You Want Me to Pay You … Why?

Fed Funds Rate goes negative
Negative rates burn wealth! ramcreations/Shutterstock

14 August 2019 – There’s been some hand wringing in the mass media recently about negative interest rates and what they mean. Before you can think about that, however, you have to know what negative rates are and how they actually work. Journalists Sam Goldfarb and Daniel Kruger pointed out in a Wall Street Journal article on Monday (8/12) that not so long ago negative interest rates were thought impossible.

Of course, negative interest rates were never really “impossible.” They used to be considered highly unlikely, however, because nobody in their right mind would be willing to pay someone else for taking money off their hands. I mean, would you do it?

But, the world has changed drastically over the past, say, quarter century. Today, so-called “investors” think nothing of buying stock in giant technology companies, such as Tesla, Inc. that have never made a dime of profit and have no prospects of doing so in the near future. Such “investors” are effectively giving away their money at negative interest rates.

Buying stock in an unprofitable enterprise makes sense if you believe that the enterprise will eventually become profitable. Or, and this is a commonly applied strategy, you believe the market value of the stock will rise in the future, when you can sell it to somebody else at a profit. This latter strategy is known as the “bigger fool theory.” This theory holds that doing something that stupid is a good idea as long as you believe you’ll be able to find a “bigger fool” to take your stock in the deadbeat enterprise off your hands before it collapses into bankruptcy.

That all works quite nicely for stocks, but makes less sense for bonds, which is what folks are talking about when they wring their hands over negative-interest-rate policy by central banks. The difference is that in the bond market, there really is no underlying enterprise ownership that might turn a profit in the future. A bond is just an agreement between a lender and a debtor.

This is where the two-fluid model of money I trotted out in this column on 19 June helps paint an understandable picture. Recall from that column that money appears from nowhere when two parties, a lender and a debtor, execute a loan contract. The cash (known as “credit” in the model) goes to the debtor while an equal amount of debt goes to the lender. Those are the two paired “fluids” that make up what we call “money,” as I explain in that column.

Fed Funds Rate

The Federal Reserve Bank is a system of banks run by the U.S. Treasury Department. One of the system’s functions is to ensure the U.S. money supply by holding excess money for other banks who have more than they need at the moment, and loaning it out to banks in need of cash. By setting the interest rate (the so-called Fed Funds Rate) at which these transactions occur, the Fed controls how much money flows through the economy. Lowering the rate allows money to flow faster. Raising it slows things down.

Actual paper money represents only a tiny fraction of U.S. currency. In actual fact, money is created whenever anybody borrows anything from anybody, even your average loan shark. The Federal Reserve System is how the U.S. Federal Government attempts to keep the whole mess under control.

By the way, the problem with cryptocurrencies is that they attempt to usurp that control, but that’s a rant for another day.

Think of money as blood coursing through the country’s economic body, carrying oxygen to the cells (you and me and General Motors) that they use to create wealth. That’s when the problem with negative interest rates shows up. When interest rates are positive, it means wealth is being created. When they’re negative, well you can imagine what that means!

Negative interest rates mean folks are burning up wealth to keep the economic ship sailing along. If you keep burning up wealth instead of creating it, eventually you go broke. Think Venezuela, or, on a smaller scale, Puerto Rico.

Negative Interest

Okay, so how do negative interest rates actually work?

A loan contract, or bond, is an agreement between a lender and a debtor to create some money (the two fluids, again). The idea behind any contract is that everybody gets something out of it that they want. In a conventional positive-interest-rate bond, the debtor gets credit that they can use to create wealth, like, maybe building a house. The lender gets a share in that wealth in the form of interest payments over and above the cash needed to retire the loan (as in pay back the principal).

Bonds are sold in an auction process. That is, the issuer offers to sell the bond for a face value (the principal) and pay it back plus interest at a certain rate in the future. In the real world, however, folks buy such bonds at a market price, which may or may not be equal to the principal.

