Kevin Quealy (@KevinQ) wrote a nice piece in last week’s NY Times analyzing the race for the Republican nomination from a game theory perspective. While I was slightly irritated by Rubio’s classification as a mainstream candidate, it’s an interesting application of basic game theory principles worth reading.
Public transport servants as well as cab drivers of Paris decided to strike today. Amongst other resasons, they protest against the access of amateur drivers like UBER to the personal transportation market, which in so many European countries typically requires licensing. The bulk of UBER drivers go along with the strike in order not to stir up emotions even further.
While this is true for the majority of drivers, some appear to defect, most likely due to a lack of information and more importantly to realize potentially huge gains from offering a scarce good. UBER prices are determined by an algorithm depending on supply and demand for rides within a given period in a specific area. Prices this morning were already 8.3 times higher than the base fare. In addition, some foreign cab drivers, in particular Belgian residents, are expected to take on this unique arbitrage opportunity.
I am not aware of the specifics of French competition laws but it seems highly likely that this behavior, while rational, must violate racketeering guidelines. Due to the immense cost of identification, prosecution seems unlikely though. Thus, it remains only to hope for a more subtle resolution than last time this conflict erupted. If not, the French government might have a decent case to blame UBER executives for not disabling their algorithm during the strike. Since this seems to be in the interest of strike participants-and potential rioters-in the first place, an undesirable scenario seems possible.
On Sunday, November 30, Joseph Stiglitz advertised his new book “The Great Divide” at the Vienna University of Economics and Business Administration (WU). Neither did I attend the lecture nor do I have access to any recording. My only record of his words is a German article in the Austrian daily newspaper “Der Standard” (which can be accessed here). That means, Stiglitz has been first translated into German and in what follows I re-translate into English. Given this sounds like an instance of the children’s game telephone, there might well be content lost in translation.
Nevertheless, I was quite surprised by what I read. According to the article (as objectively translated as I could) Stiglitz said:
“Demanding solidarity is not easy in good times. It becomes, however, politically dangerous if poverty and unemployment are on the rise since [in this case] it generates breeding grounds for right wing extremist parties. This also holds true for countries like Germany and Austria. Society should not only solidarize with refugees but also with low-income (and low-skill) workers. Those should be increasingly supported by the wealthy elites in these countries by re-distributional policies to avoid social tensions. Necessary funds could be generated by “wealth taxes” [private capital or equity taxes].”
There certainly is a deeper truth to this statement anywhere in the world. Also, it hardly comes as a surprise. However, I was somewhat startled to see it applied to Germany and Austria, admittedly the two countries with the biggest refugee influx per capita recently, but also two countries among the world-leading in equality and the extent of tax funded social services.
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.
A interesting instance of social and individual rationality contradicting each other is the question of how to program self-driving cars to react in the case of a looming accident. Ignoring the lurid headline the article on this social dilemma is quite interesting. Apparently, early research by Toulouse psychologist Jean-Francois Bonnefon indicates the majority of people agreeing that cars should be programmed to choose the alternative which kills the least amount of people in expectation. Unsurprisingly, this ceases to hold true if this increases the probability of the interviewee being killed in the accident.