Many years ago, someone I knew changed lanes on the highway when the traffic ahead slowed suddenly. He then ran into the back of a car in the other lane. When he recounted the incident to me, he said it was not his fault.

He became angry with me when I pointed out that he shared some of the blame. I tried to convince him that he had to take some of the blame simply because of his presence. It might not surprise you that he did not appreciate my point of view,

• “There is no blame.”

We tend to blame outside influences. “Systems thinking shows us that there is no outside; that you and the cause of your problems are part of a single system. The cure lies in your relationship with your ‘enemy.’” (Senge page 67.) Don’t blame the people when they do the best they can within the system in which they operate.

When you encounter a surly government employee, remember they work for a system that does not recognize you as the customer. They owe their allegiance to other bureaucrats and politicians, not to you. You do not influence a system that you do not pay directly.

Comments

“The only thing necessary for the triumph of evil is for good men to do nothing.” (This quote has been attributed to many men.)

Do not try to absolve yourself of errors made by a system in which you play a part. Ask yourself, “what could I have done?” If you have no answer, don’t blame others.

The renowned business consultant W. Edwards Deming addressed the same subject by distinguishing between special causes and common causes. Common causes result from the structure of the system. Special causes result from actions outside the system. When errors have a common cause, don’t blame individuals who follow the design of the system.

Deming also pointed out that a person should not treat special causes as common causes. If one person makes many errors due to poor vision, it makes little sense to require everyone in the system to wear the same corrective lenses.

Be careful when you caste blame on someone in the same system of which you play a part.

Conclusion

As a worker, don’t blame a fellow worker operating in the same system to which you belong. As a manager, don’t blame a worker doing his best in a system you designed.

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The country we call Iran has presented one big problem for the U.S. for nearly 5 decades. One president after another has proposed or implemented solutions to what they define as “the problem.” They usually focus on preventing Iran from obtaining nuclear weapons.

But, does the possession of nuclear weapons represent the entirety of the “Iran problem,” or does it make up only part of a much larger problem? If Iran had no possibility of having a nuclear weapon, would they simply become a benign actor amongst Middle Eastern countries?

I do not pretend to know the answer to this question. I do strongly suspect that our “leaders” have never asked that question. Have been feeding us half elephants as substitutes for the whole thing.

Dividing an elephant

• “Dividing an elephant in half does not produce two elephants.”

As logical as it may seem, dividing a problem into smaller problems seldom works. If you have a big problem, you must treat it as such. You may have to take sequential steps to the solution, but you must coordinate these steps to solve the single problem.

The integrated, holistic, nature of living systems requires that they must remain intact to realize their full benefit. The whole equals more than the sum of its parts.

Governments build their reputations on promising half an elephant as if it were one elephant. Treating government spending and taxation as independent issues amounts to dividing the government interventionist elephant.

Commentary

For years I have had a suspicion of the word “compromise.” Instead of putting in the time and effort to identify and understand the magnitude of a problem and to create a single solution, compromisers frequently divide a single problem into two and implement two unrelated solutions.

Quite several years ago, I had the opportunity to study the Japanese management style. One thing that set the Japanese managers apart was that they did not believe in compromise. They believed instead in concencise. They took whatever time it took to get complete agreement, which meant total commitment to the solution. They did not seek compromise on partial solutions.

This approach frustrated American managers when they worked together. It seemed to take the Japanese so long to make a plan of action, but when they were ready to act, the Americans could not keep up.

Conclusion

When faced with a problem, assure yourself that you understand its scope and design a plan of action that addresses the entirety of the problem.

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Try to explain to a five-year-old that he cannot have a pretty cake and eat it at the same time too.

Or, explain to the increasing number of socialists that they cannot have all the “free stuff” before they make their own contribution to that stuff.

You can have your cake

• “You can have your cake and eat it too—but not at once.”

Sometimes dilemmas only appear as opposing choices. For example, the false choice between “low cost” and “high-quality.” The short-term cost of higher quality may lead to both lower cost and higher quality in the long run.

The “low cost” bidding process employed by government frequently leads to the early crumbling of vital infrastructure.

Comment

I have frequently counseled people that the lowest-cost equipment often turns out to cost far more than more expensive equipment. Lower-cost equipment frequently wears out quicker and requires replacement sooner. Or, it may not meet your needs for as long as more expensive equipment.

Take some time to think about this “law.”

Conclusion

I caution those who want the state to let them eat their cake now and wonder where it went when they go back for more.

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Research has shown that most fortunes begin with small regular saving. It seems like a small thing, but do a little math, and you will see. Remember, saving is easy. It happens automatically when you spend less. If you earn $30,00 and you spend $28,000, you have saved $2,000 without any effort.

Small Changes

Small systemic changes

Chaos theoreticians speak of the “butterfly effect” in which a butterfly flaps its wings in some distant location causing a local storm in the future. Although this so-called “butterfly effect” serves mostly as a metaphor, it does give a sense of the importance of small events.

Frequently, the most obvious solutions either don’t work or make matters worse. Small, targeted, actions, however, can often produce significant and enduring changes. These high leverage actions do not seem apparent to the participants in the system. A one percentage point increase in the rate of saving might, through increased investment, improve long-term consumption by more than 15 percent.

Comment

It’s my turn to implement one of these laws.

Think of a situation in which you took more action than you needed.

Or

Think of a small action you took that had a surprisingly large result. These frequently do not draw attention the way large impressive actions do.

Conclusion

Next problem you encounter, ask yourself, “What is the smallest action you can take to achieve the desired outcome?”

I have avoided providing examples of government action that amounted to more effort than needed. They usually expend more effort than needed.

Introduction

The police chief called a gathering of members of the police force to make an important announcement. It took a while for the entire force, including office staff, to congregate in the conference room. The chief felt that this announcement was so important that he had the 911 operators redirect their calls to an answering service.

The chief entered the conference room, which instantly grew quiet. He had indicated in his memo calling this meeting that its importance overshadowed the brevity of the announcement.