If the market price is lower than the principal, then the effective rate of interest will be higher than the offered rate because what the actual market value is doesn’t affect the pay-back terms written on the loan agreement. If the market price is higher than the principal, the effective rate will be lower than the offered rate. If the market price is too much higher than the principal, the repayment won’t be enough to cover it, and the effective rate will be negative.

Everyone who’s ever participated in an auction knows that there are always amateurs around (or supposed professionals whose glands get the better of their brains so they act like amateurs) who get caught up in the auction dynamics and agree to pay more than they should for what’s offered. When it’s a bond auction, that’s how you get a negative interest rate by accident. Folks agree to pay up front more than they get back as principal plus interest for the loan.

Negative Interest Rate Policy (NIRP) is when a central bank (such as the U.S. Federal Reserve) runs out of options to control economic activity, and publicly says it’s going to borrow money from its customers at negative rates. The Fed’s customers (the large banks that deposit their excess cash with the Fed) have to put their excess cash somewhere, so they get stuck making the negative-interest-rate loans. That means they’re burning up the wealth their customers share with them when they pay their loans back.

If you’re the richest country in the world, you can get away with burning up wealth faster than you create it for a very long time. If, on the other hand, you’re, say, Puerto Rico, you can’t.

Measuring Project Success

 

 

Motorcycle ride
What counts as success depends on what your goals are. By Andrey Armyagov/Shutterstock

7 August 2019 – As part of my research into diversity in project teams, I’ve spent about a week digging into how it’s possible to quantify success. Most people equate personal success with income or wealth, and business success with profitability or market capitalization, but none of that really does it. Veteran project managers (like yours truly) recognize that it’s almost never about money. If you do everything else right, money just shows up sometimes. What it’s really all about is all those other things that go into making a success of some project.

So, measuring success is all about quantifying all those other things. Those other things are whatever is important to all the folks that your project affects. We call them stakeholders because they have a stake in the project’s outcome.

For example, some years ago it started becoming obvious to me that the boat tied up to the dock out back was doing me no good because I hardly ever took it out. I knew that I’d get to use a motorcycle every day if I had one, but I had that stupid boat instead. So, I conceived of a project to replace the boat with a motorcycle.

I wasn’t alone, however. Whether we had a boat or a motorcycle would make a difference to my wife, as well. She had a stake in whether we had a boat or a motorcycle, so she was also a stakeholder. It turned out that she would also prefer to have a motorcycle than a boat, so we started working on a project to replace the boat with a motorcycle.

So, the first thing to consider when planning a project is who the stakeholders are. The next thing to consider is what each stakeholder wants to get out of the project. In the case of the motorcycle project, what my wife wanted to get out of it was the fun of riding around southwest Florida visiting this, that and the other place. It turned out that the places she wanted to go were mostly easier to get to by motorcycle than by boat. So, her goal wasn’t just to have the motorcycle, it was to visit places she could get to by motorcycle. For her, getting to visit those places would fulfill her goal for the project.

See? There was no money involved. Only an intangible thing of being able to visit someplace.

The “intangible” part is what hangs people up when they want to quantify the value of something. It’s why people get hung up on money-related goals. Money is something everyone knows how to quantify. How do you quantify the value of “getting to go somewhere?”

A lot of people have tried a lot of schemes for “measuring” the “value” of some intangible thing, like getting where you want to go. It turns out, however, that it’s easy if you change your point of view just a little bit. Instead of asking how valuable it is to get there, you can ask something like: “What are the odds that I can get there?” Getting to some place five miles from the sea by boat likely isn’t going to happen, but getting there by motorcycle might be easy.

The way we quantify this is through what’s called a Likert scale. You make a statement, like “I can get there” and pick a number from, say, zero to five with zero being “It ain’t gonna happen” and five being “Easy k’neezie.”

