Dear fellow faculty, administration, staff and not at least students: Poets & Quants chose the Cornell Teach MBA as the program of the year. See the article here.
Congratulations and well deserved!
When obtaining a post-secondary education in Economics and/or Business related fields, one typically spends a considerable amount of time studying various models of decision-making. Arguably two prominent reasons for teaching those models to students not targeting an academic career—most notably the majority of undergraduate students as well budding MBAs—are a) to provide them with frameworks to forecast and foresee the decisions of others and b) to sharpen their ability in making decisions themselves (which, in turn, is closely related to a)).
For their lack of opportunities to make significant decisions themselves while still in training, we typically resort to (real-world) examples featured in the business press or to (fictitious) business cases. In order to provide them with practice, we jointly tackle questions as in “how would you decide in this situation” or “what do you predict as the likely outcome of that scenario” in class. To put it bluntly, we teach them how to read, analyze and understand subject-specific articles. In the age of “fake news” and ubiquitous news coverage, I truly hope we also teach them how not to.
I typically challenge the class to feed each other with interesting and currently published information related to course content. Recently, a student of mine sent me this article published in the Economist linking the National Football League (NFL) with game theory. This student conceivably made a brilliant choice. The major sports leagues in the United States constitute an arena of decision-making commonly beloved by students, game theory is exciting as it adds the strategic component and The Economist is a highly reputable media outlet of business and politics. On the surface, I could not have chosen better myself.
In short, the article describes the contract situation between the (in recent decades) chronically unsuccessful Buffalo Bills and Tyrod Taylor, their current starting quarterback (the one who throws the ball), in early 2017. The Buffalo Bills benched Taylor for their last regular season game on New Year’s eve. At this point, Buffalo had no chance of reaching the playoffs anymore, i.e. it was de facto the last game of their season. After Taylor had played through a groin injury for several weeks, he opted for surgery at the very beginning of the offseason, i.e. 3 days after the last game (in which he did not feature).
The Economist argues that both actions, the Bills benching Taylor for their last game as well as Tyrod opting for surgery were direct consequences of the incentive structure inherent to their contractual situation. While, as claimed in the article, Taylor was an above average (top third) quarterback at an average quarterback salary, the Bills had the option to cut Taylor for negligible expenses until the beginning of March. However, if Mr. Taylor was rendered not fit to perform football services, the Bills would owe him close to $30M if they fired him.
This, for the Economist, constituted a so-called prisoner’s dilemma, a strategic stand-off between multiple parties in which each party has an unequivocally optimal action, which, if employed by everyone relevant to the game results in the socially worst scenario. In other words, the Bills had an incentive to bench Taylor for the last game whereas he should try everything possible not to be fit to play during the offseason (at least until March). What is more, it was stipulated that the Bills overlooked that they were in fact caught in a repeated prisoner’s dilemma with varying actors, that is other players with who they would have to deal in the future.
The main predictions based on their analysis were that, while not explicitly claimed, it was likely that the Bills were either going to fire Tyrod Taylor while injured (a costly endeavor) or opt not to due to the financial penalty of doing so although they would prefer to part ways. In any case, acting according to their best option would somehow sever the bond between the Bills and their quarterback. Moreover, by not realizing the more general implications of crossing a star player, the Bills would significantly reduce their chances of hiring popular players in the future. All of these implications taken together would even prolong and worsen the Buffalo Bills drought and their absence from the playoffs (17 years and counting). Lastly, it was argued that Rex Ryan, the coach of the Bills until their last season game was fired by the club’s owners since he disagreed with benching Taylor for the last season game.
