By Alan Kirman, David Bassett, and François Claveau
Alan Kirman is professor emeritus at l’Université d’Aix-Marseille III and researcher at GREQAM (Groupe de Recherche en Économie Quantitative d’Aix-Marseille). He has published over a hundred academic articles and edited and authored many books including noted monographs on general equilibrium analysis and most recently Complex Economics: Individual and Collective Rationality.
In this interview Professor Kirman discusses his understanding of the relationship between individual behaviour and aggregate patterns, why it is essential to consider the interactions between agents, and what the study of ant’s behaviour can teach us about collective human actions. The interview also ranges more widely, discussing the different goals of economics (for instance, explaining, predicting, and controlling), the role of mathematics in modern economics, and the state of macroeconomics.
David Bassett and François Claveau: What brought you to economics in the first place and how would you describe your research in the early years of your career?
Alan Kirman: Well, my story is a bit weird because I started out after my first degree at Oxford as a school geography teacher. But I found myself asking: “Do I want to do this for the rest of my life?” I went to some evening classes in economics organized by the Workers Educational Association, and I thought: “Oh, that is really interesting. Maybe I should try and do something with this.”
I first did a one year diploma (part of it on international economics) at the Johns Hopkins School of Advanced International Studies in Bologna (Italy). One of the people who were teaching there, Ira Scott, gave me a recommendation to do a PhD in Minnesota, so I took off to Minnesota the year after. There, it was very cold and extremely mathematical. But I had done no math before, so my advisor Hugo Sonnenschein told me I had to do a degree in math as well.
By spring, I thought that this was not what I came there to do. For me, economics was about unemployment and inflation and so on, and yet here I was struggling with fixed point theorems and all that stuff. I said to Hugo: “Look, why couldn’t I do these other things?” He said: “No, no, that is macroeonomics, and macroeonomics is about wisdom. Microeconomics is about analysis, and young people should do micro”. Anyway, I got a fellowship to go to Princeton, where I thought I was going to do more real economics. Once there I looked around at the people who were teaching and by far the most interesting and inspiring teacher was Harold W. Kuhn, who was—unfortunately for me—a professor of mathematics and also a professor of economics! So I did my thesis with him, applying non-cooperative game theory to international trade.
Afterwards I moved into general equilibrium. I worked on a lot of other things too in my early years, because, you know, general equilibrium is not very inspiring. I mean, it is a great intellectual game, but it is so mathematical. So I worked on fairness, social choice, a bit on international trade—lots of different things, nothing very deep, and that is how I started out.
Your book is called Complex Economics. Many economists in the last twenty years or so have endorsed similar labels. What does ‘complexity’ amount to? How did you shift from general equilibrium to this other project?
The Journal of Mathematical Economics was first published in 1974. Hans Föllmer—a mathematician in Bonn at the time, later in Zurich, and now in Berlin—had a paper in the first issue of this journal which was called “Random economies with many interacting agents”. He showed there that if you have lots of people who have their regular preferences and so forth, but those preferences are influenced by their neighbours—like particles in the Ising model from physics— that could destroy the underlying notion of a unique equilibrium or, put alternatively, that you could not say much about the aggregate once you had this interaction.
I started to think about interaction models and talked to Hans about that but I was not imaginative enough. Then I met a mathematician from Warwick called David Rand and we had a long discussion about whether we could think of demand differently, with each individual’s demand being influenced by the demands of his “neighbours”.
I think this was when I started to think of systems where you have these really quite primitive individuals interacting. That is what came to underlie my view of complexity: lots of rather simple individuals who by their interactions generate phenomena at the aggregate level that do not coincide with what you see at the lower level. In economics typically, we make a short-cut: we just assume that what is going on up there looks like what is going on down here.
You reject the standard rationality assumptions in economics. What are your reasons for doing so? What are the substitutes?
Those axioms—and you can find a whole series of people from Pareto onwards who make the same argument—come from economists’ introspection and what they think is necessary for their work, not from observation of what people are doing.
Some of these axioms seem natural, at least at first sight. For example, transitivity seems a natural idea—if you prefer A to B and B to C, you also prefer A to C. But if you look carefully at how economists define the things over which you are making choices, you could never observe whether or not an individual is making transitive choices.
