were 15-17 on a Friday…. I would not recommend this course. As a result I put in the minimum effort, which did not affect my grade at all. Experimental Economics This course was also ran by the economics department. In my cohort, the initial five lectures were taught by Ganna Progrebna, who is just plain awesome. She knew the topic, explained it well and got people enthusiastic for it. It was early, 9-11 on a Thursday, which was slightly unfortunate. The last five lectures had a different teacher and I was not a fan. Stopped attending them as a result. This again did not impact my grade. The topic of the course in itself was interesting, but for me personally not applicable.
Neuroeconomics Knowing that I am a behavioural scientist, you might think Neuroeconomics would be the course I’d be least interested in. Well I am here to tell you, you are wrong! I loved it. Absolutely loved it. The course is taught by Elliot Ludvig, who is an amazing teacher to begin with. Knows his stuff, well-spoken, knows how to make things relevant and applicable to current day and just so entertaining. It was fortunate that he was a good teacher and his course was interesting, because dear Lord, that was a lot of work…. In term 2, the lion share of my time went to studying NE. The course was fast and difficult. There are just some things which cannot be “dumbed down.” Before each lecture you had to read two chapters on the basics, then have the lecture (2 hours), and make a lot of notes about it! After the lecture you had two days before you needed to have read the articles that were going to be presented and discussed in the seminars on Friday. There were two in class tests, a forum for which participation was graded, a presentation and a written assignment (3 1500 word blogposts, or a 4000 word paper). Thinking back my head starts spinning. But I thought it was the most fascinating course of the whole MSc, and I hope to teach it this academic year. So it couldn’t have been that bad!
Psychological Models of Choice This course was a joint effort of the psychology department. It had several lecturers and as such I am not too sure who to refer to as its teacher. Elliot taught the models of Expected Value, Expected Utility, (Cumulative) Prospect Theory and TAX. Whereas Thomas Hills talked about exploration and exploitation and choice paradoxes. Neil explained computational modelling if memory serves me and there were lectures on emotions and heuristics by Lukasz Walasek. It was a great course. The topics were very interesting and offered a very wide range of the models used in psychology. I would deem this to be a core course of the MSc. Quite intense as well though. Three in class tests and a paper which was based on coding Cumulative Prospect Theory. I did mention before that you needed to know R to progress in this MSc, right?
Behavioural Science: Implications and Applications When you are looking for the MSc BES now, you won’t find this course on the program anymore. And I can understand why. It was quite theoretical, and very simple. Which was good for the science track, as they had to juggle six courses, but still. This class offered fun lectures, had three in class texts which were so literally based on the lectures studying was not required and a final coding assignment which was so simple you couldn’t fail it even if you tried. When looking at the course overview now, this course has been replaced by Behavioural Change: Nudging & Persuasion. Which to me sounds like a pretty awesome course, which I might try to audit this academic year.
Principles of Cognition This course was ran through the business school, just like BME. It was taught by one of the WBS’s flagships: Nick Chater. He deserves that status, he is a great researcher and teacher. He likes to challenge foundational beliefs held in science and make people argue for the other side. He taught on the basics of perception, Bayesian statistics (and its errors), and quite a few biases as well. The course was mainly lecture-based, very interesting, not a lot of work. It was graded through one written essay of about 2500 words. I enjoyed it.
Some of the courses in term 2 were intense. Luckily, not all of them were. For me the obvious winners were Neuroeconomics and Psychological Models of Choice. These courses were the most interesting and the most fun. Ironically, they were also the most work. As we had so many courses and assignments, our spring break was pretty much just writing out those assignments. Lucky thing was, there was at least a week between each deadline, so it did not feel like you were drowning. There was definitely team to breath.
Term 3 This term prepared me for life as a PhD student. In this term we worked on our respective dissertations. The topic for my dissertation had already been set as a trial run for my PhD studies. I knew I was working with a longer-term horizon in mind. As a result, the supervision I got was really great. We easily met twice a week to make sure everything was in place and ran smoothly. In that respect I was quite lucky. Not each supervisor was as available, or as willing to be available, nor were all of them as supportive. That one can be quite a hit or a miss. Although I do have to emphasize that all the staff directly involved within the MSc BES were nothing but great at being supervisors.
Conclusion I know this article has become massively long already, but please bear with me for a little longer. Although I was not equally enthusiastic about all of the courses, I do think the MSc Behavioural and Economic Science is great. I feel like I had to put in a lot of hard work, but I also learned a lot, felt supported and surrounded by a great group of people and got a lot of great experiences out of it. I would recommend it to anyone who wants to progress in behavioural science and/or behavioural economics. Another lucky thing is the program is well-grounded in academia. It was designed to help you obtain a PhD, so for those of you who are thinking about this already, definitely keep this MSc in mind.
If you have made it this far: thank you and congratulations! Let me know if there is any aspect I missed in reviewing this MSc, whether you have a different opinion, or whether you are left with any questions.
Check out this link if you'd like to know more: https://warwick.ac.uk/fac/sci/psych/bes/