In fact, the Buffalo Bills and Tyrod Taylor did not part way in the offseason of 2017. Instead, they renegotiated Taylor’s contract to keep him as a quarterback on a significantly lower salary. During the season the Bills took Kelvin Benjamin, a highly rated wide receiver (the one who catches the ball) from the Carolina Panthers, under contract. While the Bills traded assets (future draft picks) for the receiver and the trade was not directly Benjamin’s decision, it seems unlikely that the Bills would part with valuable options for today’s college players for an athlete who was not eager to play for the franchise. As of week 15 of the current season (two more games to follow), the Bills show a record of 8 wins and 6 losses and are at the brink of qualifying for the playoffs for the first time in 18 years.
While one time negative results do most certainly not refute the validity of predictions in the first place, a strategic analysis delivers similar results. A football player who opts for surgery only 3 days after the end of the season, a surgery which has an average recovery time of 7 weeks for non-athletes, does not seem to try everything possible to be deemed unfit when March comes around. If Taylor was above average in quality but paid below peers of his level, would it not be optimal for the team if he took care of his injuries as quickly as possible (to ensure his availability for team as long as possible before the start of the next season)? Many teams in various sports bench their star players in games that are inessential to their season goals. Why was this such a particular move in the case of the Buffalo Bills and Tyrod Taylor and why does this move necessarily carry negative consequences for an already injured player? Why, if Tyrod Taylor was overpaid against the league’s standards, did he agree to continue on the team for a substantially lower salary? Is it more likely that the Bills fired their head coach over a singular disagreement regarding the line-up or due the fact that Mr. Ryan did repeatedly not manage to lead a talented team to the playoffs and that he had an abysmal record in close games?
The model-theoretic analysis of the quoted article is as little capable of answering those questions as its predictions coincide with what unraveled after its publication. Bar a very few superstars, the National Football League (NFL) and its teams have tremendous power over their players as most NFL players would be expected to earn only a tiny fraction of their actual salaries if they were not to make it into or would have to exit the league. This fact paired with a salary cap, which ensures talent to the distributed across teams, guarantees teams significant bargaining power.
Dazzled by the institution of a reputable magazine and by the connection of buzz words and sports, I initially forwarded the article to the remainder of my students without any specific comments. After thoroughly reading and reflecting, however, I decided to scrutinize the article in class. In addition to teaching students how to filter business press articles and other relevant outlets for information and conducting an analysis based on these premises, I believe we ought to realize that, in a world characterized by the ubiquity of unfiltered content, teaching them to challenge this very information is the first crucial step towards a successful analytical contribution. While this sounds trivial, it clearly has to begin with questioning the intentions of author and publisher when reading an article. Whether the creators of an article intend to push a dogma, support a particular political view or simply myopically attempt to maximize readership, abstracting from those intentions should be the very first step in the process of filtering information.
Kenneth J. Arrow, the youngest economist ever to be awarded a Nobel (jointly with John R. Hicks) for “for their pioneering contributions to general economic equilibrium theory and welfare theory”, died aged 95. Arrow, undoubtedly one of the most brilliant minds of recent times, is considered a founding influence of several sub-fields of Economics and among the architects of the advancement of Economics as a science in the twentieth century.
Many share the opinion that his ground-breaking contributions to social choice, innovation, health economics and the economics of risk have been even more ground-breaking for the Economics community than his work on general equilibrium theory for which he was awarded the Nobel Memorial Prize in 1972. Arrow is among a selected very few who consistently made it on the bookies’ list to win another Nobel.
I have briefly pondered about writing a piece on his research contributions to make the unbelievable wealth of his ideas accessible to a broader audience. There is, however, no need to reinvent the wheel. My former classmate Kevin Bryan (who btw considers Arrow to only be the second greatest economist of all time), professor at the University of Toronto, and among other things an expert in the history of Economic Thought, started a brilliant mini series of four posts on Ken Arrow today on his blog A Fine Theorem.
Economist Noah Smith, assistant professor for Finance at Stony Brook University, recently wrote a post titled “Most of What You Learned in Econ 101 is Wrong” on Bloomberg view. He basically argues that standard introductory Economics textbooks—citing Mankiw’s “Principles of Economics”—solely refer to (outdated) basic models and do not incorporate advances in the profession. Although he did not choose the catchy title of the Bloomberg post himself, he claims that “… Mankiw’s book, like every introductory econ textbook I know of, has a big problem. Most of what’s in it is probably wrong.”