The chief began, “I will make this brief. After extensive research, followed by lengthy debate, I finally convinced the city council to ban the sale of ice cream within the city limits during the months from May through October inclusive.

“We have decided to enact this ordinance because of the close correlation between the sale of ice cream and the rate of crime. You can see the relationship in this chart.”

Cause and Effect

Cause and effect in systems

People intervening in market systems frequently commit the error of equating proximity of events with cause and effect. Human systems share the fundamental characteristic that cause and effect do not occur closely in time and space. We may not see the results of the actions we take today either in the same time or the same place. What appears like a sound expenditure now, may prove catastrophic when the effect finally reaches the market.

Comment

I think the story I recount above was originally told as a joke, but if you stop in a small town and discover the absence of ice cream, don’t be surprised.

Does the rise in oil prices really cause price inflation, or do separate events converge to cause the price of gas and the general level of prices to rise at the same time?

The Federal Reserve buys a large amount of government securities from national banks and pays for them by increasing bank reserves; shortly after that, “loan” volume and the quantity of “money” increase. Is this evidence of the “money pumping” they accuse the Fed of doing, or is it the result of the pent-up demand for credit already present in the system?

It’s your turn to come up with an example.

Conclusion

The next time you see an expert present two curves and state the chart proves the causal connection between the two sets of data, ask yourself, “Does this correlation evidence causation or coincidental results from separate causes?

Only an examination of the systemic structure can provide a meaningful answer.

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Introduction

A racecar driver desperately wants to win this race. He has his foot near, but not yet on, the floor, but his car is only going as fast as his nearest competition. Although his tachometer is right on the redline, the driver thinks that if he pushes the car just a little more, he can pass the competition and win the race. He pushes the gas pedal all the way to the floor, and his car quickly moves ahead of the competition. Since the driver has only half a lap left to go, he thinks that this race is in the bag.

With only a quarter of a lap left to go, a plume of smoke suddenly rises from under the hood of the car, which suddenly grinds to a halt. The frustrated driver sits in his car watching the rest of the field pass him. Instead of taking second place, he will now have to settle for last place.

The structure of the race car system had more influence on the performance of the system than did the element we call the driver.

Faster is Slower

“Faster is slower in systems”

Remember the tortoise and the hare. Systems operate at the pace allowed by their structure. Pushing them too fast will cause delay or breakdown.

In our persistent efforts to create economic growth, we forget that the economy has a natural rate of growth. Rapid rates of business growth, brought on by market intervention, frequently outrun the capability of businesses to generate capital to support that growth. High rates of broader economic growth have the same effect. High rates of consumption eat away at capital growth, which slows future consumption.

Comment

Some of the most successful businessmen have recognized, even if it’s just by intuition, the capabilities of their business systems. They have recognized the capabilities of their manufacturing operation, and more importantly, they understand that customers will not buy more products than they need.

The desire to make more and more money has frequently destroyed formerly viable businesses. If a businessman wants more profit faster, maybe instead of pushing his current business beyond its limits, he should sell that business and buy another one.

Politicians who frequently have no experience running businesses want “the economy” to grow more rapidly. They have this false notion that creating bigger and better numbers will get them reelected. Their intervention usually contributes to the boom-and-bust cycles, which I will discuss in another article.

Conclusion

Always understand the limits of the system in which you are operating. Attempting to complete a job in one day with the system designed to operate at half that speed will frequently lead to equipment damage and a much longer time frame.

Remember, people are also part of the operating system’s structure. An important part of the manager’s job consists of assessing the capabilities of the workforce. Expecting more from workers than what they are capable of can lead to poor performance, frustration, and burnout, on the part of workers.

Could Iran, which had been a problem across the globe for nearly fifty years, have been dealt with more effectively if done slowly and methodically than just bombing them and expecting a positive outcome?

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Introduction

When learning about systems, one should never forget that a person always represents an element of a system. To point out a universal example, remember that the universe (pun intended) consists of a system from which we can never escape.

Don’t worry, however, although the small structural changes we make will not affect the universe for eons. But think about it.

The unspoken cure for many systemic diseases consists of death. When faced with that choice, most people choose misery in life rather than certain peace in death. The oppression in many countries reaches that extreme.

Look at Iran, Russia, China…you fill in your own examples.

Worse Cure

Cure can be worse than the disease in systems

When we don’t account for the feedback from changes we make, we sometimes don’t see the full impact of our actions. Our central banking system increases the money supply to stimulate the seemingly slow economy. The misinformation sent by this artificial cure causes malinvestment, which leads to a depression worse than the apparent, but natural, slow down.

Sometimes the easy, familiar, solutions have no effect. Indeed, sometimes they become addictive and dangerous. By misguiding market players, monetary expansion creates an addictive dependence that eats away at healthy productive investment.

Comment

In the world of markets (i.e., economics), government intervention is one of the best examples of a cure worse than the disease. The “Great Depression” provides the most prominent example. Intervention caused the combination of boom and bust. To cure the bust, the government intervened in ways that prolonged the misery for more than a decade.

Government spending, financed in large part by monetary expansion, distorts market prices in a way that causes people to act rationally based on flawed feedback. If you have concerns about income inequality, think about how the cures for this “problem” actually make it worse.

I have one last comment (or question): Why do we consider a house, which continually deteriorates, an investment?

Conclusion

Remember that the structure of a system always has more control over the behavior of that system than any action within the system.

In Peter Senge’s book, The Fifth Discipline, around which I have formed this series of articles, he poses the question: What individual has the most influence on how fast a huge ocean liner can turn?

The answer: the designer.

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Introduction

We humans, suffer the same weaknesses as other creatures: we have a strong will to survive. We really don’t have a high capacity for creativity. If we find a way out of one problem, we tend to try the same solution when we encounter a problem that looks similar to one that we encountered before.

The second weakness with our way of solving problems is assuming that the best way to resolve problems is to take the same way out that got us into the difficulty.