You do that for all the places you’re likely to want to go and calculate an average score. If you really want to complete the job, you normalize your score by weighting the scores for each destination with how often you’re likely to want to go there, then divide by five times the sum of the weights. That leaves you with an index ranging from zero to one.

You go through this process for all of the goals of all your stakeholders and average the indices to get a composite index. This is an example of how one uses fuzzy logic, which takes into account that most of the time you can’t really be sure of anything. The fuzzy part is using the Likert scale to estimate how likely it is that your fuzzy statement (in this case, “I can get there”) will be true.

When using fuzzy logic to quantify project success, the fuzzy statements are of the form: “Stakeholder X’s goal Y is met.” The value assigned to that statement is the degree to which it is true, or, said another way, the degree to which the goal has been met. That allows for the prospect that not all stakeholder goals will be fully met.

For example, how well my wife’s goal of “Getting to Miromar Outlets in Estero, FL from our place in Naples” would be met depended a whole lot on the characteristics of the motorcycle. If the motorcycle is like the 1988 FLST light-touring bike I used to have, the value would be five. We used to ride that thing all day for weeks at a time! If, on the other hand, it’s like that ol’ 1986 XLH chopper, she might make it, but she wouldn’t be happy at the end (literally ’cause the seat was uncomfortable)! The value in that condition would be one or two. Of course, since Miromar is land locked, the value of keeping the boat would be zero.

So, the steps to quantifying project success are:

  1. Determine all goals of all stakeholders;
  2. Assign a relative importance (weight) to each stakeholder goal;
  3. Use a Likert scale to quantify the degree to which each stakeholder goal has been met;
  4. Normalize the scores to work out an index for each stakeholder goal;
  5. Form a critical success index (CSI) for the project as an average of the indices for the stakeholder goals.

Before you complain about that being an awful lot of math to go through just to figure out how well your project succeeded, recognize that you go through it in a haphazard way every time you do anything. Even if it’s just going to the bathroom, you start out with a goal and finish deciding how well you succeeded. Thinking about these steps just gives you half a chance to reach the correct conclusion.

Misconceptions About Maslow’s Hierarchy of Needs

Maslow's Pyramid
Maslow’s pyramid of needs analyzes human needs and arranges them in a hierarchy. By Shutter_M/Shutterstock

24 July 2019 – Abraham Harold Maslow (1908-1970) was a 20th century psychologist famous for describing human motivation as an hierarchy of needs in a 1943 paper entitled “A Theory of Human Motivation” published in Psychological Review. He was a central figure in the founding of Humanistic Psychology, which concentrates on studying mentally healthy humans.

You have to remember that Maslow did his most important work in the middle of the 20th century. At that time there was great popular interest in the works of Sigmund Freud, who worked with the mentally ill, and B.F. Skinner who mainly studied lower animals. Indeed, the entire arts-and-letters school of Surrealism explicitly drew inspiration from Andre Breton’s interpretation of Freud’s work. Despite (or perhaps because of) this interest in Freud and Skinner’s work, there had been little, if any, study of mentally healthy people.

Humanistic Psychologists felt these earlier studies were of limited value to understanding the healthy human mind. Maslow chose to study the workings of healthy human minds from all social strata, but he was especially interested in studying high achievers. For this reason those of us interested in organizational behavior find his humanists of particular interest. We kinda hope our organizations are populated with, and run by, mentally healthy humans, rather than Freud’s neurotics or Skinner’s lab rats!

Maslow’s emphasis on studying high achievers likely gave rise to the first misconception I want to talk about today: the idea that his work gives cover to elitist views. This elitist theory assumes that everyone strives to reach the self-actualization level at the top of the so-called “Pyramid of Needs” used to illustrate Maslow’s hierarchy, but that only an elite fraction of individuals reach it. Lesser individuals are doomed to wallowing in more squalid existences at lower levels.

