Edward Hadas: Bring on kitchen economics

June 17, 2015

The author is a Reuters Breakingviews columnist. The opinions expressed are his own.

The new buzzword among academic economics is “mathiness”. The word was coined by Paul Romer, a professor at the Stern School of Business of New York University who is often considered a candidate for the economics Nobel Prize. He says his academic opponents hide intellectual prejudice behind abstract models which are not really mathematical, just math-y. Romer understates the problem. Equations muddle almost all economic debates.

Romer coined the word as part of an argument around what is known as growth theory, which analyses the drivers of prosperity. He explains his own view with a helpful non-mathematical model. Think of a kitchen, he says. A larger supply of ingredients will make more meals, but not necessarily better ones. For that, recipes are crucial. In an economy, the quantity and quality of the output – cooked dinners – depends in part on the quantity of the inputs of raw materials, labour and capital. It depends much more on the recipes – knowledge.

So, while capital investment and skilled workers are necessary, technological innovation is the key to growth in developed economies. Romer and his opponents agree on that. They differ when it comes to the analysis of how stuff is discovered and disseminated. In his analogy, they disagree about how recipes are written and then learnt by the cooks in the big economic kitchen.

Romer uses his kitchen economics to help people understand his thinking. But he also says that economists should prove their points using the rigour of equations. His 1986 growth model can be summarised with 14 of them. To turn reality into variables which follow the rules of mathematics, he postulates such remarkable abstractions as an omnipotent social planner and identical households which “maximize a typical CRRA [constant relative risk aversion] utility function”.

Romer’s equations add no insight to the analogy. On the contrary, it adds confusion. After all, there is no social planner, households are not identical and they do not maximise any sort of utility. Doubt about those simplifications distract attention from the question at hand: what pushes growth?

The model is weakened by enveloping it in a haze of mathiness. Romer’s use of a single variable to describe “output-augmenting technological progress” is effectively circular. It assumes something that comes as the conclusion of the argument. In the kitchen analogy, it is easy to wonder what sort of recipes capture the complexity of economic reality. In Romer’s equation, that key issue is hidden behind a variable “A”.

Now consider the work of the winner of the 2014 Nobel Prize for economics, Jean Tirole. He and his co-authors thoughtfully analysed how to regulate monopolies such as water companies and dominant players such as Google in search engines. The basic conclusion is that there is never a simple or single formula. Companies, industries and societies differ too much, he says. There are too many tradeoffs. The effects of any particular decision are unknown.

Tirole has presented these conclusions with innumerable equations. They all rely on the standard economic assumption that everyone acts entirely for selfish gain. Since that claim is simply false, the equations can only subtract value from the sensitive qualitative analysis.

Mathiness pervades almost everything in academic economics, from the basic models of supply and demand to the most complicated models of macroeconomic equilibrium. Ideological assertions and intellectual sloppiness are hidden in the choices of what to ignore and what to include, what to crush together into a single variable and what to split up.

Of course, explanations, whether verbal or algebraic, always involve simplifications, but words are much closer than abstract symbols to economic reality. In the right places, and in moderation, there is a role for mathematics in economics. Statistical analysis helps understanding by organising factual data. But abstract models take economics into an alternate universe.

The math-y approach might be excused if it worked, say by predicting economic recessions or by eliminating poverty. In fact, the dominant theories work badly by any standard. The failure should also be expected from models which exclude everything that cannot be squeezed into equations. What is left out? The things in human nature that lie at the heart of so many economic decisions: generosity, jealousy, loyalty, ambition…

Mathiness encourages a dangerous intellectual isolation among economists. They cannot follow the thinking of sociologists and anthropologists. That is a shame, since these social scientists could keep economists from ignoring the cultural values which shape modern economies and the institutions, from corporations to legislatures, which make them work.

Even worse, mathiness cuts mainstream economics off from ethics. Professionals rarely ask the most important and basic question: what is economic activity supposed to accomplish? Rather, it is simply assumed that the goals of economic activity must be something mathematically recognisable – such as maximum GDP growth rate or minimum income inequality.

Economics should help us understand and promote nebulous but wonderful goals such as human happiness, the responsible use of natural resources, and just allocation of the fruits of human labour. Mathiness gets in the way.

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