By applying systems thinking we will realize the validity of the following rule of systems thinking:

The Easy Way Out

The easy way out usually leads back into a system

Familiar solutions to apparently similar problems usually keep us mired in the same problem.

Adjusting tax rates to cure the “Social Security” problem eventually leads us back into the difficulty caused by the structure of this unsustainable “Ponzi” scheme.

Making significant structural changes to a poorly designed system will have more effect on eliminating recurring problems than making small changes to processes that only address symptoms.

Comment

We can attribute many business failures to not understanding this simple “law.” Many business managers do not understand the simple fact that as the world changes, the structure of their business must also change.

The business consultant Chris Argyris identified this same problem and referred to it as single-loop learning. The single-loop learner starts with an assumption that may work for a while. He assumes that if the system does not produce the desired results, they must try harder.

The double-loop learner, on the other hand, questions early assumptions and makes many changes as needed.

Businesses frequently look for the easy way out. They either adapt or fail. The market acts as a strict enforcer. The Government, on the other hand, being afraid of losing constituents, always takes the easy way out.

I admit that I benefited from the Government’s ignorance (consciously or not) of this “law.” The legislature continues to disguise the “Ponzi” called Social Security by perpetuating the myth of a “trust fund.” In truth, the SSA transfers money from current taxpayers to current Social Security recipients.

At some point, the government must eliminate the Social Security system.

Conclusion

Be careful of implementing solutions to seemingly familiar problems. The system producing patterns of behavior similar to those produced by another system in a different time and place may have a very different structure. These patterns may correlate with each other without having any causative relationship. Do what you must to understand the structures of the system in question before taking action.

The ease of action may act as a warning by itself.

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Introduction

Have you ever heard of someone coming down with a severe headache, taking a large dose of headache medicine, and feeling just fine in a couple of hours? The next day, the same thing occurs. The person checks into the hospital several weeks later to find out they have brain cancer. Four days later, that person is dead.

I hate to start this article with such a morose example, but it addresses the idea expressed in this article. Symptomatic solutions to problems frequently just disguise the underlying structural problems.

I have written in other articles about the systems archetype known as shifting the burden. When a person seeks a quick, easy solution, the system’s structural influence causes the problem to worsen.

Systemic Behavior Grows Worse

“Behavior grows better before it grows worse.”

Any success at overcoming structural influence will only last for a short while. We find simple, “easy,” interventions enticing because they seem to work — in the short term. Then, again, compensating feedback takes over and things get even worse.

Economic stimulus gets people to spend more money. This causes a nominal increase in GDP. It also causes a lack of savings and investment, resulting in reduced employment and reduced availability of goods in the future.

Comment

I want you to think about situations in which you’ve encountered a problem that seemed rather easy to solve at the beginning, only to have it become much worse at some time in the future. Because politicians don’t understand the complexity of the American economy, they frequently implement short-term solutions that have a devastating effect in the long term. Neither the self-professed “capitalists” nor the self-professed “socialists” have a true understanding of the structure of a healthy economy.

I will give you a short list of cases in which short-term solutions lead to long-term problems. I will discuss these in greater length in the future.

Expanding the money supply helps finance short-term problems, but in the long-term, it leads to resource misallocation and eventually to inflation.

Wage and price controls seem like a simple solution, but they ignore the importance of price signals and inevitably cause greater harm.

Conclusion

The short-term success achieved by symptomatic solutions applied to a system does not always translate into the results the system produces.

When addressing any problem, always examine the system’s structure. Remember that systemic structure always has more influence than any short-term action.

The American stock market provides a perfect example. When an analyst compares current market behavior with past behavior, always ask: “Does the market have the same structure today as it did when the previous pattern formed?”

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Introduction

While in college, I had an American history professor who said that when a bully pushed a kid into a corner and kept pushing him, the kid would eventually push back (he phrased it a bit more crudely, but adults might read this article). You might have guessed that he told this story to explain how countries will react. Push them too far, and they will respond.

That professor was giving an example of the systems law highlighted in this article.

Push Back Law

The harder you push a system, the harder the system pushes back

Because systems contain “compensating feedback,” well-intentioned interventions frequently stimulate responses from the system that offset the benefits of the original interventions.

The higher lawmakers raise minimum wages, the higher the resulting unemployment.

The more lawmakers attempt to regulate segments of the market, the more frequent the occurrence of black markets or illegal activities.

Comment

When cars increase their speed, they burn more gasoline for each additional mile per hour. The air, which is part of this transportation system, “pushes back.”

Law enforcement activities frequently receives “push back” from the community to which it belongs.

If you strike a brick wall, you will receive “push back” commensurate with the blow you deliver.

I am sure you can think of better examples. I just want to prime your thinking.

Conclusion

Don’t get this “law” confused with the frequently misunderstood Newton’s 3^rd law of motion. The response from pushing a system will seldom, if ever, be equal and opposite. Just keep in mind that any action against a system will stimulate a response. Don’t say, “I did not expect anything to happen.” Always say, “I did not expect that to happen.”

I could come up with better examples of this “law.” I want you to think of your own.

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Introduction

Systems have “feedbacks,” or a transfer of information, that we frequently do not recognize when they occur. For example, when you flip a lightswitch the light comes on. That gives us information that the switch, the electricity, and the light bulb are all working.

When we fill a bathtub, we see the water level rise. That feedback information helps us judge when to turn the water off.

When a baseball pitcher throws a pitch and the batter ducks, the pitcher has feedback that tells him the pitch was too close.

Systems Law

Today’s problems come from yesterday’s ‘solutions’

The presence of feedbacks represents one of the distinctive characteristics of systems. Many of the processes in systems create information that, when fed back into the system, change the input to the next iteration. Feedback becomes particularly crucial in human systems — i.e., systems that include humans as an element. For example, the system that includes both car and driver provides feedback to the driver so that he knows when to speed up, swerve, or brake.