The second misconception I want to treat today is a similar notion that people start out at the lower levels and climb slowly up to the top as their incomes rise. This theory substitutes a ladder for the pyramid image to visualize Maslow’s hierarchy. People are imagined to climb slowly up this ladder as both their income and social status increase. This, again, gives cover for elitist views as well as laissez-faire economics.

Maslow’s Conception

What Maslow’s Hierarchy really describes is a priority system that determines what people are motivated to do next. It has little to do with their talents, income or social status. To illustrate what I mean, I like to use the following thought experiment. This thought experiment involves Albert Einstein and it’s particularly appropriate because the Grizzled Genius loved thought experiments.

Albert Einstein’s greatest joy was becoming immersed in translating his imaginings about the physical universe into mathematical equations. This is an example of what Maslow called “peak experiences.” Maslow believed these were periods when self-actualized people (those engaged in satisfying their self-actualization need) are happiest and most productive.

Once in a while, however, Einstein would become hungry. Hunger is, however, one of those pesky physiological needs down at the bottom of Maslow’s Hierarchy. There’s nothing aspirational about hunger. It’s what Fredrick Herzberg called a “hygiene factor” or “demotivator.” Such needs are the opposite of aspirational.

If you’ve got an unsatisfied demotivator need, you become unhappy until you can satisfy it. If, for example, you’re hungry, or have a toothache, or need to pee, it becomes hard to concentrate on anything else. Your only thought is (depending on the nature of the unmet physiological need) to go to the bathroom, or the dentist, or, as in Einstein’s case, go find lunch.

The moral of this story is that people don’t sit somewhere for extended periods of time on a shelf labeled with one of Maslow’s categories. Rich people don’t float in a blissful self-actualizing state. Poor people don’t wallow in a miasma of permanently unmet physiological needs. People constantly move up and down the pyramid depending on what the most pressing unmet need of the moment is.

The hierarchy is therefore actually an inverted priority list. Physiological needs are more important than safety needs. When something frightens you – a safety need – the first thing that happens is you feel an urge to pee to take care of a physiological need to prepare your body for running like a scared rabbit. When you see a fast-moving Chevy bearing down on you, you immediately forget pride in that (esteem level) achievement award you just got.

Elitist Fallacy

A combination of confusion about how Maslow’s heirarchy works and his preference for studying high achievers has led many people to imagine his work gives cover for elitist views. If you’re predisposed to imagine that rich people, smart people, or those of high social status are somehow innately “better” than denizens of what 19th century novelist Edward Bulwer-Lytton called “the great unwashed,” then you’re an elitist. An elitist can derive great comfort by misinterpreting Maslow’s work. You can imagine there being a cadre of elite people destined to spend their lives in some ethereal existence where all lower needs are completely satisfied and life’s only pursuit is self actualization.

The poster child for elitism is 16th century theologian John Calvin. In Calvin’s version of Protestant theology everyone was tainted with original sin and doomed to an eternity in Hell. That was a pretty common view at the time of the Protestant Reformation. Calvin added an elitist element by hypothesizing that there was a limited number of individuals (the elect) whom God had chosen for salvation.

It’s called predestination and those folks got tickets into the elite ranks through no merit of their own. There was nothing anybody could do to beg, borrow, or steal their way in. God decided, while making the Universe in the first place, who was in and who was out based on nothing but His whimsey. (Sexist pronoun used specifically to make a point about Calvinism.)

Of course, the requirements of natural selection logically lead to everyone having a desire to be part of an elite. We all want to be different, like the Dada-esque avant garde group King Missile. That’s how DNA measures its success. Only elite DNA gets to have long-term survival.

So, elitism has a lot of natural appeal. This natural appeal accounts for all kinds of rampant racism and xenophobia. Misunderstanding Maslow’s heirarchy provides a pseudoscientific rationale for elitism. To the elitist, the fact that this view is completely mistaken makes no nevermind.

I hope that by now I have disposed of the elitist fallacy.