In reply, David Henderson, research fellow at the Hoover institution and associate professor of Economics at the Naval Post-Graduate School in Monterrey, defending the Econ 101 textbook points out: “Here’s what’s striking. In an article that purports to show that Mankiw is wrong on many issues, he [SMITH] doesn’t point out how he [MANKIW] is wrong on ANY issues.” To be fair, it should be mentioned here that Smith moderates in his reply: “… is that “right” and “wrong” are not very descriptive, helpful adjectives in this situation.”
In my opinion, Noah Smith is correct that “right” and “wrong” are problematic adjectives to evaluate basic theory in Economics. On the other hand, I agree with Henderson that Smith dropped some strong claims in the original Bloomberg view post but only supports them half-heartedly. The truth—if there is any—is, as so often, probably more moderate. In what follows I explain why and to which extent I agree with Smith’s opinion on introductory Econ classes and why not:
Why I disagree with Noah Smith
Known to every economist and valid as ever before, Joan Robinson once famously said “A model which took account of all the variegation of reality would be of no more use than a map at the scale of one to one.” I have frequently experienced students untrained in Economics to come to class and strive for the most complicated model there is to take into account and depict every eventuality of a real world situation. Every economist, who at least once attempted to write down a model, is perfectly aware of the fact that such an approach is frankly quite useless. Econ 101 ideally teaches students the ability to abstract from an incomprehensible environment to focus on questions of matter.
As an example for a stylized model N.S. mentions the basic minimum wage model, which predicts that the introduction of a lower price floor—the lowest wage employers may legally pay in a given market environment—leads to an increase in unemployment. Naturally, this (and similar stylized) model(s) do(es) and cannot apply to every real-world labor market. The validity of this model necessitates well-behaved preferences, rational behavior and an also otherwise friction-less environment. Moreover, it neglects various indirect benefits of minimum wages. While I deeply hope that decision makers do not base their actions solely on such a model, it is, in my opinion, still a valid and tremendous starting point for a comprehensive analysis. In addition, it serves an enormous educational purpose as a vehicle to teach students to abstract. This holds true for both theoretical and empirical analysis likewise unless we are eager to revert to ad-hoc estimation techniques.
Why I agree with Noah Smith
I disagree with N.S.’s claim “There’s no reason a college econ student shouldn’t learn how to run regressions in 101.” While teaching introductory regression to students both in Austria and at Northwestern I have experienced an eagerness of students to apply their newly acquired skills exorbitantly over-interpreting results which are far from robust. Thus, I do not believe that theory is necessarily to blame when Economics graduates in professional jobs over-interpret their stock of knowledge to make far-reaching decisions. Results from a basic regression analysis are equally likely as stylized models to be over-emphasized. An issue about which I entirely agree with Smith, if I interpret his contributions correctly, is the missing link between theory and empirics in basic Economics education. As of now, we are teaching stylized models in introductory classes and basic regression analysis parallel, often in the same quarter, not succeeding in highlighting their connection and necessary interplay for well-founded decision making.
I was fortunate enough to attend a class by Dale Mortensen on Labor Economics a couple of years ago. He picked five central theories of Labor Economics and devoted two classes to each of them. The first introduced a model rigorously on mathematical grounds whereas the follow-up class discussed stylized facts, available data, empirical contributions and the limitations of theory. Although I did not exactly end up being a Labor Economist, I have always admired the design of Dale’s class and plan to replicate his approach—when feasible—in the future. The course I am referring to, however, was a PhD elective and I am uncertain to which extent this interplay is replicable in freshman or sophomore classes. But I agree with Noah Smith’s discussion of theory and empirics in Econ 101 in so far as I believe that the missing link is the link itself.