The solutions that we apply to today’s problems simply shift the problem to a different time or space. The people who inherit the “new problem” frequently don’t recognize it as the return of an old problem.

This explains why many market interventions seem to address problems for which solutions have already been applied.

Comment

For those who have seen the movie “Groundhog Day” this systems law might have a ring of familiarity. Our problems frequently seem eerily familiar. Sometimes we get the sense that we should have foreseen today’s problem

People frequently ask, “Why do we have this problem?” They then start looking for solutions without examining what they might have done in the past that contributed to today’s problem.

Looking into the future, with every action you take today will create feedback that will surely influence what happens tomorrow.

Conclusion

I do not expect to dwell on these “systems laws” as I go through them. I will bring them up in one way or another in the future.

I only hope you will think about them now and consider them as you view your actions and those of others.

Introduction

While serving in the Army in South Korea during the mid-1960s, I operated a petroleum tank farm. As with most equipment in Korea at the time, those tanks were in pretty shoddy condition. One day, the sergeant who ran the petroleum operation reported to me that one of the large tanks had sprung a leak.

We received the petroleum in rail cars from Pusan, roughly 100 miles away, then had to truck the petroleum another 5 miles from the railhead. We did have another storage tank, but because demand from the units we served was so high, we needed the most efficient solution we could find.

With the counsel of my sergeant and an Air Force sergeant, I decided we could fill the tank with water to the level of the drainage spout and pump the petroleum from the tank with minimal water contamination.

Unbeknownst to me, the logistics Major had ordered a train of empty tanker cars from Pusan. Needless to say, the Major did not appreciate that I had caused him to travel about 200 miles with an empty tank train for no reason.

This cute story has meaning to me only because, upon reflection several years later, it caused me to realize I am a systems thinker. That does not make me any sort of genius. It just means that I ask a lot of annoying questions.

The Austrian method of studying economics attracted me because it employs systems thinking.

Systems Laws

In this article, I want to introduce you to systems thinking by listing “The Laws of The Fifth Discipline” from The Fifth Discipline by Peter Senge, to stand in for Systems Theories until I have had the opportunity to assemble and consolidate a more comprehensive description of Systems Theories. In later articles, I will add my annotations to his “laws.”

Today’s problems come from yesterday’s “solutions.”

The harder you push, the harder the system pushes back.

Behavior grows better before it grows worse.

The easy way out usually leads back in.

The cure can be worse than the disease.

Faster is slower.

Cause and effect are not closely related in time and space.

Small changes can produce big results—but the areas of highest leverage are often least obvious.

You can have your cake and eat it too—but not at once.

Dividing an elephant in half does not produce two elephants.

There is no blame.

Conclusion

I could summarize my description of systems thinking by saying that everything relates to everything, but that would destroy much of its value by making it too broad. I will give you a more definitive description in later articles.

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I apologize to my regular readers for my extended absence. I have had a lot of accidents and mishaps over the last several weeks that have prevented me from writing regularly. The clincher, however, was that my computer crashed. I won’t go into much detail, but it was bad enough that I had to buy a new computer, install it, and reinstall all my software. I cleverly saved all of the data from my old computer. One never realizes how many wires, programs, and passwords it takes to get their system back up and running. The “downtime” led me to reassess some of my goals in my publishing activities. I will soon get back on schedule. I’m not yet ready to commit to a regular schedule, but I hope to make it more frequent than before.

I want to make it clear that this publication is more about clear thinking than about economics and free markets. I use free markets as my primary vehicle for demonstrating the importance of clear thinking. I’m offering a brief introduction to systems thinking to demonstrate how systems thinking can be used to examine more deeply some of the things you were told.

Politicians and economic commentators make many statements that you are supposed to accept without question. After all, they spent a good bit of time studying the subject. Regardless of your level of expertise, these subjects are too important to you personally not to spend a little extra time making sure that you fully understand them. Systems thinking provides you with a powerful tool to ask a few extra questions. I want to introduce the subject by discussing what is commonly known as “the broken window theory.”

The broken window theory is attributed to Frederick Bastiat. The title is derived from a story about a shoemaker who comes to work one day and finds one of his windows broken. He calls a glazier and has the glass replaced, which is done in relatively short order. The shoemaker has to spend a certain amount of money to get the class replaced. Many economists will look at this incident and say that’s good because now the glazier has more income, raising the income level of the economy.

Bastiat wants to point out that although the glazier will indeed make more money, one has to ask on what the shoemaker would have spent that money. Because of the expense of replacing the window, the shoemaker must delay his plans to buy new equipment for his shoemaking business. We cannot say with certainty whether the general economy benefits from the glazier’s income, or whether the shoemaker would have contributed more had he been able to retain the money to buy the equipment he needed.

Every economic activity consists of two parts: first, the price that one person must give up in the present to receive a good or service; second, the cost, which consists of what that person has to give up in the future.

Now, I would like you to connect to personal exercise. Take out your latest pay stub, or whatever record you have that shows your gross pay and deductions. Gross pay is the amount you negotiated with your employer at the time of your employment. Now, focus on your deductions, about which you did not negotiate with your employer. Think about the goods and services that you might have bought if that money had not been taken from you. To possibly get benefits in the future, don’t forget that you’re giving something up in the process. Which do you value more: the “benefits” from those deductions, or the consumer goods or services you could’ve bought with that same money?

These are the kinds of questions that I plan to address over the coming weeks and months. These are not questions just for economists. These are questions you must answer daily.

I will get back to the subject of systems thinking in my next publication.

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The three levels at which we can understand the performance of systems consist of Events, Patterns of Behavior, and Systemic Structure. Working from the bottom up, each level provides more knowledge about what influences the system’s behavior.

This diagram shows the direction of influence—most important influence at the top.

Description Graphic

The description begins from the least informative level of performance—Events—and proceeds to the most informative, and influential, level—Systemic Structure.

Events

Events, which amount to one-time occurrences, consist of a single result from the systemic processes.