My main problem is that none of these axioms is taken by observing lots and lots of people. In other disciplines, that is what you do. You look and then you try to develop a model which might explain what you observe. In economics, we started out by doing the formalization and building models which were internally consistent but often far removed from reality. To construct models which we could analyse formally, we needed to make some formal assumptions. As I said, many scholars starting with Pareto basically made the same remark: these assumptions are somehow not natural, they are not about what people do, they are more about what we need in order to pursue our analysis. So that is my real objection.
What do you replace that with? Do you just say that people just make arbitrary random choices? Well of course not. The argument I would make would be that, in some sense, people see directions in which they think their welfare improves, and they try to move in those directions. A simple way to model this is to give simple rules to agents that you find plausible and then look at how that works. In such a model, people are not irrational, but rationality must have a much more open definition.
You display some sympathy with the project in behavioural economics to supply psychologically-refined assumptions regarding economic agents. At the same time, you assert that we have much to learn from studies of ants, bees, and other social animals which can be modelled as acting based on simple behavioural rules. Are these two lines of inquiry—refining the psychology of our modelled agents and looking for simple behavioural rules—not in tension?
The distinction is really the following. Say that I observe people behaving in certain ways and that together they are generating some aggregate pattern. I say to myself: “Can I think of this phenomenon in terms of the rules people are following without worrying about their intentions for the moment?” That is like the ants phenomena, in the sense that the ants are interacting in very simple ways.
Now you might say that you are interested in why they act like that. Why are they following these rules? One can say that evolution has led them to select the rules that they follow. This is what is often said about ants. Yet Deborah Gordon, a famous entomologist has collected a mass of evidence to show that quite often ants are individually inefficient and fail to do what they are trying to do. Although they achieve a lot, they do not seem to be behaving optimally in any standard sense. I think economists have bought in too easily to the unsophisticated evolutionary arguments. Her advice to people who argue for optimal behaviour is “spend time watching ants”. The same advice could be given to economists, “watch economic agents!” Thus, when we are looking at human beings we probably want to know much more than that they seem to follow, in general, simple rules and we want to look at the psychological side of things. That is why I have been interested in neuroeconomics and published a couple of articles on that.
So I do not think there is a contradiction. When we are interested in humans we are not only interested in knowing which rules they follow but also why they follow these particular rules and why they often seem to behave non-rationally. This would be my distinction.
The term ‘collective rationality’ is in the subtitle of your recent book. What do you mean by it? How does it relate to our usual understanding of individual rationality?
Well, I am not happy with ‘rationality’. One of the problems that we find is that people have now somehow absorbed the economist’s notion of rationality, so that when people say ‘rational’, they immediately have in mind something like what economists define as rationality. In fact, rationality can be thought of in many different ways.
Rationality for me would mean something more like coherent or interpretable behaviour; behaviour that is not just random. So ‘collective rationality’ would mean that in some sense this group or society moves in a way that you can observe and anticipate and seems to be purposeful—although I do not want to insist too strongly on ‘purposeful’ because it is not clear that the aggregate has purposes. In this sense, ‘collective rationality’ could well be applied to a physical system, where there is clearly no intention involved. Take a system made of physical particles. The system’s basic tendency is to minimize its total energy. One might want to say that the system tries to reduce its energy, but it is not intentional. The system does not have an intention but you can still observe it minimizing its energy and that is something that is well defined. In the end, what I am after is perhaps more a sort of collective coherence rather than rationality.
Some might conclude from a discovery of ‘collective rationality’ that it is acceptable to simply use techniques that concern themselves with analysing the aggregate level only. Since connecting the behaviour of individuals to macro-patterns is so difficult, such an approach is certainly analytically appealing. What would you say of such an alternative?
Actually, this alternative is in the spirit of the old macroeconomics where we used to have relationships between aggregate variables, and then you have things like Goodwin’s business cycles. It is not an illegitimate activity to think in terms of aggregates. You do not necessarily have to be interested in explaining aggregate relationships in terms of individuals. Central bankers actually often look at rather simple aggregate relationships without worrying about what it was that motivated people; and they do not even try to derive the aggregate relationships from underlying models. For many purposes (particularly policy purposes), focusing on simple aggregate relationships may even be better than worrying much about all the mechanics of the economy. You may also be interested in the mechanics, but for certain purposes it may be perfectly legitimate to want relationships between aggregate variables. To use a familiar metaphor, you do not have to understand the mechanics of a watch to be able to understand the regular movements of its hands.
