A changing US tax code and shifting geopolitical activity puts more focus on the opinions of economists. Bloomberg economist and Michigan economics PhD, Noah Smith (his blog is Noahpinion) highlighted many of the issues in modern economic analysis in a recent twitter thread. At the core of most modern economics is an over simplification that leads to theoretical results that differ from reality. Biology as a field avoids this by embracing complexity and data.
Smith’s point highlights a common concern with economics – it solves problems through simplification. As an undergraduate double majoring in biology and economics the two fields are polar opposites. Biology encounters complexity and tries to make sense of the systems and data that the world presents. Economics does the opposite. An economist sees the complexity in an area without data – and proceeds to create simple, imaginary characters called ‘rational consumers’ and build up models based on equations and assumptions.
Simplification was an essential tool in a time of limited computing power and little data – but these items are no longer a constraint in how we can look at the world. Moore’s law gives computational power. Data is abundant – and if the specific data is not, then there are many ways to test or create it.
The economist sees a world that behaves irrationally because people aren’t rational consumers. People are more than consumers, and they place importance on items that aren’t in simple models. The moral simplification of people into actors with few unchanging needs feels ethically shallow.
The biologist starts with data, embraces complexity, and interprets facts to create a model as the pattern becomes clear. In the modern world, there are times when complexity needs to be embraced, and times when it needs to be simplified. Pivoting between the two extremes is an important skill.