Examples of events:

· the current price rose 5% this today

· long-term interest rates rose 1/8 th of a point yesterday

· Sears sold 10,000 socks yesterday.

Systems produce results one event at a time. An event shows us what the system has produced at a single place and time, but a single event provides little explanation of events in the past or evidence about what the system will produce in the future.

Patterns of Performance

Patterns of behavior show a series of events that trace out a pattern over time. These patterns reveal a much deeper level of understanding of system performance. They show behavior over time.

Examples of patterns of behavior:

· interest rates have fallen (risen) for 14 consecutive months

· stock prices have fluctuated within a 20% range for three years

· bank reserves have trended upward for the past 93 years

A series of events produced by a single system form a pattern of systemic behavior. Patterns of systemic behavior provide a history of what a system has produced in the past.

Based on the assumption that the system will produce results in the future similar to those it produced in the past, we can predict future events (or results). Patterns of behavior do not help us to understand why a system produces the results that it does.

The Theory of Variation, which I will describe in a later publication, can help us determine whether the system has produced a particular event or whether an external influence has caused a variance in behavior.

Systemic Structure

Systemic Structure provides the fundamental determinant of system behavior. The deepest understanding of systemic performance comes from understanding the systemic structure.

To understand why a system produces specific results (events or patterns), one must know the system’s structure.

A person cannot make lasting changes to the behavior of a system without first understanding its Structure. The Structure of a system determines the limits of its performance—what events it will produce and what patterns those events will form.

Examples of systemic Structure:

· fractional reserve banking, the Fed’s power to create reserves, which influence money creation at banks, and mental models of those in charge. A structure that influences the natural market forces to expand credit without limit (reinforcing process)

· the capacity of the government to spend money. It drives increasing taxes, borrowing, and inflationary monetary policy (reinforcing process)

· the free market system. It gives the greatest influence to consumers for all levels of the market (generally balancing process)

Complex Adaptive Systems

One type of systemic structure, known as a “complex adaptive system”, can make predicting patterns in systemic behavior difficult. These systems, which include all living systems, have the ability to observe their own patterns of behavior and modify their structure and change their behavior to some degree.

And you wonder why most economic and market forecasters don’t do it too well.

Conclusion

I have given you only a brief introduction to a very complex subject. I hope I have helped you see why the more you understand the structure of a system, the more you will understand its performance. Be careful how much you believe predictions about a system’s performance from someone who does not understand its structure.

Remember, the designer has a greater effect on a racecar’s performance than the driver does.

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Statistical charts provide one of the most effective tools for conveying information (and misinformation) When a commentator presents a graph as “proof” of their argument, view it with great care.

Graphics can help describe patterns of behavior and provide evident of structural connections, but they never prove anything. Scientists must continually subject theoretical “proofs” to disconfirmation, or they do not qualify as science.

I frequently use charts to help explain statements, but I try not to present them as proof.

Charts seldom have any use without comparing at least two sets of data. I find line charts helpful to explain changes over time. I use line charts to compare either linear changes or percentage changes.

In a recent publication, I made a brief explanation of the difference between linear scales (measuring absolute changes) and semi-log scales (measuring relative changes). In this post, I want to clarify the explanation.

To illustrate the difficulty of visualizing relative changes, I offer this riddle from my files.

The Lily-Pad Riddle

A powerful illustration of the exponential effect of change comes not from a scientist or a futurist, but from a child’s riddle:

“On day one, a large lake contains only a single small lily pad. Each day the number of lily pads doubles, until on the thirtieth day the lake is totally choked with vegetation. On what day was the lake half full?”

The answer, of course, is the twenty-ninth day. It takes twenty nine days for the first half of the lake to fill with lily pads, but only twenty-four additional hours for the lake to become overwhelmed.

Welcome to day twenty-nine. Imagine that the proliferating lily pads represent the expanding array of changes that face the world. Suppose that the human resilience required to address these changes is represented by the lake’s capacity to accommodate the lily pads. What happens as day twenty-nine approaches?

Daryl R. Conner
Managing at the Speed of Change

Comparing Charts

I will use two charts to help clarify the differences between a linear chart and a semi-log chart.

These two charts reflect the same data; the only difference between the charts consists of the vertical scales. I will explain the red box outlines after you have had time to examine the charts.

Linear Chart

Semi Log Chart

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Although the charts represent precisely the same array of data points, they appear significantly different. Changing only the vertical scale changes the information conveyed in each chart.

The first chart (linear) shows the number of units of change regardless of the time interval. People use linear charts to demonstrate absolute changes (e.g. increase in the quantity of water in gallons regardless of time, or an increase in the number of dollars regardless of the length of time).

The second chart (semi-log) shows the number of units of change relative to the length of time. One might express these changes in quantities as rates of change (e.g., increase the quantity of water in gallons per hour, or an increase in the number of dollars per year).

One good way to visualize these changes consists of visualizing the length of time it takes for the absolute change to occur. I have drawn red boxes to help you visualize absolute change versus relative change.

Specific Charts—Excess Reserves vs. Money Supply (M2)

I wanted the readers of this publication to have a couple of real-life examples to see how changing the manner in which they have data presented to them can influence their interpretation.

I have chosen to present the same data streams (Excess Reserves vs. Money Supply (M2)) in two different formats: linear and semi-log. Does changing your chart change your interpretation of the data?

Linear

The linear chart clearly shows that the amount of excess reserves increased more in 2008 than in 2020.

In those same years, 2008 and 2020, respectively, M2 increased by a far greater amount in 2020 than in 2008.

Semi-log

The semi-log chart shows clearly that excess reserves increased by a dramatically greater percentage in 2008 than in 2020.

In those same years, 2008 and 2020, respectively, M2 increased by a greater percentage in 2020 than in 2008.

Which chart provides a more accurate representation of the relationship between excess reserves and M2? Should the larger percentage increase in excess reserves also have a larger percentage increase in M2?

