# Why we need maths in economics

*Secondary subject line: Why words and intuition aren’t always good enough.*

First, let me say that I can wholly agree that a fixation with mathematical formulation has been detrimental to economics in a number of instances. By any reasonable account, many an economist has become enamoured of their elegant theoretical models and abstract equilibria points, all the while ignoring the implausibility of their founding assumptions and the unpredictability of real-life phenomena. Point made, let’s correct for these imbalances and move on.

1) Yes, economists (and other social scientists) use much-simplified models to describe complex phenomena. That doesn’t mean that the relationships under analysis aren’t valid. Scientists (social and otherwise) already have a “perfect” model with which to observe the world...

*The world.*Unfortunately, this is of little practical use. The planet is too complex to formulate in its entirety so we must simplify things in such a way that (hopefully) preserves the most salient features and variables.[*] The ability to simplify is a virtue that should be embraced, not disdained. To put it another way, try to think of simplified economic models – complete with stylised assumptions – as thought experiments. We deliberately isolate key variables and analyse how changes in their levels or compositions can affect other key variables,

*ceteris paribus*.

*is*a language of logic... perhaps

*the*language of logic. Expressing relationships between economic variables – human or non-human, physical or intangible – in mathematical terms allows us to convey a message in manner that is unambiguous and can be universally understood.[**] (Proficiency in mathematics not withstanding...) Further, and I would say more importantly, it enables us to

*fully*work through the consequences and dynamics of these relationships. Our intuition may suggest certain outcomes, but intuition can be pretty limited in scope. Working through a set of equations enables you to arrive at a final result with a cool clarity, which may then show up unexpected results that only become “intuitive” upon further reflection. In other words, maths can both help to reveal ambiguous effects and prevent some of the undesirable ambiguities of normal language.

*de facto*method of analysis. Now, I certainly don’t think that anything and everything should be quantified in numerical terms.[***] However, if we’re dealing with money and prices, investments and interest, output and revenue, jobless numbers and government spending, wealth and exponential growth... There’s precious little way to do substantive analysis otherwise.

**THOUGHT FOR THE DAY**: Maths can be difficult and/or boring... for a lot of us. Certainly, it can be harmful to focus on the elegance of a theoretical equation at the expense of observing what actually happens in the real-world. However, economists and other social scientists

*need*maths. Our understanding of our respective disciplines is certainly richer for the rigour that maths helps provide. It is not the only tool at our disposal, but a critical one nonetheless. And relying solely on words or our intuition is often simply not good enough.

**UPDATE**: The first of these examples, The "Oil Tank" Model is up.

**UPDATE 2**: The second example, Schelling's Segregation Model is up now as well.

*magnitude*of economic effects, even when we have very strong theoretical grounds to be sure about the

*direction*that those effects should take.

*without*resorting to the language of mathematics, while most ordinary individuals can do so fairly easily

*with*the aid of mathematics.” This particular book also starts with a great quote by Emerson: “If I have a message to send, I prefer to use the telegraph to the wheelbarrow.”

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