The Complexity of Economic Decisions

We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task’s complexity is determined by its composition of cognitive operations. Complexity emerges as the inverse of the total factor productivity of thinking about a task. It increases in the number of importance-weighted components and decreases in the degree to which the effect of one or a few components on the optimal action dominates. Higher complexity generates larger decision errors and behavioral attenuation to variation in problem parameters. The model applies both to continuous and discrete choice. We develop a theory-guided experimental methodology for measuring subjective perceptions of complexity that is simple and portable. A series of experiments test and confirm the central predictions of our model for perceptions of complexity, behavioral attenuation, and decision errors. We apply our framework to core economic decision domains, including the complexity of static consumption choice with one or several interacting goods, consumption over time, the tax system, forecasting, and discrete choice between goods or lotteries. These applications demonstrate how our approach to complexity can be used in empirical and theoretical work