A briefing on what economics has been up to while you were studying it at school.
Recall the first time you learned about economics. Marginal utility and all that, right? Bold smooth curves on graphs rampant with assumptions about human psychology. Perhaps you bit the bait and found the amazing simplicity of the relations between economic quantities enchanting. Or perhaps you didn’t see the logic behind the cut-and-dry intuitions of centuries-old economists trying to observe how ‘invisible hands’ worked. You see, the thing with invisible appendages is that they aren’t exactly the easiest to observe.
Economics has long been considered the most rigorous of humanities, eschewing the various concerns and ideals of our lives to reach straight for the essential drivers of our behavior. Hiding underneath all the shining armor of a knight arrived to save humanity from itself, the heart of economics always had a worm in it, eating away at its pretense of scientific accuracy. Most sciences only find out what actually is. They draw conclusions from observed events. Economics is a package deal. Along with arguments about how things are, economics also often secreted in assertions about how things should be. Sir Homo Economicus came riding out of the land of positive sciences only to leap over the fence into the wild, wild country of normative philosophy. Try naming another science which assumes that satisfaction of human wants is a “good” thing.
And the struggle to accommodate this idea accurately is visible in the sequence of topics in economics classes. First, we learn of cardinal utility before switching forward to the ordinal utility. In terms of actual history, the phase during which economics shifted from cardinal assertions to ordinal ones was nothing short of a revolution. A brief refresher: cardinal utility draws on the understanding that utility is measurable in the form of units of measurement called “utils” and further draws on the possibility that one person’s measurement of utility can be compared with another’s. Perhaps you hadn’t given this much thought before but all the talk about our inability to really know another’s mind, to look into it and feel what they feel, all this talk really hit economists hard. By the 1930s, they were denouncing the idea of measurable cardinal utility as nonsense and holding up the new standard of preference satisfaction in ordered rankings of preferences as the new meaning of utility. But wait a moment. Come the 1940s, further developments had brought cardinal utility back to haunt its ordinal cousin. The modern economic theory began to drop its assumptions to look at how individuals actually behaved. This is what is meant by the term “revealed preferences”, a term that brings to mind an economist pulling off a cloth from a dissected brain with a grandiose flourish. As long as we are able to measure the size of a risk taken by a person, we may be able to tell how much they really want it. And hell, be honest! Hasn’t this discussion about measuring utility brought up images of patients with electrodes stuck to their scalps, measuring neurological reactions? Measurement and comparison are possible, surely?
I know what you’re thinking. This was supposed to be a briefing about things that economics has been up to while you were studying at school. Microeconomics 101 is all about cardinal and ordinal utility, isn’t it? But the explanation of how they’ve emerged serves to show how the development of modern movements like behaviouralism was foreshadowed by an increasing willingness to relax traditional neoclassical assumptions to see how people actually behaved.
The biggest assumption was the one about perfect information. Relax that and you open a Pandora’s Box of questions that you cannot assume your way out of. This idea of less than perfect information resulted in the flowering of notions such as “information asymmetry”, the idea that when persons interact with each other without the appropriate information needed to make choices, they are likely to make bad choices, especially when one party has an informational advantage over the other. This development, in turn, sowed seeds of change in our understanding of institutions, corporations and the appropriate places for governments to intervene in private activity. Psychology, also undergoing a transformation into a positive science, began to smirk snidely at rationality assumptions in economics. Daniel Kahneman and Amos Tversky reported findings way back in 1979 that pretty much knocked Sir Homo Economicus off his horse. The Rational Man now stares back at us through the mists of economic history like a fantastic mythical beast. Kahneman and Tversky found that individuals, in fact, used what are referred to as “biases” and “heuristics” to take shortcuts in their thinking. It’s still thinking, but is it rational?
You have a choice between two scenarios. In scenario A, you will definitely win $250. In scenario B, you have a lottery where there is a 25% chance to win $1000 and a 75% chance to win nothing at all.
This is the only information you have about the scenarios. Think it through and remember the choice you make.
Now consider this:
You have a choice between two scenarios. In scenario A, you will definitely lose $750. In scenario B, you have a draw of lots where you have a 75% chance to lose $1000 and a 25% chance to lose nothing at all.
What would you pick in this second choice? Compare your answers from the two sets of choices. In both sets, scenario A presents certainty and scenario B presents a risk. Now, the trick is that economics traditionally viewed an individual’s outlook towards uncertainty in simple terms. “Expected utility” could be calculated by multiplying the amount of benefit or loss with the probability of getting it. Thus the benefit from scenario B in the first set is (25/100 x 1000) + (75/100 x 0) = 250. This is the same amount of utility as the first set’s scenario A. The choice between A and B seems to have been driven purely by the question of whether the benefit is uncertain or not. The case is the same in the second set. The loss suffered in scenario B is (75/100 x 1000) + (25/100 x 0) = 750. This is the same as scenario B. Kahneman and Tversky found that how people choose between risky and certain scenarios was determined by what they called a “framing effect”. People were more willing to take risks when the choices were “framed” or presented as benefits as compared to when they were presented as losses. The magnitude of utility in the gain or loss is the same. So there must be something about our mind that is more averse to risk when it is faced with losses as compared to when it is faced with a possible benefit.
Kahneman and Tversky found many other such “heuristics” or shortcuts that our minds take instead of employing slow, conscious deliberation before making a decision. Unfortunately, Tversky died before Kahneman became the only non-economist to win the Nobel Prize for Economics in 2002 for the work that they both did together.
The joy in this new science of how to deal with uncertainty lies in the exciting, counter-intuitive results that experiments throw up. This is especially engaging when applied to policy-making. Various tests in different circumstances have created a paradigm shift in the appropriate way that governments approach their work. Assume the effects of a law on the basis of broad assumptions about the problem? No way, say behavioural economists. Let’s have an experiment with the law to find out what its effects really are. Such evidence-based policy-making uses randomized, controlled testing to find out the answers. Randomisation of test subjects is done so as to ensure that no other variable (extraneous, irrelevant considerations that could creep into the data by accident) apart from the policy action affects the subjects on the relevant question. A control group is also created to see what similar individuals would do if they did not have such a law applied to them. Ph.D. students thus register early if there is a penalty for late registration but not for if there is a discount for early registration. A test in India showed that when women from the local community were engaged as remedial tutors for underachieving students, the program significantly improved test scores, especially in maths. What other wonders can be discovered in this manner? What entrenched notions of ours are yet to be debunked?
Let’s see. What can be done for hooked readers at this stage? Want to understand this revolution better? The thing with our modern age is that we don’t need to delve into academic articles to understand what is happening there. One need only recommends readings from bestsellers such as Nudge (Thaler and Sunstein), Predictably Irrational (Dan Ariely) and Thinking, Fast & Slow (Kahneman). So do yourself a favour and do not let yourself sink into the satisfaction that you understand high school economics. There is a wild, complex and very human world being unveiled all around us and you do not want to miss it.