You often use the term ‘emergence’ in your own work. What do you mean by it? Among the many interpretations of emergence in philosophy, at least one, the irreducible-pattern interpretation, seems to imply that one would not be able to analyse some aggregate-level, emergent properties in terms of the interactions of units at a lower level (e.g., individuals). But your strategy seems to be exactly that. Why should we expect the study of individual-level interactions to be a fruitful way to analyse aggregate-level properties if the latter are deemed emergent?
I am not a philosopher, so I do not know much about these things, but if you look back, people who were at the interface—J. S. Mill, and people after him—were interested in exactly this distinction between what is happening at the different levels. My primitive, non-philosophical, feeling is that it is not a distinction between looking at the individuals and then looking at the interactions between them. What generates the difference at the aggregate level is that individuals are interacting with each other. So I cannot take that individual, examine him (the way he behaves and his decisions), and conclude from that what the crowd will do. I cannot because I am eliminating the essential part which is the interaction. I would say it is the individual characteristics plus their interaction which generate the activity up here, which has different characteristics from the specific individuals. It is the fact that one cannot derive the aggregate property from adding up the behaviour of individuals that makes aggregate phenomena ‘irreducible’, I think.
One main argument—if not the main argument—in your recent book is that “direct interaction between agents plays a crucial role in determining aggregate outcomes”. What is so “crucial” about it? Is it that direct interaction is more “crucial” than other elements—e.g., the behavioural rules of the agents themselves?
Well, when you come to economics, at the start you are told it is about the distribution of scarce resources amongst competing needs, or whatever—they give you a definition. And you say, well how is this achieved? Well, we are told, this is achieved by people trading with each other and collectively that leads to outcomes that have certain properties. But then you say to yourself: “trading with each other, how is that organized?” And they say: “Well, it is through a market. There are some prices which are given and then everybody uses those prices”. Yes, but who trades with whom?
In the standard model, the part where people meet each other, trade, and so forth—in which things happen—is just missing. As soon as you start to think about it, you realize that, if people are interacting with each other in markets, what one person is doing will influence others. For instance, when I meet someone and he tells me that he is buying an asset, that would probably influence what I think of its prospects.
All this interaction seems to me important, and yet that is something that we just push under the rug in the standard set-up. There are very few markets where the actual mechanism of dealing—the actual influence of one person on another—is not important. If you want to understand economic activity you cannot lay aside the fact that it has to happen between trading partners.
The typical way of modelling interactions between agents in economics would be to use game theory. But you express some dissatisfaction with game theory. Is not game theory more flexible than you depict it? Do your criticisms apply as well to evolutionary game theory for instance?
If you read Binmore’s Essays on the foundations of game theory (1990) you will find a section where he says that, unfortunately, we get into a kind of impasse. We get this infinite regress linked to the common knowledge problem. For example, I drive frequently from Aix to Marseille. You have the autoroute and parallel to it is the route nationale. Say there is, one day, congestion on the autoroute and nobody on the nationale. I think: “Tomorrow I will take the nationale. But, wait a minute, these other drivers are intelligent too, so they will take the nationale tomorrow, I would do better to stay over here. But, wait a minute, these drivers are pretty intelligent so they can make that step too…” It is actually not logically possible to reason to the solution of these kinds of problems that people are supposed to be solving in game theory.
You can surely define an equilibrium, and say that if we were there nobody would want to move. But then you get to the problem of how we get to this equilibrium—the exact same problem that we have with general equilibrium.
One way out is evolutionary game theory, which does not have people reasoning. You simply identify individuals with strategies, and strategies that do better reproduce more, while strategies that are doing worse disappear. That is extremely mechanical; it drops any reasoning on the part of individuals and, as I said earlier, it relies on too simplistic an interpretation of evolution.
For certain specific, local problems, game theory is a very nice way of thinking about how people might try to solve them, but as soon as you are dealing with a general problem like an economy or a market, I think it is difficult to believe that there is full strategic interaction going on. It is just asking too much of people. Game theory imposes a huge amount of abstract reasoning on the part of people—far more than in standard economics where you only need to know the prices and your own preferences.
