Philosophy of Economics Crash Course 9 – Finer Details of Discourse


Dr. Alexander X. Douglas‘s biography states: “I am a lecturer in philosophy in the School of Philosophical, Anthropological, and Film Studies at the University of St. Andrews. I am a historian of philosophy, interested in the philosophy of the human sciences, particularly from the early modern period. I am interested in theories of human reasoning, desire, choice, and social interaction – particularly work that questions the foundations of formal theories in logic and economics from a humanistic perspective. I am particularly interested in the thought of Benedict de Spinoza, which continues to inspire alternatives to the dominant paradigm in economics and social science. My first book, Spinoza and Dutch Cartesianism, proposed a new interpretation of Spinoza, situating him in the context of debates within the Dutch Cartesian tradition, over the status of philosophy and its relation to theology. I am completing a book manuscript, which aims to introduce and develop Spinoza’s theory of beatitude. This is the culmination of Spinoza’s theory of desire, since it describes the condition of ultimate satisfaction. Although Spinoza saw the revelation of true beatitude as the ultimate goal towards which his philosophy reached, there are few interpretative works devoted primarily to this theme. Spinoza’s theory of beatitude is, in my view, the keystone that holds together diverse parts of his philosophy – his theory of desire and the emotions, his metaphysics of time, his theory of human sociability, and his philosophy of religion. These are often studied separately; my introduction to beatitude aims at helping readers understand Spinoza’s philosophy as a unified whole. I have also published a book examining the concept of debt from the perspective of language, history, and political economy. I’m interested in the philosophy of macroeconomics, which receives considerably less attention from philosophers than microeconomics. I am a member of the Centre for Ethics, Philosophy, and Public Affairs, the Executive Committee of the Aristotelian Society, the Management Committee of the British Society for the History of Philosophy, and a Research Scholar at the Global Institute for Sustainable Policy.”

In this series, we discuss the philosophy of economics. For this session, we come back after some time with session 9 on finer details on the symptomatology of pseudoscience, “precision” in economics, the copying of the style of the sciences in economics without the content or character of the sciences truly, the idea of rationality or rational choice, assumptions about the applicability of mathematics to behaviours, and utility-maximization as an idea.

Scott Douglas Jacobsen: I decided to make some modifications to the series moving forward since the collapse of Conatus News and the reduced activity and the original recommendation from Dr. Stephen Law while acknowledging the due appreciation to the work in skepticism and humanism of Dr. Law and the recommendation for the collaboration with you. Now, with the transfer and renaming of the series to Philosophy of Economics Crash Course from Q&A on the Philosophy of Economics with Dr. Alexander Douglas, we have 8 parts in total, which, in a manner of speaking, provide a reasonable idea as to some of the boundaries and borders of the discipline of philosophy of economics. What I will aim with the educational series into the future is an appreciation of the finer details of the discipline and some of the radical notions inherent in its work, for example, part 8 examined how the term “pseudoeconomics” does not seem like a useful term at this time. You stated, “I don’t think ‘pseudoeconomics’ is a particularly useful category. To show why, let me say something about pseudoscience in general. Engaging in pseudoscience means aping the concepts and terminology of the sciences without taking on the critical methods that make them reliable. On this definition, to put it bluntly, much of economics is pseudoscience.” In the further analysis, you showed the advanced inclusion of and advancement of mathematics within the discipline of economics does not, by necessity, lead to more accurate predictive capacities of economics as a field. In fact, you make the painful comparison to Intelligence Design with reference to a particular leader in this theological field with “Michael Behe” based on “irrelevant probability equations,” as a “symptom of pseudoscience.” What are some other symptoms, the “finer details,” of economics leading to a symptomatology of pseudoscience?

Dr. Alexander Douglas: I think there is a lot of work going on in economics departments and think tanks that is useful and productive for society – especially empirical studies that simply gather useful data. It’s very helpful, for instance, to know how many people are really struggling to find work and why the headline unemployment figures are misleading in this regard. It’s useful to know how people in different economic categories are at different risks of illness and other problems. But this is, it seems to me, mostly research that anyone with a statistical background could carry out: medical researchers, for instance. I’m dubious about how connected that work really is with what a philosopher of science might call the ‘research programme’ of economics. The research programme involves using very complicated mathematical models to predict the outcomes of various social interventions, based on strong assumptions about human behaviour. These assumptions are either axiomatic: derived from a certain conception of rationality that then became encrusted within the discipline, or based on studies of people under clinical conditions, with probably no more relevance to behaviour in the real activities of human life. In any case, I’ve shared my reasons for believing that there’s no real way to scientifically test any of these assumptions, even in a clinical setting.