Conclusion

How you have information presented to you will have a great deal to do with how you interpret that information. Charts provide an excellent way for people to see the same information from different perspectives. Writers should remember that different charts have different meanings to different people. When communicating, choose charts that clarify your meaning.

I have given an example of one graphic that I have used frequently: the semi-log chart. Semi-log charts provide a very useful tool for showing trends over a long period. Frequently, showing a rate of change carries more importance than the absolute numbers.

Charts never, by themselves provide any proof; they can, however, point the way.

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Last week, I published an article that hinted at the possibility that drawing conclusions from too little data can be misleading. I offered as an example a graph of the money supply (M2) with no comparison data. Some might conclude from that one graph that The Fed has been steadily expanding the money supply since 1985. But that conclusion may have flaws because of the limited data.

In a second graph, I presented data depicting activities at The Fed. Based on that data, some might conclude that the money supply should have jumped during 2008 – 2009. After all, does The Fed not control the money supply?

The proximity of the two graphs in my article might call either one or both of those conclusions into question.

In this article, I will take another look at the same data.

Combination

First, I combined the two graphs. Now, an observer can view two data series on a single graph. (I eliminated the required reserves because that added nothing to the analysis.)

In combining these two, I had to make one significant change. Since the number of “money dollars” (M2) amount to between 7 and 13 times the number of “reserve dollars,” I had to use two different scales: 1) Number of “money dollars” (M2) on the left in $billions and 2) Number of “reserve dollars” on the right in $millions.

These two changes help align the time frame for changes in these aggregates, but they lack one thing: rates of change. How rapidly has the quantity of money grown? How rapidly have the quantities of reserve balances grown? If, for example, total reserves rise by 20%, does the quantity of money increase by a comparable amount?

Rates of Change

To get some clue about the connections between the rate of changes in reserve balances and the rate of changes in the quantity of money, I have converted the scales on both the right and left axes to logarithmic scales.

Since many people seem not to fully grasp the concept of a logarithmic scale, I will give a brief layman’s description. (If I cannot make a logarithmic scale understandable, please consult with Doctor Google.)

On a logarithmic scale, for a value to double, the gap between the values remains the same; e.g., on a logarithmic scale, the distance between 4,000 and 8,000 equals the same distance as between 2,000 and 4,000. Thus, if an amount increases by 25% per year, on a logarithmic scale, that would result in a straight line, as opposed to the upward-sloping line that would result on a linear scale.

On this chart, I have converted the X-axes to a logarithmic scales to depict percentage increases better.

Increase in Excess Reserves

The logarithmic scales show that excess reserves (and, by deduction, total reserves) increased by a much larger percentage during the “quantitative easing (QE1)” than during QE2, activated in response to COVID.

According to popular theory, when excess reserves increased so dramatically in response to QE1, the quantity of money (M2) should have increased at a comparable rate.

In 2021, the increase in excess reserves (QE2) should have caused a much smaller percentage increase in the money supply (M2) than in 2008, but the money supply (M2) increased much more rapidly. Do the rates of increase in the quantity of money confirm this “theory”? The graphs expose contradictory results.

The Quantity of Money

Using logarithmic scales, we can now see that the supply of money has grown at about the same percentage rate for nearly the entire period covered by these charts.

Contrary to the popular theory that ties monetary growth to reserve expansion, the quantity of money did not increase as expected with the implementation of QE1. During QE2, however, the growth in money did increase as the theory would predict.

The different results between “QE1” and “QE2” provides us with a disconfirmation of the theory that The Fed creates “money.”

Conclusion

I have written this article to accomplish two purposes. First, to show that a person should seldom use only one data set to draw any conclusions, particularly with living systems like markets. Second, to challenge some of the popularly accepted assumptions made by people commenting about markets.

I have combined the data sets on the money supply and excess bank reserves to determine the correlation.

Because I consider rates of change important for these comparisons, I have converted the values on the X axes to logarithmic scales.

Having made these adjustments to these charts, I can make some more definitive statements about the relationships between the actions of The Fed and the money supply (M2).

First, the actions The Fed during QE1 had little or no effect on the quantity of money (M2) in the system. During QE2 The Fed may have facilitated, but did not represent the primary cause, of the increase in the quantity of money (M2).

Second, the lack of correlation between the level of excess reserves and the growth in the money supply (M2) confirms (does not prove) the importance of other influences outside The Fed on the growth in the money supply (M2).

I want to make the important point that you should never take affirmative statements about economic data without question. Many popular comments about market behavior contain false or misleading statements.

Be careful what you believe.

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This article has more to do with clear thinking than it does about the important, but widely misunderstood, subjects of money and banking. When one of the many talking heads on YouTube and elsewhere makes definitive statements about money and banking, and the federal reserve stop to ask yourself whether all the pieces actually fit together.

I don’t pretend to understand the many theories and calculations used in the cosmological argument of Albert Einstein, but I do understand that the theories based on sound thinking cannot stand in contradiction. If, as Einstein theorized, nothing in the universe can travel faster than the speed of light, then gravity cannot, as Newton assumed, travel instantaneously from the Sun to the Earth. One of the two theories must have a flaw.

It turns out that both are sufficiently accurate if one limits the boundaries of the system. In a sufficiently limited system Newton’s assumption provides acceptably accurate answers. Beyond that limit, one must rely on the General Theory of Gravitational force.

Fully understanding a proposition requires knowing which assumptions to include in your analysis. In terms of systems thinking, a person must clearly understand the extent of the system’s boundaries. Set the boundaries too narrowly, and you will probably leave out important influences. Set the boundaries too broadly, and you define the system at a level of complexity that the human mind—even with the aid of computer modeling—cannot comprehend.

To demonstrate, I have included two line graphs related to money, banking, and bank reserves.

Line Graph A

The first graph plots the quantity of money (M2) over the period from 1985 to 2020[1]. What definitive statements can you make about the money supply over that period of time?

