I have posted previously about problems associated with simplification. This post continues that discussion looking at more specific problems.
One way economists simplify things is with an archaic tool known as mathematics. Economists use math to measure things and relate them to each other. Math helps make things easier to think about by creating new, simplified ways to understand them. For example, once you understand the concept of elasticity, it is easier to think about “elasticity of demand” than “the amount that demand will change in response to a change in price.” It is likewise easier to think about productivity than it is to think of “the ratio of output per person.”
It is good when terms are precisely defined with equations, but even well-defined concepts can be problematic. First, complex concepts may fall victim to a sort of "sanitizing conflation", when a concept made up of other concepts takes on a simplified meaning that ignores one or more of its constituent factors. Concepts may be bundled into packages that distract us or focus our attention in different ways than the individual concepts might. Another way to think of this problem is that even when a model (or even an even simpler definition of an economic concept) is accurate, the way it represents the world may be misleading.
Misleading representations can be seen everywhere when you start looking. Even in such a field as accounting, where relatively rigorous and standardized quantification exists for most everything, simple headline concepts such as “profit” can obscure important details about internal costs. In economics, the idea of productivity suffers from sanitizing conflation when we focus on the beneficial effects of increased output and competitiveness instead of the possibility of job losses.
Santizing conflation is particularly likely when the different factors in a derivative concept have different levels of quantifiability. For example, economists generally agree that both technology and education levels are important determinates of productivity, but education is relatively quantifiable while culture is a nebulous concpt that is difficult to fit in an equation. Education therefore shows up in far more studies as a relevant variable.
The second problem that concepts even very precisely defined by other concepts may face is that the original concepts themselves may not be coherent or exactly defineable. If you are enjoying the fancy labels we can call this "indefinite origination". Indefinite origination is a huge problem in economics because even the most exact data on something as straightforward as, say, unemployment may in fact be problematically defined. In the USA there are six different measures of unemployment! The question of which one to use has enormous influence on anything you might use the concept of unemployment for.
But one does not always need math to simplify things—if you do it right you can get along fine with hand-wavey obfuscations. Economists are often guilty of this, certainly, but economics also does a decent job in many instances of making assumptions explicit. A good economist is far better equipped to understand the full details and implications of an economic concept than, say, your average journalist or voter.
One common hand-wavey simplification is “efficiency”. Efficiency has several exact mathematical definitions in economics, but those definitions do not have much to do with everyday usage in business or politics. Efficiency is generally assumed to mean cost reduction or increased speed or output, but it is silent on how those reductions or increases come about. Much like productivity, effiency gains can stem from improved processes and eliminated waste, or they can come from reduced pay and benefits (scroll down to section II).
Instead of efficiency, I have tried to start thinking more directly in terms of costs. This is helpful because costs—even costs that are eliminated—are easier to see than “efficiencies”. It is also clearer that many costs are two-sided: my employer’s cost is my salary, whereas efficiency for an employer does not necessarily have anything to do with me. Costs are also clearer to think about in both monetary and non-monetary terms, because they are “something” instead of “a reduction in something or an increase in something else.”
I plan on writing more about efficiency and costs in a subsequent post, but for now I think I have made the points I want to make. Be careful with complex concepts because we have a hard time comprehending them in their full complexity. Math is an powerful and essential tool to help your thinking, but it structures your ideas in a rigid framework that may or may not be appropriate to the real world. And beware the multitude of these concepts that have already entered your thinking and understanding of the world.