Jacobsen: You remarked on Alexander Rosenberg’s analysis of economics as ‘lacking predictive precision.’ What is defined as “precise” within the remit of economics? How does this definition of “precise” compare to other notions of precision seen in other fields, as a contrast justifying the aforementioned “lack of predictive precision” described by Rosenberg in 1994?

Douglas: Rosenberg’s book uses research by Leontieff from the 1980s, which showed that economists could at best only predict the direction of a trend: e.g., will the price of something go up or down following this change? Natural scientists can usually do much better: they can estimate how quickly something will change and how long the change will last. But that’s old research, of course. Noah Smith wrote a reply to a more recent piece by Rosenberg and Tyler Curtain, arguing that economics does have some predictive power. He gave two examples; one of them is as follows:

My favorite example is the story of Daniel McFadden and the BART. In 1972, San Francisco introduced a new train: the Bay Area Rapid Transit (BART). The authorities predicted that 15 percent of area commuters would use the system. But, using money from a grant provided by the National Science Foundation, University of California, Berkeley, economist McFadden and his team of researchers predicted that usage would be only 6.3 percent.

The actual number? 6.2 percent.

Of course it’s bad data science to infer too much from one or two examples. Also, from what I can tell McFadden’s more successful model basically took existing data and ran it through an algorithm to make predictions. His algorithm was described in economists’ terms: preferences, choice, utility, etc. But McFadden himself later pointed out that the algorithm is itself a ‘black box’: it doesn’t matter what it implies about human psychology or choice, it just needs to output the right results mathematically. So was his model really a success for economics, or just for applied mathematics? That’s to say, McFadden certainly chanced upon a good algorithm, but did the economic theory of preferences, utility-maximizing, and so on really help, or could a non-economist with a decent maths background have managed just as well? I’m not in a position to say, but I certainly don’t think Smith’s couple of examples are typical of the level of predictive precision found in economics, otherwise McFadden wouldn’t have got so famous for getting so close to the true value in this case.

Jacobsen: With the ‘copy of the style and not the substance’ of the sciences in economics, is this reflected in not only the inflated mathematical language and models but also the forms of verbiage or patois found within the field of economics?

Douglas: Yes, I think so, definitely. You might remember the outrage around White House advisor Kevin Hassett using the term ‘human capital stock’. People took him to be referring to workers, but ‘human capital’ generally refers to the skills and abilities of workers. Hassett was perhaps trying, in a hamfisted way, to make the point that those skills were spare capacity that had been laid aside and it was time to reactivate them. But you see these sorts of terms everywhere in valuation statements. Key financial decisions are made on the basis of these careful calculations of value, and finance people have to record everything as an asset: even goodwill is an asset with a numerical value. This makes the valuations seem so much more scientific and precise than they are: if you think a company should be more valuable than whatever you get by counting up the normal assets, you can always stick a bit more into the goodwill. So long as shareholders are willing to invest in the company at a certain value, that justifies the assignment of goodwill value, and, circularly, the full valuation including the goodwill assignment affects what people are willing to pay for the company.

The false precision is doing some crucial work here, and this terminology always originates in economic theories. Economics and finance amount to a sort of metaphysical theory: an ontology that divides the world into assets and liabilities with definite values to be estimated. The ordinary world as it appears to us doesn’t really fit into that model, so I do think this a sort of metaphysical theory that ‘cleans up’ reality to fit it into a form that allows capitalism to work. It’s different, I think, from a particle physicist’s model, which admittedly doesn’t match reality as it really is but is close enough to track some real phenomena. When a pension fund enters a valuation, people think it’s a valuation of the pension fund, not some abstract model of a pension fund.

Jacobsen: When speaking of utility, utility functions, utilitarianism, etc., there seems to be a premise of some objective trait of human nature assumed in the framework. As you note about Joan Robinson, does this seem to reflect a trend of superficiality, reification, circularity, and subjectivity within the fundamental concepts and lever points of economics? An attempt to grope towards the objective while lacking the “substance” to do such a maneuver.