You might say that, over that period, The Fed has had a pretty steady hand on the money supply until 2020. Whatever effect monetary expansion has had on inflation has been steady if not a bit too high. Based on this data, one can ignore monetary expansion as a contributing factor to any dramatic economic events.

I would argue that the graph does not contain enough data to make definitive statements about monetary expansion and the role of The Fed.

To demonstrate, I will refer to the second graph.

Line Graph B

The following graph shows the reserve balances required of banks to either hold at The Fed or in their vaults (dotted line) and the excess reserves of depository institutions (solid line). I have also noted changes in reserve requirements on the approximate dates[2].

The data plotted on this graph reflect changes in reserve accounts that should have a significant influence on the quantity of money (”money dollars.”)

Required Reserves Ratios (%)

I indicated the changes in required reserves ratios only to highlight a significant influence that analysts seldom mention. When analyzing the quantity of money, one should always ask whether required reserves ratios have changed. In 2020, The Fed acknowledged that the required reserves ratios had become meaningless after the 2009 reserve expansion and eliminated them altogether.

Reserve Balances Required

You will notice that the reserve balances have changed little during this entire period.

(In a future post, I will explain why required reserves ratios should consist of a multiple, not a fraction.)

Excess Reserves

Until 2009, excess reserves had the most influence on the money-creating power of banks. When the system contained larger excess reserves, banks could create more money dollars. When the amount of excess reserves declined, banks could create fewer money dollars.

The Fed would influence the amount of excess reserves primarily through open market purchases and sales of financial assets. Banks with deficit reserves would borrow from banks with excess reserves, thus the Fed Funds Rate served as a bellwether for market rates, but it has never been a “base rate” for the bond market. Banks traded Fed Funds in a closed market.

Most of the time, sufficient credit demand existed that when banks had excess reserves, they would create “money dollars” to buy interest-bearing assets. Finally, the largest source of monetary expansion resulted from the purchase of federal government debt.

All that changed in 2009 when The Fed performed what they deceptively referred to as “quantitative easing.”

When The Fed bought a large quantity of government securities in 2009, traditional theory held that the market would see a comparable increase in the quantity of money. If you look at graph A, you will see that did not happen. Maybe The Fed does not “control” the expansion of the money supply. But, did the reserves expansion in 2020 reassert the historical connection?

The events of 2020 actually pointed to the government as the culprit in monetary inflation.

Conclusion

This article has a singular purpose: to encourage you to question everything you hear from market and financial analysts. Take a lesson from the physical scientists: no theory exists beyond examination.

[1] I have restricted these graphs to this time frame to limit the number of rather dramatic events. Also, The Fed discontinued tracking the data on the bottom graph.

[2] The first two changes have different ingredients that play an insignificant roles.

Introduction

I have on my schedule the writing of an article about the creation of money. Before starting this note, I watched a couple of videos about money and bonds. These presentations contain numerous errors that call the validity of the entire presentation into question. I want to offer some new information that readers can reformulate as questions to test any one of these presentations.

As I have in many other publications, I want to avoid confusion by offering a precise definition of “money.”

Definition of Money

Money consists of any economic good, or any claim on such a good, that serves as a general medium of Indirect Exchange and that acts as a final means of payment.

I compare the understanding of money to the understanding of gravity. Gravity acts the same always and everywhere. To walk down the street, you don’t need to know much about gravity. You can be reasonably sure your next step won’t spring you into space.

On the other hand, learning a bit more about gravity will help you design a F1 car.

For years, F1 designers explained that wider tires would not improve cornering speeds because physics dictated that a car could never corner at a force greater than gravity. Then, someone put a wing on the car. With the use of aerodynamic downforce and wider tires, F1 cars now corner at about 4 times the force of gravity.

“Money”

For the general use of “money,” a person normally does not need to look “under the hood,” but those looking at videos and reading accounts of “money” might need more precise information.

So who decides what to use as “money,” and who creates “money?”

I can provide you with answers far simpler than you might expect.

First, individuals in a defined market choose what to use as “money.” In the U.S. market, people have chosen to use dollars authorized by the government as “money.”

Second, only banks create the new dollars that people can use as” money.” Banks create those dollars in two basic forms: demand liabilities and currency.

Most people understand the creation of demand liabilities regardless of the method by which customers use them: check, debit card, phone scan, etc. The bank simply records the liability in its ledger.

Currency, however, tends to confuse people somewhat. Many think that dollar-denominated currency comes from The Government or The Fed. Remember who delivers the currency to the public. As long as currency resides at The Fed or in the bank vault, people cannot use it as money. Those dollars consist of bank reserves, and, as reserves, people cannot simultaneously use them as “money.”

To avoid common confusion, the act of accepting customer notes (AKA making “loans”) does not create “money.” Banks create “money dollars” in exchange for promises to pay (usually more) dollars in the future. Banks can create “money dollars” for other purposes, such as paying salaries, buying furniture, and purchasing office supplies. Bank regulations, however, restrict what assets banks can own.

Summary

Markets choose what to use as money. The U.S. markets have chosen to use the dollars authorized by the U.S. Government.

Only banks have the authority to create new dollar-denominated “money.” The Fed does not create or hold any dollars used by the market as “money.” Dollars at The Fed act as reserves to “back” dollars at banks. Those dollars, which, by regulation, remain inaccessible to the market, cannot logically also serve as “money.”

Because of its importance, I will have more to write about “money” in the future.

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If you believe that all dollars “are” money, I have a whole bag of dollars (about $165) that I will exchange for one $5 bill.

Bag of Money

I have used the image of shredded dollars to demonstrate that use determines what people do or do not use as “money.” The definitions of many other words depend on their use. Worms, for example.

If you dig in most fertile soil, you will find worms. People often add worms to compost heaps to aid the composting process. When asked to identify the squirmy critters, the composters will respond, “worms.” When you insert a fishing hook into the squirmy critters, they suddenly become “bait.”

