If you’ve been paying attention to the debate over the state of economic theory and economics education, you’ve probably seen the introductory economic models defended on the grounds that ‘all education starts with simplifications’. This is often combined with comparisons to physical sciences, where simplifying assumptions are also made: as Rehle & Jeny point out in their textbook ** Advanced Microeconomics**, “In the physical world, there is ‘no such thing’ as a frictionless plane or a perfect vacuum.” The idea is that economic models, such as the economic model of the perfectly competitive market, serve as pedagogical tools to introduce students to the idea of modelling, as well as key ideas, and serve as a platform from which we can launch more complex analysis.

In principle, this argument is valid. We cannot introduce students to the most complex models from the outset, so we need to drop layers of complexity in earlier classes, hoping that studying them will still help students gain critical thinking skills and under- standing. It is my contention that economics education simply does not achieve this. Introductory economics classes make key ideas more difficult, not easier to understand.

Key concepts such as utility, competitive equilibrium and optimisation are extremely abstract and difficult to grasp, which is why surveys of economics students commonly contain complaints about the level of abstraction and lack of practical relevance. The assumptions in economics serve to build a parallel universe – a ‘castle in the sky’ – rather than simply eliminating unnecessary aspects of the problem.

Consider the way consumer theory is taught. You are introduced to a handful of axioms about peoples’ preferences and told that they can be represented by a ‘utility function’, which consumers maximise in order to attain the most satisfaction possible given their budget constraint. Utility has no obvious real world counterpoint, and neither do the properties derived from utility – students endure tiresome graphical and mathematical manipulation to understand the so-called ‘Hicksian demands’, which are not observable in the real world.

The whole exercise is done with infinitesimally small ‘bundles’ of abstract goods, goods which typically have no other characteristics than being ‘good x’ and ‘good y’. Depending on the level of difficulty of the class, you will build up utility theory meticulously from the aforementioned axioms and possibly go on solve some constrained maximisation problems. The purpose of the exercise itself is not obvious, aside from testing students’ abilities (and patience).

Contrast this with mechanics and the canonical ‘bouncing ball’, taught in introductory classes. Using certain information (mass, gravity’s pull), you can predict how high a ball will bounce when you drop it. The *concepts* involved are intuitive, straightforward and measurable – a 5-year-old can understand the idea of a bouncing ball – but the *mathematics* is challenging (even the most basic differential equations are more difficult than most of the mathematics you’ll find on an undergraduate economics degree). If anything, the opposite is true in economics, where the ideas involved can be difficult to grasp, but much of the mathematics would be considered trivial by a first year maths undergraduate.

Furthermore, the assumptions used in mechanics truly are simplifying: eliminating air resistance simply drops a known mathematical variable, one which can be added to the initial equation later in the same class. To be sure, not all assumptions in natural science simply eliminate a known mathematical variable; some, such as the assumption of a perfect gas, make some obviously ‘wrong’ assumptions which facilitate the use of a simple equation (PV=nRT). Nevertheless, when it is done, it is made clear that there are many cases when the equation does not apply (e.g., to steam), and it is shown that the results you get are accurate to within ~ 4 decimal places. Furthermore, the theoretical foundations of the perfect gas equation are not generally taught to undergraduates, since they do nothing more than add unnecessary complexity. The way economic theory is taught seems to *glorify* unnecessary complexity over focusing on the empirical relevance of the simplifications made.

Now, there is an obvious counterpoint to this argument: economics is intrinsically more complex than bouncing a ball or boiling a gas, so we can’t help but drop a greater degree of relevance in our models. But how much relevance can be dropped while we can still claim the model is credible? If economics teachers cannot manage to get undergraduate students to a point where the models they are using are demonstrably worthwhile, then perhaps economics should not be taught at undergraduate level at all. This may sound extreme, but complex sciences such as meteorology are not typically taught at undergraduate level, partly for this reason. Similarly, if engineers told you that what they taught their students was only the first couple of steps on an elaborate theoretical journey, and had little practical relevance, you’d probably doubt the efficacy of teaching engineering at undergraduate level, too.

However, we can do better than dropping economics from the curriculum by instead dropping the *assumption* that an economics education needs to be heavily focused on modelling. The purpose of economics education should not be to provide students with a limited introduction to the most abstract elements of academic economics, but to provide them with a basic but demonstrably useful view of the workings of the economy. This would include things like economic history and the history of thought; firm, banking and accounting practices; empirical methods used to analyse the economy (experiments, statistics, surveys); and, where necessary, an introduction to the kinds of formal models that further our understanding. For example, it is possible to teach and test the basic demand-supply model without building it up ‘rigorously’ from a collection of axioms, a task which is surely of interest only to academic economists.

Mark Blaug once commented that “economics has increasingly become an intellectual game played for its own sake”. If this is the case, the game should solely be the reserve of academics, and not imposed on students who go out into the real world. What economics students need to gain from their education is an ability to handle data, a working knowledge of key aspects of the economy and an understanding of how economic problems can be approached using different tools. Where theories are taught, the focus should be on their relevance, rather than their obscure theoretical foundations. Assumptions made should have clear interpretations, consequences and limitations if they are to be defended as ‘simplifying’ the students’ experience. This is the best way to introduce students to key ideas which not only prepare them for more in depth study, but stand on their own to help the students form a useful understanding of economics.