Economic Ladder Fallacy

Hoping that I’ve disposed of the idea that Maslow’s work gives cover to elitism, I’ll turn to the fallacy of imagining his hierarchy as an economic ladder. This puppy is a natural outgrowth of the Pyramid of Needs image. The top (self actualization) level of the pyramid is imagined as “higher” than the bottom (physiological) level.

This image actually works from the viewpoint that “lower” needs take precedence over “higher” needs in the same way that a building’s supporting foundation takes precedence over the walls and roof. Without a foundation, there’s nothing to support walls or a roof in the same way that without fulfilling physiological needs, there’s no motivation for, say, self actualization.

Think of it this way: dead people, whose physiological needs are all unmet, hardly ever want to run for President.

So, how do you reach something high? You use a ladder!

That’s the thinking that transforms the Pyramid of Needs into some kind of ladder.

If you’re a strict materialist (and way too many Americans are strict materialists) the “high” you care about reaching is wealth. Folks who haven’t understood last month’s posting entitled “The Fluidity of Money” often confuse income with wealth, so there’s some appeal to thinking about Maslow’s Hierarchy of Needs as a metaphor for income levels. That completes the economic-ladder fallacy.

With this fallacy, folks imagine that everyone starts out at the bottom of the ladder and, with time, hard work and luck, climbs their way to the top. There are obvious problems matching income levels with needs levels, but if you’re sufficiently intellectually lazy, you can unfocus your mind’s eye enough to render these problems invisible.

I especially get a kick out of efforts to use the idea of Engel curves (from economics) to make this ladder fallacy work. Engel curves map the desireability (measured as the demand side of the economics law of supply and demand) of a given good or product against a given consumer’s income level. If the good in question is, for example, a used Mazda Miata, the desirability may be high when the consumer has a low-to-moderate income, but low if that particular consumer has enough income to pay for a new Ferrari SF90 Stradale. If you want to, it is obvious you can somehow conflate Engel curves with the ladder idea of Maslow’s Heirarchy of Needs.

The problem with this thinking is, first, that the Ladder doesn’t make a lot of sense as a visualization for Maslow’s Heirarchy, since the latter is formost a priority-setting scheme; second, that Maslow’s Hierarchy has little connection to income; and, third, that Engel curves present an incomplete view of what makes a product desirable.

The elitist fallacy and the economic-ladder fallacy are not the only fallacies people, with their infinite capacity to generate cockamamie theories, can concoct in connection to Maslow’s work. They are just two that have come up recently in articles I’ve had occasion to read. I think analyzing them can also help clarify how the Hierarchy of Needs applies to understanding human behavior.

Besides, I’ve had a bit of fun knocking them around, and I hope you have, too.

The Fluidity of Money

Money exchange
Money is created in the exchange of credit for debt. Image by bluedog studio/shutterstock

19 June 2016 – I’m supposed to have some passing understanding of economics and accounting. I have, after all, a Master’s degree in Business Administration, for which I had to study Macroeconomics and Microeconomics, as well as Cost and Financial Accounting.

Howsomever, while trying to make sense of what folks call “Modern Monetary Theory” it dawned on me that, not only didn’t I have a clear concept of what money actually is, but the people babbling on about money and monetary policy aren’t any clearer on the concept than I am. A review of the differences between neoclassical economics based on Keynsian ideas and so-called Modern Monetary Theory reveals an incomplete understanding of money.

We all think we know what money is, and spout long winded and erudite-sounding loads of gobbledygook that only serve to prove, beyond a shadow of a doubt, that none of us have a clue what the stuff actually is!

I find that situation intolerable, and have set out to change it by trying real hard to come up with a theory that makes sense of all the stupid things we do with and say about money.

Now, I’m not a financial wizard, or a prize-winning economist, or even a whiz-bang developer of computer models of the global economy. I’m just some schmuck with some basic math ability, a little time on my hands, and the desire to make sense of something that it seems the “experts” haven’t wrapped their brains around, yet. So, I’ve thought about this problem a bit, and have a hint of an answer that I want to run up the flagpole to see if anyone salutes.

