“Stability is destabilizing.” – Hymin Minsky

Hyman Minsky, an economist at Washington University in St. Louis from 1965 to 1990, developed a theory known as the financial instability hypothesis. This theory suggests that the market is fundamentally unstable because periods of economic stability foster an environment where risk-taking increases. According to Minsky, this increased risk-taking leads to the formation of financial bubbles which, when they burst, cause economic crises. Essentially, stability breeds complacency, which in turn leads to speculative excesses and eventual market instability.

During the good times, people make bad decisions. The accumulation of these bad decisions leads boom-bust cycles.

The Minsky Moment: Why Stability Leads To Panic And What To Do About It

Stability itself is the enemy. That’s like putting out all fires in the forest in order to stabilize the forest. Never mind that later the entire forest burns down to the ground.

What follows is a summary of an article from Mauldin Economics: “Ubiquity, Complexity, and Sandpiles.” John Mauldin’s article uses the sandpile analogy to explore how systems, including economies, can reach critical states where small events trigger significant changes, emphasizing the ubiquity of instability and the potential benefits of antifragility in managing systemic risks.

Ubiquity, Complexity, and Sandpiles

• Introduction to Change: Change in various systems, including economies, can happen quickly and unpredictably, often following a mathematical principle where stability fosters instability.
• Sandpile Experiment: The analogy of a sandpile illustrates how systems can reach a critical state where a single grain can cause an avalanche. This was explored by physicists at Brookhaven National Laboratory in 1987, showing the natural emergence of a critical state through the addition of grains.

The Critical State

• Critical State Definition: This state refers to a balance point where minor changes can lead to significant consequences, analogous to phase transitions in physics or critical mass in nuclear reactions.
• Unpredictability: The critical state leads to unpredictability as the entire system becomes hypersensitive, with each new grain of sand potentially causing avalanches of varying sizes.

Fingers of Instability

• Concept: The sandpile model shows how grains connect into “fingers of instability” across the pile, where a chain reaction can lead to an avalanche of any size based on where the grain falls.
• Economic Implications: In economics, these fingers represent interconnected risks where small events can cascade into larger crises.

A Stable Disequilibrium

• Minsky’s Insight: Economist Hyman Minsky suggested that prolonged stability leads to greater instability, where the longer a system remains stable, the more severe the eventual collapse might be.
• Economic Sandpiles: Economic systems can be seen as sandpiles where small avalanches (economic adjustments) prevent large, catastrophic collapses. However, preventing these small avalanches might lead to massive instability.

Antifragile Systems

• Antifragility: Drawing from Nassim Nicholas Taleb’s “Antifragile,” the article discusses how systems that benefit from stress (antifragile systems) are composed of fragile parts, allowing for improvement through adversity.
• Economic Application: Economies that tolerate small, unpleasant economic events might avoid massive economic collapses by not allowing “fingers of instability” to grow too interconnected.

Conclusion

• Ubiquity of Critical States: The article concludes that the phenomenon of critical states is not just theoretical but ubiquitous in nature, economics, and social systems, explaining why unpredictable upheavals occur.
• Implications for Policy: The discussion extends to how economic policies might inadvertently contribute to systemic risk by preventing smaller economic corrections.

Ubiquity, Complexity, and Sandpiles – Mauldin Economics

There is a secret law that governs sandpile collapses: the power-law. It governs a lot more than mere sandpiles: Size of cities, wealth, avalanches, earthquakes, stock market crashes, wars and more.

“The mathematical law that shows why wealth flows to the 1%”:

• Power Law Distribution: Wealth distribution follows a power law, where a small number of people hold a disproportionately large share of wealth. This is similar to how a few websites get the majority of traffic or how a few words are used most frequently in languages.
• Pareto Principle: Often referred to as the 80/20 rule, this principle is an example of power laws in economics, where roughly 80% of the effects come from 20% of the causes. In wealth distribution, this means that a very small percentage of people (the 1%) control a significant portion of the wealth.
• Feedback Loops: Wealth begets more wealth; those with capital can invest it, leading to returns which increase their wealth further. This feedback loop makes it difficult for those at the bottom to climb up the wealth ladder.
• Network Effects: In social and economic systems, connections and networks amplify the advantages of the already wealthy. The rich have better access to opportunities, information, and influential people, further concentrating wealth.
• Mathematical Models: Jha discusses how models like the “preferential attachment” or “rich get richer” model explain why certain entities (like websites or companies) grow disproportionately larger over time. This can be applied to wealth distribution where those who start with more resources tend to accumulate more.
• Inequality and Social Structure: The article connects these mathematical laws to real-world inequalities, suggesting that structural changes might be necessary to address the concentration of wealth at the top.
• Occupy Movement: The piece was published during the time of the Occupy Wall Street movement, using the movement’s focus on the 1% vs. the 99% to illustrate the relevance of power laws in economic disparity.
• Critique of Current Economic System: Jha implies that understanding these laws might push for a reevaluation of how economic policies are made, potentially leading to more equitable distribution mechanisms or regulations.

The mathematical law that shows why wealth flows to the 1% | Alok Jha | The Guardian

Feedback loop: When the past heavily influences the future. A feedback loop mechanism is a key driver of systems that follow the power law.

And now we get to war, the ultimate collapse. Sean Gourley shows us how war follows the power law.

Sean Gourley on the mathematics of war – YouTube

The number one thing you need to be worried about is war. In particular, nuclear war. That’s the ultimate crash.