Last week I had the pleasure of attending the Rebuilding Macroeconomics Conference with a theme of Bringing Psychology and Social Sciences into Macroeconomics. The basic question of the conference seemed to be ‘how can we avoid another financial crisis’ or, from a different perspective, ‘how can we avoid not predicting the next financial crisis’. There was an impressive roll call of speakers from economics, psychology, anthropology, neuroscience, sociology, mathematics and so on with their own take on this issue. Here are a few random thoughts on the conference (with the acknowledgement that I didn’t attend every session).
I was most at home with the talks from a behavioural economics perspective. But it was still great to get extra insight on how this work can be applied to macroeconomics. For instance, Rosemarie Nagel and Cars Hommes gave an interesting perspective on how the beauty contest has real world relevance. Most economists are familiar with the basic idea – people individually write down a number, you find the average, multiple by 2/3 to get the winning number, and being close to the winning number is good. No doubts this is a great game to play in the lab to pick apart strategic reasoning and learning. The new insight for me is how to connect the game directly with macro behaviour. Basically, the world is one big beauty contest. Both Nagel (focussing more on strategic reasoning) and Hommes (on learning) gave us a picture of how to apply our knowledge of the beauty contest to inform macro debate.
Still on familiar territory for me, David Laibson gave some updated results on present bias. The main focus here is how we can explain the average person simultaneously having a large credit card debt (at high interest) and large savings (at low interest rates). The answer, according to Laibson, is that we have present bias (and are naïve about it). This means we tend to focus on today, putting off difficult things until tomorrow; until we get to tomorrow and then we put it off until the next day. For connoisseurs of this the estimated beta discount factor to explain observed bahaviour is 0.5; which basically means today is a lot, lot more important than tomorrow. This implies that people are going to put off things they should do, like save for retirement, and so there is a remit and rationale for governments to come in and take some control of important decisions.
Another session with a behavioural economics feel was panel 2 with talks by Sam Johnson and Henry Brighton. Johnson gave a great talk on how people may fail to take into account ‘grey swan’ events. The basic idea here is that the person thinks something is reasonably likely to occur, e.g. there is a 20% chance Donald Trump will do a good policy, but when it comes to making a decision they essentially ignore this possibility, they think there is no chance Trump will do a good policy. This can lead to overconfidence or excess pessimism. The thing I would pick up on here is that this presentation, like that of Laibson and others, emphasized some of the ‘dumb’ things humans do. Brighton, by contrast, gave the ecological rationality viewpoint (most closely associated with Gerd Gigerenzer) that humans are remarkably clever at making decisions. I think it is fair to say that Brighton got a tough run in the subsequent discussion with a fairly hostile audience. That surprised me a little because the ecological rationality argument surely has some tractability. Maybe, however, in a conference on trying to avoid another financial crisis the selling point of ‘don’t worry, humans are very clever’ doesn’t seem to offer much of a solution.
And that brings me to my main overall reflection on the Conference, which is perhaps best summarized by ‘where were the macro-economists?’. To be fair, there were some macro people in the room but even they seemed unwilling to go far in defending DSGE modelling and the current state of mainstream macro-economics. I am no macro-economist but I do sense we may be reaching a turning point in the evolution of economic ideas. A turning point in which mainstream macro becomes something of an irrelevance. There is no doubt that macro-economists will carry on churning out mathematical models, publishing in top journals, and celebrating their success. But is this stuff any use? Does it give us anything? This conference was packed with people from other fields who arguably have more to contribute when it comes to predicting the next financial crisis. Maybe policy makers will start listening to them a bit more than the results of the latest DSGE model? If so, that means we are entering a long period of flux before a coherent new macroeconomics is born.
To pick up on one example, I was particularly taken by the role that anthropology can play. Douglas Holmes set the scene in looking at central bank decision making. Then Charles Stafford gave a very compelling argument that economists need to read anthropology. He used the example of Taiwanese fisherman deciding whether to choose the high risk, financially rewarding option or low risk, less rewarding option to illustrate the complexities of decision making (and the role of religion). The title of his talk ‘Economic life in the real world’ sums it up nicely. Economists can learn from pocking their head above the simplicity of our mathematical models to see what actually happens when people make economic decisions. But, lets be honest, it is a long step from conferences like this to building a new macro that incorporates such perspectives.
And then we get to talk of Andrew Caplin which nicely drew together various themes in the conference. Caplin reflected on his work about bank runs financial crises before focussing on the theme of data. He argued that a crisis typically comes about from a ‘predictable’ collapse in confidence. Everyone is chugging along thinking things are bad but maybe it will pick up; then one firm falls and everyone else falls with them. If we could tap into people thinking ‘things are bad’ and understand the linkages between firms then we would have the data to get on top of these things earlier. But are we going to get data? Caplin explained that collecting this data is going to require a long term, big team approach. And that is not what economists are good at. He, therefore, was sceptical it will happen. Let’s hope it does. Either way it seems that rebuilding macroeconomics may take some time.