Not too long ago I tried to make the argument that physical principles may be useful in the analysis of human behavior, as well as societal and cultural phenomena. Well-known physics concepts such as inertia, momentum, force and impulse seem to have analogs in the social and behavioral sciences. There are other reasons that suggest a deeper connection between the physical realm and social realm, as seen in the fields of network theory and complexity. Common mathematical relationships and structures have been discovered over a remarkable range of systems, from the Internet to social networks to business networks, and even in food webs and metabolic chemical networks.
Further evidence of deep links between physical systems and economic models have also been discovered. In the September issue of Physics Today, an article entitled “Is Economics the Next Physical Science?” is featured. Yale professor Martin Shubik and Santa Fe Institute researchers Doyne Farmer and Eric Smith have been working on econophysics, where well-established mathematical methods used by physicists over many years have been used to establish better dynamical economic models. For example, the study of chaotic systems in physical systems as economic analogs in the sense that an economic market can follow very different paths if there are relatively minor changes in the initial conditions of the market. The mathematics used in this type of analysis follows techniques used in physics. The observation of numerous power laws in physical systems and networks (i.e. scale-free networks) over a number of years has led to more refined analysis tools, which are now being used to understand newly discovered power laws in economic theory. These power laws include analysis of price movement in stocks over short periods of time as well as income distributions in capitalistic economies. Production and distribution networks of large corporations have been shown to follow characteristic power laws associated with scale-free networks. What may seem like random trading patterns in the stock market that lead to market swings and patterns may be analogous to random motions of many-body systems that show emergent behavior. Statistical mechanics relationships are being used to study various types of economic models (since probability distribution functions rule).
While standard physics analyses may provide some leads into the deeper understanding of economics, there is still the difficulty of including human beings into the mix. It is not clear that we will be able to model human responses that are based not on logic or deterministic physical laws, but rather raw emotion and the possibility of random response decisions to evolving market conditions that are built around strategies that may or may not be well thought out. We are not yet at the point of creating a Foundation like Harry Seldon did in Isaac Asimov’s classic ‘Foundation Trilogy,’ but this is a fascinating new way of thinking about the possible universality of physical and social sciences.