That is why I think game theory, as an approach to large scale interaction, is probably not the right way to go. But I still think that a really important insight comes out of game theory: as soon as people start to worry about the fact that what they do has an impact on what other people do (and they start to think about it), that makes life very different.
You favour agent-based modelling as an alternative method to study agents’ interactions. Can you sketch the characteristics of this method?
There are two possible approaches to agent-based modelling. The first approach is to start with a very simple, rudimentary model that can be solved analytically. Then you generalize it and simulate this more general model. We know the analytical results in the simple model and the question is whether these results continue to hold in the less restrictive model. You find such an approach in the chapter on fish markets in my book. In the simple model with two sellers and many more restrictive assumptions, we worked out analytically whether people increase the probability of going to the seller from whom they made the most profit in the past. Then we ask what would happen if we tried to generalize the model. Since the results can no longer be derived analytically, we simulated what happens.
The alternative approach—the artificial life approach—gives people pretty much arbitrary rules to start with, and lets them choose different rules as they go along, and then you see if anything emerges from that. That was the Santa Fe stock market approach: throw these individuals into the pot and then you look at the soup and see if anything has happened.
An objection to this second approach is that you have so much freedom. You can choose completely arbitrarily the very basic rules that you give people to start with. David Colander at some point raised this objection. He said that, if you are reasonably clever, you can just give the right rules to get anything you want to come out. So a legitimate objection to a lot of agent-based modelling nowadays is that the specification is often not justified; one just puts down rules which seem intuitive.
In your book, one finds a lot of terms like ‘understand(ing)’ and ‘explain(ing)’. In contrast, you seldom use terms like ‘predict(ing)’, ‘forecast(ing)’, ‘control(ing)’, ‘intervening’ and ‘policy making’. What would you reply to someone who believes that economics is primarily in the business of predictions and policy recommendations and that, while your enterprise is perhaps valuable for explanatory purposes, it is of little use in the pursuit of these goals?
My wife says the same thing to me. She says: “Whenever you talk, I always have the feeling of somebody who is looking at an ant nest or a beehive and is very interested in what is going on in there and is really curious about it, but is not particularly worried about making it work better. In some sense, you are a curious observer rather than someone who is actually in the business of doing something”. I think that is a legitimate criticism. I do not know whether that is my nature or what. I just find these things very interesting. I reason a little bit like an entomologist.
So, on forecasting, if you believe in this sort of systems approach, forecasting is a very difficult exercise. Just look around now at people forecasting, and people have these big, very sophisticated models. But, when you look at the discussions about what the growth rate in the European Union will be, or the growth rate in the United States, say, you see how quickly these things are revised. From one month to the next, the French government says: “Well, we have come down from 2.5 to 1.7”. Is that not a big change? It is, in fact, a very big change; it makes a huge difference in terms of what we had better do with the deficit, and so forth.
I think we will do much better by looking at the nature of the evolution rather than trying to predict “this is going to happen”; trying to say, would this type of change that is happening lead to a more positive evolution or a more negative evolution? That is something we can probably say something about, but saying that the growth of GDP will be 1.2, 2.3, or whatever, I just think we are not in that game.
In using this stuff to actually make policy recommendations, I think one has to be pretty modest. In fact, I am not sure how much it is really about using economics and how much it is a matter of having a vision of the world. When Hugo Sonnenschein said to me that macroeconomics was about wisdom, well, I have come to believe more and more that he was probably right. In some sense, macroeconomics is a lot about experience and rather little about formal analysis. But that is just a personal view, and a bit of a cop-out—a way of saying: “Sorry dear boys, I cannot do this!”
We also want to ask you about your feelings toward the use of mathematics in economics. Many heterodox economists argue that there is too much mathematics expected of economists, and that the profession has become obsessed with being overly formal. How do you think economists should use mathematics?
I find it strange that we should worry about a tool, that this tool should somehow be a criterion for judging work or be the subject of criticism. Mathematics is just a way of simplifying a problem, perhaps wrongly at times. John Chipman did a survey of international trade theory at one point, which was published in Econometrica, and there he says that sometimes mathematics turns out to be useful because it enables you to frame things in a clearer way. For him, solving certain problems in economics without mathematics is a bit like crossing the Channel by swimming. It is an admirable feat and everybody applauds it, but it is probably not the easiest way to cross the Channel. So, in a sense, avoiding mathematics in principle does not seem to me to make any sense. But becoming obsessed with mathematics does not seem to make any sense either.
