Laws of Demand and Diminishing Marginal Returns Outside Economics

Yesterday, I posted on a synthesis between economics and the other sciences. In this blog post, I provide a couple examples of such theoretical crossover. This is from a current working paper of mine on the endogeneity of social systems.

The laws governing the physical universe are constant through time and space; however, they must be discovered by someone to be brought into the set of scientific theory and knowledge recognized by humanity. Likewise, economic laws are constant throughout society, but it takes observations from people to draw these theories out from the interactions of others. Economic laws are inherent to the universe; they are de facto a priori synthetic. The laws of demand are known to be constant and everywhere existent, much like the laws of the positive sciences. It does not take transactions amongst people for the laws of economic to become evident, notably the first law of demand can be seen in biology, chemistry, and physics.

For instance, the law of demand has been seen throughout the biological systems as animals have evolved to display certain traits. The male peacock, for example, has a wonderful plume of tail feathers for which he uses to attract mates. The larger his plume, the more attractive he becomes but at a price: he is more visible to predators. This form of tradeoff is seen throughout the animal kingdom, but there is a correlation with increased expression and increased vulnerability to predators. As can be easily identified, there are more animals with nominal characteristics within any given population and increasingly less as phenotype characteristics become more flamboyant. The quantity of phenotypes that make an animal attractive to mates decreases as the resulting characteristics make the more easily seen by predators.

In the physical sciences, the law of diminishing returns can be seen through the processes of chemical reactions and limiting reagents. In the process of creating a fire, three factors are needed: heat, fuel, and oxygen; however, in a contained environment, an increase in any one of these could lead suboptimal reaction if the other factors are held ceteris paribus. If there is too much fuel for the fire to consume, then the oxygen in the environment becomes the limiting reagent: the reactant that is used up first in a chemical reaction and determines the amount of product that can be formed in a reaction. If the oxygen in the environment becomes too abundant, the fire will begin to burn faster. The chemical reaction may happen so quickly all the fuel becomes used and there is leftover oxygen. If the heat in this scenario becomes too high, the risk of changing the reaction from a fire to combustion increases. The law of diminishing returns is a priori to economic and societal systems.

Tilson, William. “Societal Actions as Outcomes of an Endogenous System: Economic Theory and Policy: Autonomous or Caused?” Working Paper, 2019.

Bridging the physical and social sciences

Throughout the past, biology has borrowed much from economics. I think it’s time that economics begins to take back some ground. I’d argue that economics and biology have more in common than you’d think. We both deal with agents who are constrained in their environments and are subject to larger systems whose rules may not be fully known. Agents, animals, cells, and DNA all have similarities in how they engage with the world. 1) They’re subject to the law of demand: price and quantity demanded of any good and service are inversely related to each other. 2) They must follow diminishing marginal returns. 3) They all abide in a world of emergent behaviors and outcomes; some of these may take hundreds or more generations to manifest themselves.

Given these constraints, it can be followed that outcomes of this system can be described by other outcomes of the same system. Most notably, there should be patterns of behavior and design that transcends the individual agents within the system, no matter how large or small they might be. From this point, I think that the sciences, both social and physical, should be able to share methods and ideas. I think many of the truths in our would can be found at the intersection of these ideas.

In my current research, I’m looking to create a synthesis between the rules provided by evolutionary biology and the human action from the micro scale to the macro phenomenon. Many of these patterns will reside in the meso-level, a place in between micro and macro. Note that the feedback loops will reside at all levels of the system.

I’m going to take a moment here, while I am in class to give my impression on Charlie Plott’s fundamental equation. In it, he says

preferences * institutions * physical possibilities = outcomes.

Is there anything wrong with this attempt to constrain the outcomes of human actions? I would say yes. The biggest issue resides in an engineer-like observation of human action. This equation steps outside the system, when it actually unable to do so. Furthermore, all of these are self-reinforcing or self-removing. The equation is entirely endogenous at both the system level and the agent level. In a Robinson Crusoe situation, at least on of these variables need not exist. Additionally, where does choice and subsequently action occur? In this line of thinking, there is little room for the adaptation that happens in reality.

On a side note, I recently listened to a podcast on the ideas purported by Glen Weyl where he claims that the study of economics has a difficult time explaining increasing returns to scale. Much of human social behavior exhibits this, not to mention digital technologies. Does economics explain this? I’ll link to another blog on this later.

Farms or Cities: A Chicken and Egg Problem

I am only a few pages into Jane Jacobs’ book The Economy of Cities and she posits something I have yet to hear in any of my time learning economics or philosophy: cities are not made possible by the agricultural economy but agricultural economies are made possible by the economies of cities. I think most of the profession, and many farmers, would argue against that thought. To them, cities must arise out of the foundations of agrarian economies. For the first cities, that is certainly true. What about later cities?

If it wasn’t for cities, there could be no expansion of farming technologies. There could be no global exchange of produce. Without cities, farms would have fewer people to which they could sell their goods.  I am not against farming; in fact, I think transitioning to many more, smaller farms instead of the mega-factory farms would be a net good to our society. However, this does not detract from the case presented by Jacobs; farms need cities to advance their trade and keep it viable.

But let’s face it, cities are unable to produce enough food to keep their own fed. They rely on massive harvests from farms the world over. Vertical farming has recently become a fad, but upon closer inspection, vertical farms can only produce leafy greens and vegetables with low-caloric value. A city cannot be sustained on vertical farms, nor can a farm be maintained over multiple generations without plenty of customers.

