Psychology and economics are both attempts to study human behavior. While the precise focus may differ, we want to be able to make precise and accurate predictions about how humans respond to stimuli. We can use reasoning to make theoretical predictions about what will occur, and use empirical results to confirm or disconfirm them, or use empirical results to guide what our theory should be. You must have both, however.
I argue that economics is far better than psychology because it has a theory. Psychology does not. It is the fitting of epicycles to match observed empirical phenomena. If published research were an unbiased reflection of reality, this would be a distinction without a difference, but published research is distorted and obviously distorted. Psychology is a science without priors. They are left chasing the newest paper, without the slightest idea why it should be true or not true. Its only test of plausibility is whether it can tell a plausible story rationalizing the results. The funny thing about stories, though, is that you can spin a story to fit any particular set of facts. It is, moreover, in principle not possible to say what causes what without theory when looking at data sets after the fact. A randomized controlled trial (where people are assigned some treatment at random) can sort out that some treatment caused an effect, but for many interesting questions we can only observe data sets after the fact. As this paper proves, you cannot establish what causes what without a theory, without a prior.
Consider the example of priming. Priming, since debunked, is the idea that making people think about certain things will unconsciously affect their behavior. People who read a text about being old would supposedly walk slower after reading it. It is striking that it would be perfectly plausible to rationalize the exact opposite effect. You find that they walk faster – perhaps because they were reminded of their mortality, and walk faster to remind themselves of youth. You don’t have a sound sense of what would be confirming evidence, and what would be surprising evidence.Research will go on until a significant, publishable result is found – and so you end up with spurious claims on pointless questions.
This is not merely my complaint. Psychologists, surveying their own field with disappointment, agree. Muthukrishna and Henrich (2019)write, “Rather than building up principles that flow from overarching theoretical frameworks, psychology textbooks are largely a potpourri of disconnected empirical findings on topics that have been popular at some point in the discipline’s history.” They go on, “outside of psychology, useful theoretical frameworks tell scientists not only what to expect, but what not to expect.” To quote from Poincare, “Science is built up of facts, as a house is built up of stones; but an accumulation of facts is no more a science than a heap of stones is a house.”
I suspect that psychology is like this because it has its intellectual origins as clinical practice, in an era where medicine had only the scantest idea what to do, and knew still less why things worked. Reading Paul Meehl’s polemic against case study conferences, one is struck by how much of a psychologist’s work is still one to one. He, a professor with a sound footing in statistics, still gave ten to twelve hours a week in private psychoanalysis. Psychology even now has not fully shifted over to being statisticians.
ii. Why economics?
Economics has a core set of theoretical claims that can stand on their own. We can explicitly state our assumptions (generally, what people or firms are trying to maximize) and then show precisely how they can maximize it. Our work on how to optimize an auction requires no experimental proof whatsoever – it stands on its own. So too does much of microeconomic theory. How a monopoly could maximize their profits is simply proven – there’s no other method which maximizes revenue.
And this theory can meaningfully guide what we research. A paper that comes to mind is Ben Bridgeman’s “Competition, Work Rules, and Productivity”, as it could never have been made without a sound theoretical foothold. Suppose that there is a firm with some degree of market power – while not perfectly a monopoly, they are able to get rents. (Rents, in the context of economics, are profits in excess of what would be earned in a perfectly competitive market). Labor unionizes because they wish to divide the rents between them and the firm in some way. Crucially, the union is able to control wages and the number of people hired, but is not able to control output. Under these assumptions, it is optimal for the union to insist upon hiring some people who add nothing to production – what is called “featherbedding” – rather than simply maximizing their wages. A change in wage changes the marginal cost of producing a good. Firms would be incentivized to reduce their total production, in order to claim more rents for themselves. Requiring a certain number of people to be hired changes it to a fixed cost. The marginal cost of producing additional outputs is kept nearer the competitive outcome.
That’s it! That’s all you need! You do not need to appeal to theories of solidarity across workers (which is not so much an explanation as acknowledgement of the facts – you cannot make meaningful predictions about where and why “worker solidarity” would vary). Everything follows from conventional microeconomic theory taught to every undergrad. All you need to explain featherbedding is simple maximizing behavior. You can then make strong predictions about the degree of featherbedding as competition increases, and what will happen to wage rates. As the market becomes more competitive, workers will be willing to reduce wages first, before they reduce the number of people required to be hired – as he supports on page 13. The theory leads to meaningful, testable predictions. The two work hand in hand.
I am an economist. I may be biased by tribalism, but I should hope I have the independent will to choose my tribe. I do fundamentally believe that the ethos of economics is simply a better way to study the world. I like economics for its serious concern for proper statistical inference, for its intolerance of stupidity, and for venturing out into poorly handled fields and setting them right. I hope we never lose this.
The problem with psychology is that it has no theory.