In fact, I do not think the real issue has to do with mathematics and non-mathematics. Mathematics is just a tool, and really whatever tool that you can find around, well, that is fine. But somehow there is now a hierarchy, and mathematics is thought to be a superior thing to do. Recently, in our group, they refused a PhD student that I wanted them to take because she did not have hardcore training in mathematics. And she had done courses in business and so forth and wanted to work on behavioural finance. But they said: “This is not a serious person”. This in my opinion is a very poor criterion, because her making some progress on this particular problem does not necessarily require her to be a mathematician. There are lots of people around, like Akerlof and Bob Shiller, who do not use very high-powered mathematics, but do have good insights.
Many of my colleagues think that Schelling should not have won the Nobel Prize. When I ask them why, they say, “there is almost no math in what he does!” And it is certainly true that he does not use difficult mathematics. But he has difficult and really interesting ideas. Why should I judge him on the mathematical tools he uses?
Years ago, I was involved in organising conferences with Christopher Zeeman, who was one of the founders of catastrophe theory and the head of the mathematics department at the University of Warwick. He used to organize rencontres between mathematicians and people from other disciplines, and we organized one between economists and mathematicians. We had some great mathematicians—John Milnor, Steve Smale, Rene Thom, and others—wonderful mathematicians. And on the other side, we had Gérard Debreu, Hugo Sonnenschein, Werner Hildenbrand, and a whole group of very distinguished mathematical economists. After the first two, three hours, I think it was Milnor who said: “We all know that you guys can do mathematics, you do not have to show us. Everybody does his own thing. You want to show us that you are good at doing certain sorts of mathematics; that is fine. But we are interested in the economic problems. We thought that you were going to tell us about economic problems and we were going to use our mathematical tools to help you. But all you are telling us is the mathematical tools that you use and how you are doing well with them. But that is not going to create much”. I think that was absolutely right. After that, the economists were rather silenced and started shifting in their seats uncomfortably. Debreu never said very much anyway, but it was clear he was very insulted, because basically he liked to think of himself as a mathematician.
Is it possible for you to summarize your diagnosis of the state of macroeconomics?
I would say that macroeconomic theory has gone down a blind alley in the sense that we have locked onto a particular model: general equilibrium. But it is not really general equilibrium, I mean, it is a oneman model! In particular, it has become mathematically sophisticated without representing the fundamental features of the macro-economy.
So I would say that people like Kydland and Prescott, and so forth, people like that, deserve their Nobel Prizes because they changed the way that people do macroeconomics. But in my view it was not a positive change. I think we have gotten away from worrying about the macro-economy as a system with interdependence, and so on, and become obsessed with this particular vision of how it works. One predominant idea is that of external shocks—and in particular the idea that the shocks that happen to the economy should essentially be the technological shocks. As Joe Stiglitz said, what could we mean by a negative technological shock? That people forget what they could do before?
So we have this idea that we have a system which is in equilibrium and that every now and then it gets knocked off the equilibrium by ‘a shock’. But shocks are part of the system! We have gone down a track that actually does not allow us to say much about the real, major movements in the macro-economy. In the end, we should be more interested not in the periods where the economy is running along relatively smoothly, but in the periods where it changes. People typically say: “Well, this is not a normal period, and we analyse what happens in normal periods, and all of this is about deviations from that”. But we should be studying non-normal periods, instead of normal ones, because that is what causes real problems. And we do not do that.
So my vision of the state of macroeconomics is that it somehow has the wrong view: an equilibrium view and a stationary state view. But what is important and interesting about macroeconomics is precisely when those two things do not hold. How can you talk of equilibrium when we move from 5% unemployment to 10% unemployment? If you are in Chicago, you say “Well, those extra 5% have made the calculation that it was better for them to be out of work”. But look at the reality; that is not what happens. People do not want to be out of work. It is a tragedy for these individuals; it affects their identities. It upsets me a lot to think that people just say: “Ah, only another 5%; we handled this rather well”. Millions of people are out of work, and we are not worried about that?