I don’t think Jacobs is entirely correct in her assumption. Cities need farms and farms need cities. There is a feedback loop here. Farms feed innovation and human interaction in cites; this, in turn, brings innovation back to the farm and allows it to profit from these interactions. The city is then able to have increased interaction due to increased production from the farms.

One issue that arises is that massive fixed costs undertaken by some farmers attempting to compete with larger farms who are able to dilute the costs across their investments. For the average non-factory farmer, this level of capital expense may be unsustainable. What does competition look like in the farming industry? I imagine the margins are tight.

Comparative economic systems, thoughts

As I alluded to in an earlier post, no economic system is purely capitalistic or socialist– there are an infinite number of potential combinations (this is analogous to sociology’s proposal that no person is purely masculine or feminine). This is not to say that one combination can clearly be superior to any other; though, at any given time, there might be one system combination may produce more output than another. Furthermore, there may be other metrics than the dichotomy that I have just posited. Surely, there are numerous types of economic organization that we have long forgotten or have yet to discover.

Some systems, even a few currently in existence, fail to expand past their current boundaries because of scalability issues. We know that issues with moral hazard and adverse selection often lead to the downfall of interpersonal and interfirm relationships; at the very least, they can put considerable strain on these same relationships. In the market, insurance companies and banks have to find contractual work-arounds and screening devices to limit these problems. Depending on the constraints and the desired outcomes, not all economic systems are created equally. Some systems may perform better for a certain task, at a certain time.

This poses a number of questions:

  • What are these outcomes?
  • What metrics do we use to measure the economy?
  • Are these metrics correct?
  • What is the goal of the system?
  • What is the paradigm that governs the system?
  • What are the base ideas of the system?
  • How do these ideas change the system?
  • What are the marginal changes of black swans?
  • Are averages overrated? (I think so)
  • What is inequality, and by what metric do we determine inequality?
  • What are the feedback loops in each economic system?
  • How do stocks and flows change these?
  • Which feedback loops have increasing returns to scale vs those that have diminishing return to scale?
  • What about returns to scope?
  • How can open ended evolution systems help us find the answers? (In a way that DSGE is unable to do?)
  • What are the ultimate ends of the society?
  • Was George Bernard Shaw correct when he stated that socialists were just communists without courage?

Upcoming, a look at the Soviet economy via Janos Kornai.

Thoughts on complexity in economic systems

  • If a social system develops in practice, it should also work in theory. (That theory may be convoluted and never finished, however.) Much like the sorting and randomization algorithms, the efficiency and effectiveness of the system of economic organization will vary.
  • The difference between economic systems lies not only in the rules of the game, but the stocks and flows of each system, and how they are determined. Additionally, how much self organization do the agents have?
  • The flow chart will change depending on the type of system.
  • No system is purely socialist or purely capitalist, but a gradient of each. Communism may fit in somewhere, as well.
  • The system must seek resiliency and self perpetuation
  • This fails at the extremes because in the purest systems there are leakages; not all agents will be able to continue in economic means.
  • In pure socialism, the end will transfer economic activity into the public choice domain as people, no longer lacking of economic wants, will demand positional goods in their place.
  • Pure capitalism creates its own undoing by driving technology to a place at which there is no work available for anyone to do. To put it simply, after the Hansonian singularity, there will be no more economic activity necessary for an agent.

Productivity Growth and the Steady State

The idea of diminishing marginal returns is a key founding block in economics. We assume that as one adds each additional unit of something, the additional product of that unit decreases unless all other inputs are increased by the same amount. This is not always the case, but for many real world examples, diminishing marginal returns (DMR) hold.

Over the past couple centuries, the amount of growth the world has seen has been tremendous. On all known levels of human development, there has been significant progress even at the average level. Granted, some nations have fared better than others (that’s another story), but the industrial revolution has been a net positive for humanity. Within the United States, this rate of growth peaked in the mid 1920s, but high levels of growth continued in the subsequent decades. Many of the highest impact inventions were created during this time: radio, television, cellular technology, semi-automated home appliances, the early versions of the internet, nuclear energy, solid state electronics, transistors, and integrated circuits. All of which, are still with us, but this rate of progress did not continue. It is common knowledge, amongst economists and infovores, alike, that developed countries have experienced on average lower growth in productivity and technological change since the 1970s.

Much of this decline in technological change reminds me of growth models encountered in my first year grad courses. In these models, all economies converged on a steady state growth path where the rate of change in their respective productivity growth became zero. For many of these models, this stationary state implies some sort of equilibrium; however, I’d argue that the world is in a constant state of disequilibrium while trending towards some unknown target and each of these inputs has DMR. The path towards equilibrium in many of these models contains well-specified criteria and variables, but in the real world, everything is a variable.

A small goal of mine is to come closer to understanding this slowdown in growth. Many people question it, including recent Nobel laureate, Paul Romer, but it isn’t the mainstream topic of our time outside a few, well-specified circles.

Some thoughts moving forward in an inquiry into the nature and causes of productivity growth:

  1. Innovation is a form of social violence against the current technology and producers.
  2. Complacency is a human downfall?
  3. The current set of research has reached saturation to the point of DMR
  4. Institutions, both social and legal, have changed to maintain the status quo.
  5. Leisure is to cheap relative to work (credit: SP).
  6. We are no longer engaging in basic research.
  7. We have gathered the low-hanging fruits.