Douglas: Yes, absolutely. Economists generally say these days that by ‘utility’ they only mean the maximization of preferences – people choose what they most prefer, given known constraints. And how do we know what they prefer? By observing their choices! At this level the theory is, of course, trivial: it tells you that people choose what they are observed to choose. But you can add some other assumptions about preferences: for instance, people’s preferences don’t change, so you can infer what they’ll choose from their previous choices. That gives you predictive power; it also strikes me as an obviously false psychological theory. Economists can only avoid having it falsified by adding so much noise into the environmental factors that any apparent change in preferences can by some subtle difference in the situation. I know that there is work, by Herbert Gintis and others, proposing that we might one day use evolutionary science to get better data on how people’s preferences actually form and change. It’s hard to judge that before any data has really been gathered. But I’ve explained in previous interviews why I think this might be misguided in any case: preferences range over objects under certain descriptions; the things that scientists – even evolutionary scientists – can study are only the objects. If I hold out an apple and an orange to you, are you choosing between an apple and an orange, or a red object and an orange object, or what is in your left hand and what is in your right hand, or what it is polite to take in China and what it is polite to take in the UK, or… I just don’t see how straightforward observation, even accompanied by evolutionary theory, can pin this down in a strong enough way to make good predictions.

Jacobsen: What is a “rational choice” or “rationality” in these aforementioned senses in economics with the apparency of pseudoscience built into it?

Douglas: Yes, rationality is just the name for the behavioural model that’s meant to output actions from choices. It’s pseudoscientific because it’s never been tested. It couldn’t be less like the Standard Model in particle physics, for instance. Anyway, the Standard Model is a model of things that really do seem to react fairly algorithmically to measurable changes. Human behaviour doesn’t even seem like that.

Economists are sometimes vague on whether they want us to accept their theory of rationality as an instrumental aid to prediction, a ‘black box’, as McFadden put it, which somehow outputs accurate predictions, or something that we really recognise as governing our behaviour. I find that the scholarly literature often presents it as a ‘black box’ whereas textbooks suggest that we really do think and act according to the economist’s definition of rationality. Itzhak Gilboa has a textbook in which he defines rationality in terms of choices that you wouldn’t be embarrassed to have made even if the reasoning behind them was explicitly explained. Technically this seems circular to me: you’d need to be rational, in the way described, to be embarrassed by reasoning that doesn’t follow that way. But I think it reveals something important: rationality, on the economist’s conception, seems to involve some normative element. Being rational is something to be proud of; being irrational is something to be ashamed of. There is a hint here of what Joan Robinson said many times: ostensibly scientific economics is often ideology in disguise.

Jacobsen: You stated, “Simply assuming that the results of a branch of applied mathematics have any relevance to the behaviour of a physical system – that’s pseudoscience rather than science. It has the outward elements of much modern science – mathematics and observation. But it fails to connect them together in the manner of a proper science.” Why do economists, very likely, consistently make these ‘assumptions’ about the application of a branch of mathematics to the “behaviour of a physical system”?

Douglas: Quite simply, the behaviour of physical systems can be predicted and therefore manipulated. It’s highly significant that Optimal Control Theory – a branch of mathematics developed to help engineers control physical systems – was reborn as a foundation of modern macroeconomics after it reached its limitations in physical engineering. Economists are largely funded by people who want their help in controlling human systems: to engineer certain social results for political purposes or for pure private gain. If economists conducted themselves like anthropologists I doubt they’d have the ear of politicians and businesses, and so they would lack their social standing.

Of course academic anthropology developed in the context of control as well: the colonial powers wanted to understand the peoples they colonized so as to better ‘manage’ them. But the disconnect between what anthropologists were learning and what those in power could use became apparent pretty quickly. Its approach to understanding human behaviour gave only a feeble promise of control. Economics, by contrast, promises something very appealing: it represents human reality as system of computations – agents solving mathematical optimization problems, computational units solving arbitrage equations – in short, a giant computer. Computers can be programmed by those who understand their operating systems, and that’s a very enticing promise to those who can afford the services of the programmers.

Jacobsen: Does this “utility-maximization” conceptualization of human behaviour simply fall apart because of the noted subjectivity of the concepts and the futile, unnecessary complexity and use of mathematics in its models?

Douglas: Yes, I think so. The theory is always trying to walk the tightrope between falsity and triviality. Economics textbooks often go for the ‘wow’ moment when introducing utility theory: ‘Here’s how your son picking a fight with your daughter can be explained in terms of utility-maximization!’ At first you’re impressed, then you start to wonder how a theory so consistent with everything we observe can really help with prediction. Humans seem to be capable of just about anything, so if utility theory explains everything they do then it can hardly help us to know which of the many things they can do they will do.

Jacobsen: Dr. Douglas, thanks for your time today.

Douglas: Thank you, again – always a pleasure.

Previous sessions:

Philosophy of Economics Crash Course 1

Philosophy of Economics Crash Course 2

Philosophy of Economics Crash Course 3

Philosophy of Economics Crash Course 4

Philosophy of Economics Crash Course 5

Philosophy of Economics Crash Course 6

Philosophy of Economics Crash Course 7

Philosophy of Economics Crash Course 8

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