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i. The problem with psychology
Psychology and economics are both attempts to study human behavior. While the precise focus may differ, we want to be able to make precise and accurate predictions about how humans respond to stimuli. We can use reasoning to make theoretical predictions about what will occur, and use empirical results to confirm or disconfirm them, or use empirical results to guide what our theory should be. You must have both, however.
I argue that economics is far better than psychology because it has a theory. Psychology does not. It is the fitting of epicycles to match observed empirical phenomena. If published research were an unbiased reflection of reality, this would be a distinction without a difference, but published research is distorted and obviously distorted. Psychology is a science without priors. They are left chasing the newest paper, without the slightest idea why it should be true or not true. Its only test of plausibility is whether it can tell a plausible story rationalizing the results. The funny thing about stories, though, is that you can spin a story to fit any particular set of facts. It is, moreover, in principle not possible to say what causes what without theory when looking at data sets after the fact. A randomized controlled trial (where people are assigned some treatment at random) can sort out that some treatment caused an effect, but for many interesting questions we can only observe data sets after the fact. As this paper proves, you cannot establish what causes what without a theory, without a prior.
Consider the example of priming. Priming, since debunked, is the idea that making people think about certain things will unconsciously affect their behavior. People who read a text about being old would supposedly walk slower after reading it. It is striking that it would be perfectly plausible to rationalize the exact opposite effect. You find that they walk faster – perhaps because they were reminded of their mortality, and walk faster to remind themselves of youth. You don’t have a sound sense of what would be confirming evidence, and what would be surprising evidence.Research will go on until a significant, publishable result is found – and so you end up with spurious claims on pointless questions.
This is not merely my complaint. Psychologists, surveying their own field with disappointment, agree. Muthukrishna and Henrich (2019)write, “Rather than building up principles that flow from overarching theoretical frameworks, psychology textbooks are largely a potpourri of disconnected empirical findings on topics that have been popular at some point in the discipline’s history.” They go on, “outside of psychology, useful theoretical frameworks tell scientists not only what to expect, but what not to expect.” To quote from Poincare, “Science is built up of facts, as a house is built up of stones; but an accumulation of facts is no more a science than a heap of stones is a house.”
I suspect that psychology is like this because it has its intellectual origins as clinical practice, in an era where medicine had only the scantest idea what to do, and knew still less why things worked. Reading Paul Meehl’s polemic against case study conferences, one is struck by how much of a psychologist’s work is still one to one. He, a professor with a sound footing in statistics, still gave ten to twelve hours a week in private psychoanalysis. Psychology even now has not fully shifted over to being statisticians.
ii. Why economics?
Economics has a core set of theoretical claims that can stand on their own. We can explicitly state our assumptions (generally, what people or firms are trying to maximize) and then show precisely how they can maximize it. Our work on how to optimize an auction requires no experimental proof whatsoever – it stands on its own. So too does much of microeconomic theory. How a monopoly could maximize their profits is simply proven – there’s no other method which maximizes revenue.
And this theory can meaningfully guide what we research. A paper that comes to mind is Ben Bridgeman’s “Competition, Work Rules, and Productivity”, as it could never have been made without a sound theoretical foothold. Suppose that there is a firm with some degree of market power – while not perfectly a monopoly, they are able to get rents. (Rents, in the context of economics, are profits in excess of what would be earned in a perfectly competitive market). Labor unionizes because they wish to divide the rents between them and the firm in some way. Crucially, the union is able to control wages and the number of people hired, but is not able to control output. Under these assumptions, it is optimal for the union to insist upon hiring some people who add nothing to production – what is called “featherbedding” – rather than simply maximizing their wages. A change in wage changes the marginal cost of producing a good. Firms would be incentivized to reduce their total production, in order to claim more rents for themselves. Requiring a certain number of people to be hired changes it to a fixed cost. The marginal cost of producing additional outputs is kept nearer the competitive outcome.
That’s it! That’s all you need! You do not need to appeal to theories of solidarity across workers (which is not so much an explanation as acknowledgement of the facts – you cannot make meaningful predictions about where and why “worker solidarity” would vary). Everything follows from conventional microeconomic theory taught to every undergrad. All you need to explain featherbedding is simple maximizing behavior. You can then make strong predictions about the degree of featherbedding as competition increases, and what will happen to wage rates. As the market becomes more competitive, workers will be willing to reduce wages first, before they reduce the number of people required to be hired – as he supports on page 13. The theory leads to meaningful, testable predictions. The two work hand in hand.
I am an economist. I may be biased by tribalism, but I should hope I have the independent will to choose my tribe. I do fundamentally believe that the ethos of economics is simply a better way to study the world. I like economics for its serious concern for proper statistical inference, for its intolerance of stupidity, and for venturing out into poorly handled fields and setting them right. I hope we never lose this.