In a similar manner peole do not (or cannot) use dollars held in reserve as “money.” To test this assumption, I will use two criteria to determine which ones people can use as “money.”

· Commodity or claim on commodity

· Common acceptance

Commodity in Circulation

People can use any commodity in circulation commonly accepted as a medium of indirect exchange as “money.”

Bills in Circulation

People can use bills and notes in circulation as claims, commonly accepted as a medium of indirect exchange, as “money.”

Transaction (demand) Accounts

People commonly use transaction (demand) accounts as media of indirect exchange, commonly accepted as “money.”

Deposits at The Federal Reserve or Cash in a Bank Vault

People cannot use deposits at The Federal Reserve or cash in bank vaults as a medium of indirect exchange or “money.” Reserves, wherever they exist, cannot satisfy either of our tests.

· Commodity OR claim on commodity

The small word “OR” plays a critical role in this test. “Cash” at The Fed, in whatever form, cannot act as money and reserves at the same time.

· Common acceptance

Accounts at The Fed do not meet the criteria for common acceptance. Federal Reserve regulations prohibit individuals from having accounts at The Fed. Banks cannot transfer their claims at The Fed to individuals.

Zero Reserve Requirements

The implementation of zero reserve requirements has confused the issue of whether The Fed creates “money.” We now have a system in which all monetary claims consist only of claims on claims on claims, but in no case do banks have claims on their accounts at The Fed that they can transfer to individuals. Simultaneously, bank balances at The Fed fail the test of common acceptance.

Conclusion

Never have dollar reserves at The Federal Reserve been used as “money.” For most of The Fed’s history, dollars held at The Fed by banks were disqualified because they could not act as reserves and money simultaneously. At the same time, those dollars failed to meet the criteria of common acceptance.

Currently, bank balances at The Fed do not qualify as “money” because banks cannot transfer these “assets” to anyone who is not a member of The Federal Reserve System.

Please stop misleading people into believing The Fed creates “money.”

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Last week, I published on The Free Market Center Journal an article entitled “Price Determination and Interest Rates”. In addition, on May 6, 2024, I published “How to Calculate Interest Rates.” These two articles provide support and an introduction to this week’s article about “Why The Fed Cannot Change Interest Rates.”

This article has nothing to do with the power of The Fed or its influence on financial markets. I have watched The Federal Reserve implement “monetary policy” for over six decades. At one point The Fed attempted to influence the creation of money (by banks) to hit a target objection. Later, it shifted its objective to hitting target interest rates in the Fed Funds market.

For this paper, I care not whether The Fed ever achieved any of its target objectives. I want my readers to understand the calculation of interest rates and whether any entity can change any interest rate unilaterally. Erroneous thinking about the mechanics of any part of a system tends to reinforce erroneous thinking about other parts of the same system.

Many explanations of the monetary system begin with erroneous claims about the power of The Fed to “raise/lower” interest rates. I hope that if people see the error of their basic premise, they will examine the additional thinking derived from it.

Think, for example, of the numerous cries to “save our democracy” in a country that does not have a democracy.

I have provided the following diagram as a reference and reminder of the two parties required to establish an interest rate.

Interest – Time Preference

The idea of time preference provides the foundation for the concept of interest. Time preference simply means that goods and services in the present have a higher value to an individual than exactly the same good in the future.

To clearly comprehend time preference, you need to separate time preference from a cessation of wants. Time preference does not mean that people value things in the future less after satisfying their wants in the present. It means that the individual must choose between having the thing in the present OR having the same thing in the future.

Time preference holds true regardless of where the item falls on the current preference scale. For example, if a person prefers three cupcakes today over three bananas today, they would still value three bananas today more than three bananas in the future.

In summary, for an individual to trade a quantity of a good in the present for the same good in the future would require a larger quantity of the good in the future. We refer to the difference between the quantity in the present and the quantity in the future as interest.

I think you can already see that you need to know the present quantity and the future quantity to calculate the interest.

Importance of Relative Time

So far, I have referred to the “present” and “future” without specifying the time interval between now and the future. To determine the value of the good in the present and in the future, the parties must know the units of time that pass between now and the specified future. With the passage of each unit of time between now and the future, the value will decline in the minds of the parties.

In general, the further in the future, the lower the time preference—and thereby the value—for the good in the future.

Interest Rates

Real Interest Rates

We call the processes of all systems the “flow.” The accumulation of “flow” amounts to the “stock.” We state “stock” in terms of accumulated units of “flow.” “Flow” consists of the changes in “stock” over a specified unit of time.

In the classic stock-and-flow model of the bathtub, the stock might consist of 100 gallons of water. We might state the flow in gallons per hour, even if the water flows for only five minutes.

The strict definition of an interest rate consists of the units of flow per unit of time. For example, if a party lends $1Million and expects $1.3Million at the end of three years, the interest rate would amount to $1Thousand per year.

But, we don’t state interest in that manner.

Marginal Interest Rates

What people normally call the “interest rate” actually refers to the “marginal interest rate.” To calculate the marginal interest rate, divide the actual interest rate (e.g., $ 1,000 per year) by the original loan amount ($ 1 million) to arrive at 0.10 (or 10%) per year.

Marginal interest rates (AKA interest rates) provide a way to compare interest rates for different loan amounts over different periods of time.

Conclusion

I have made numerous comments on various online accounts clarifying the fact that no entity, including The Federal Reserve, can unilaterally raise or lower interest rates. From these comments, a person might get the impression that I have an obsession with calculating interest rates.

I might have an obsession of sorts with clear thinking. The calculation of interest rates provides only one of many examples in which the use of inexact language leads to flawed thinking. If you take just a moment, you will recognize that The Federal Reserve does not have the control that many attribute to it over interest rates, the money supply, employment, or “the economy.”

I believe firmly in the “principle of limited information.” This principle means you need to make sure you have enough information to make sound statements—no more but certainly not less.

Aretha Franklin has provided the best advice to people making affirmative statements: “Think.”

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