The Uncertainty Of Economics: Exploring The Dismal Science
By Andrew Beattie
When speaking or reading about economics, you’ve probably heard someone drop the phrase the dismal science. If you did not know what this phrase meant, you may have dismissed it as a clever joke, or, harboring a secret passion for experimental observation and beakers, you may have been too shy to question how on earth any science could be dismal. Looking at what the dismal science is and why it carries such a depressing name, however, may help you better understand why you may face uncertainty and contradictions in your investing endeavors.
The phrase “dismal science” was coined by Thomas Carlyle in response to Thomas Malthus’ beliefs that the exponential population growth would outpace the linear growth of the world’s food supply, resulting in a global famine. Malthus didn’t foresee the leaps in science, such as the development of fertilizer, that have allowed the earth to support many more people than was previously imagined. Still, one of the fundamental concepts of economics is the principle of scarcity – the idea that there will never be enough for everyone. That dreadful outlook is one of the reasons economics is considered a dismal science.
Why Economics Isn’t Really a Science
In addition to the blunder of Malthus the phrase dismal science refers to the unreliability of economics in comparison to conventional sciences such as mathematics, physics or biology. Most sciences work through an initial explanation of a proposed phenomenon (also known as a hypothesis). The scientist then forms a model to test and scrutinize this hypothesis until only the important variables remain. These variables are repeatedly tested to determine whether they are the causes of the end result. If in fact a variable can be isolated and determined as the sole cause, then the theory underlying the hypothesis is referred to as a law. (Please keep in mind that this is a gross simplification of the scientific method.)
Economics, like science, aims to explain certain phenomenon, but for many reasons economics cannot fulfill the criteria of the experimental model. To better understand the constraints on the study of economics, let’s take at look at what the methods of science demand:
Scientific Method Example – Car Door Experiments
So let’s say we’re studying the phenomenon of why my hand hurts when I slam it in my car door. For me to use a scientific approach I would form a hypothesis. Suppose my theory is that it’s because I’m wearing an Investopedia T-shirt. To test this theory, I create a model to test different scenarios and variables. This model involves slamming my hand in the door while wearing different shirts, including my Investopedia T-shirt. I eliminate factors (variables) that don’t affect the result (my pain) and I continue testing other variables until I am left with one that is the cause of my pain: the fact that I’m smashing my hand in a car door.
After several hairline fractures, I’ve figured out that the real reason my hand hurts is not because of the T-shirt I’m wearing, but because a slamming car door on my hand translates into pain through my nerves. So, a law has been formed: the Andrew Law, which states that if I slam my hand in a car door with “X” amount of force, my hand will absorb “Y” amount of energy causing my nerves to relay “Z” amount of pain to my brain (a gross simplification).
The Uncertainty of Economics
Economics cannot ascertain any clearly defined laws because in the market some unidentifiable factor always may be influencing a particular event or phenomena. It’s nearly impossible to isolate any given variable in economics, so the dismal science is mainly based on theories.
These theories may contradict each other, like efficient market hypothesis (EMH) and behavioral finance, but they may be proven true in certain cases or even at the same time. Furthermore, when studying economics, evidence often turns out to be coincidence more than a fact.
Typically, these unreliable characteristics are a result of three specific things that economists cannot control:
Unlike other scientists, economist don’t have special laboratories where they can create isolated models to test their hypotheses. A vacuum of the economy just doesn’t exist and cannot be created. Because of this, economists can’t verify or prove their hypotheses as easily as other scientists. For instance, when Sir Isaac Newton had to repeat his tests for the existence of gravity, all he needed to do was find more apples to drop from different trees. For my law, all I needed to do was wear different T-shirts (and eventually stop slamming my hand in the door). For an economist to test a theory, he or she has to appeal to different governments to implement a specific change in the economy or, even worse, wait for them to do so under their own accord and then take the necessary measurements.
Aside from the many different assumptions that economists make when debating their theories, probably the most hotly debated one is the idea of homo economicus, or the rational human. Nearly all economic theories assume that people are rational at all times, that they always prudently allocate their resources in a predictable manner that is beneficial. Unfortunately, this doesn’t always hold water in the real world. People will gamble even though the odds are against them; they will forget to go to the supermarket with a calculator to see if the 32 oz. can of soup is cheaper than the 16 oz. can, and they don’t routinely analyze the opportunity cost of different goods.
Blind Man’s Bluff
Imagine you were blind with a deck of cards laid in front of you and someone expected you to be able to sort out the three of hearts. We know that there is a one-in-52 chance of being right and that, if the cards are randomly sorted, there is no scientific methodology that can help you improve those odds. However, if you pull the right card, you might attribute it to anything: the way you reached out, how many breaths you took, the twitch in your right eye – anything.
Once again you are stuck slicing and applying variables, but you can’t repeat the test with any kind of consistent controls. This is similar to economics: the number of testable variables is enormous due to the sheer size of the economy. As a result, there has been little success not only in predicting phenomena but also in proposing reasons for why observable things happen. The economy can’t be controlled like a math equation or a science experiment, and there are simply too many variables to test with any sort of reliability and verifiability.
The Bottom Line
So there you have it. Next time you see someone dropping the phrase “dismal science” you can check if he or she uses it correctly; furthermore, you know that the person using the term could not possibly predict or explain market events with any smug confidence.
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