That is the major failure in macroeconomics. It does not address the serious problems that we face when we get out of equilibrium. And we are out of equilibrium most of the time.
That was the diagnosis, so now what treatment would you propose? And how do you think the profession should reform?
Ah, the profession. Well, as Buzz Brock says, we should open our minds, but not so much that our brains fall out. I think that we should take on board all sorts of different approaches to macroeconomics and to looking at how markets function. We should start to incorporate empirical evidence, rather than getting obsessed with extremely limited models. We should try to keep thinking about all these things that impact on the economy and see whether we can incorporate some of them, and maybe drop some other ones. We should not be totally focused on producing a closed-form model that you can solve and then say that it is a representation of what we see out there. If you do not look out there, this model will always be detached from reality.
That is a criticism of the profession. If you want to succeed, you have to publish in good journals. What the good journals publish are basically advances on previous work. That is absolutely reasonable, and it is understandable that the profession should have a lot of inertia in it. But it also should not be so locked in that anything that is more innovative cannot get into these major journals. I think, if you look at the American Economic Review, it is actually not really so bad, because it does incorporate quite a lot of behavioural economics, experimental economics, and so forth. But in macroeconomics, I think, it is extremely conservative. If you produce a model which is not in line with what was being done before, it is very difficult to publish.
There was this young economist, I think he was at UCLA, who wrote to me when I wrote this paper called ‘Whom or what does the representative agent represent?’. He said: “Dear professor, I really agree with what you said. I think that it is intellectually absolutely right. Unfortunately, I am a young macroeconomist who is an assistant professor. I build models based on a representative agent. I know how to do that, and I know how to publish that. And I need to get tenure. Once I have got tenure, maybe I will be able to turn around and start to think about the sort of models that do not use the representative agent, but unfortunately, what I think will happen is that by then I will have got into the habit of doing it. I will publish my articles, get a decent reputation, I will get promotion, and I will probably never think about this again. But anyway, thank you very much for the insight!”
That is a bit depressing!
No! I thought that was extremely honest. That is just the way it is. It is very difficult. Curiously enough, places like the Journal of Political Economy allow for Schelling-type models and so on every now and then. So it is not true that the profession is a solid block against anything innovative. But there is a natural suspicion of things that cannot be reduced to a standard equilibrium.
So what reforms are necessary? Well, the way that the profession reacts is to create new journals, right? For example, from the outset I was involved with the Journal of Economic Behavior and Organization, which was really considered a marginal, weird journal. But nowadays it is a very acceptable journal; it is well thought of. That is the way that these changes will happen. I would like to believe in pure natural selection, but I think that there is a lot of inertia in the profession.
Every now and then I get invited to conferences in neurobiology. There people are really interested by what they are doing. Once they start telling you about what they are doing, you know, you just cannot stop them. But in discussion at economics conferences, it is usually about who is going to get a promotion where, who published in this or that journal. We should change that.
If you go to an experimental economics conference, it is more like that. They are more excited about what they are doing. But if you go to a macroeconomics conference, all you want to do is get out! It is the price you have to pay. You have to be there. They are all there, listening very seriously to each other.
So ultimately, are you optimistic or pessimistic about the profession’s future?
Well, as Keynes might have said, ‘in the long-run’ I think that things will get a lot better. I think that people will realize that economics is a wonderful and exciting subject and they will stop treating it as an analytical exercise which is independent of reality. A lot of people do empirical work of course, but not imaginative, exciting empirical work. Often it is rather routine. But I have more sympathy for the individual who gets down and starts to analyse some data for a particular market—the market for wheat or something—and really looks at how it works, than I do for the person who builds the n th-generation DSGE model. I think that the first individual is trying to understand what is going on. The tools that he uses may not be super exciting but he adds to our understanding of the economic world. That is what it is about. That is what I thought when I came to economics, I thought: “this is really about understanding how economic phenomena happen. What a wonderful, exciting subject”.
David Bassett is a Research Master student in philosophy and economics in the Faculty of Philosophy at the Erasmus University Rotterdam. François Claveau is a PhD candidate at the Erasmus Institute for Philosophy and Economics (EIPE) and a co-editor of the Erasmus Journal for Philosophy and Economics.
Originally published at ejpe.org.
2016 October 16
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