If this essay triggers something in the brain of somebody smart that sets him, her or it thinking in a new direction about money, I’ll count it time well spent.

So, here goes … .

In science, we try to make sense of anything we don’t fully comprehend by developing some kind of conceptual model that helps us predict what will happen in any given situation. The fact that we currently haven’t a clue what will actually happen when, for example, the Federal Government runs up huge deficits for a very long time, indicates that we’re very far from knowing what we’re talking about with regard to money.

I generally try to model things poorly understood through analogy with things that are well understood. I’ve developed a two-fluid model of money by analogy to certain ideas in classical physics. It seems to work decently for the situations I’ve applied it to.

Analogy with Momentum

Specifically, the model draws an analogy with Newtonian momentum, which is a conserved vector quantity – meaning that the total momentum in a closed system cannot be changed, and that the quantity involves both a magnitude and a spatial direction.

For our analogy to be useful, we need to also use the idea of generalized coordinates, which allow the idea of “direction” to extend beyond strictly cartesian spatial coordinates (motion in straight lines). For example, a bicycle drive chain wraps around two sprockets and has flexible spans linking them, so its motion certainly does not follow along a single cartesian coordinate, yet there is a well-defined path along which any two points on the chain follow each other, maintaining their separation (measured along the path). That allows us to measure motion along the path by a generalized coordinate.

In Newtonian mechanics, momentum is exchanged between objects, which are thought of as components of a system, through the action of forces. Mathematically, the magnitude and direction of the force equals the rate of flow of momentum between the objects.

Newton’s third law, which states that every force is paired with an equal and opposite reaction force, is just an expression of conservation of momentum in that every force (representing a transfer of momentum from one object to another) is paired with an equal and opposite transfer of momentum from the second object to the first. This takes care of maintaining conservation of momentum.

Take, for example, a person stepping off a boat onto a dock. At first, everything is (as seen from the perspective of the dock) stationary. The momentum of an object is defined as the object’s mass (amount of material) times its velocity (a vector combining speed and direction). Since both the person and the boat are stationary (meaning they both have a velocity of zero), the total momentum of the system of person + boat is zero.

Then, the person applies a force to the boat in a direction away from the dock. The Newton’s-third-law reaction force is a push by the boat on the person toward the dock. That’s how the person actually gets to the dock. The boat pushes him/her toward it!

The boat moves away from the dock. The person moves toward the dock. So, the directions of the two momenta are opposite. The speeds of the person and boat automatically (or maybe you’d like to say “magically”) adjust to keep the total momentum of the system equal to zero at all times. That is, at every instant the momentum of the person is equal and opposite to the momentum of the boat.

Money

In the theory of money that I’m proposing, money itself is analogous to momentum. Altogether, it’s conserved. That is, it cannot be created or destroyed. There’s always the same amount of “money” – zero!

What we’re used to thinking of as “money” is only half the story, which is why there’s so much confusion over it. Borrowing from double-entry bookkeeping, we’ll call what we usually think of as money as credit. Everyone who understands double-entry bookkeeping knows that for every credit, there is an equal (and opposite) entry called a debit. For our purposes, we’ll shorten that word to something we’re all familiar with: debt.

Debt is the other side of the analogy, which we tend to ignore and that accounts for all the confusion.

We’re going to visualize credit and debt as fluids because they’re measured as continuous, as opposed to quantized, variables. That means that they’re representable by real numbers as opposed to integers. So, nobody has a problem with dividing seven dollars ($7) into two portions each containing three and a half dollars ($3.50). Current usage is to round everything to the nearest cent, or hundredth of a dollar, but that’s for convenience and not wanting to be bothered with truly small change.

At one time, we had half-penny ($0.005) coins, but we don’t do that anymore.

Okay, so “money” actually represents credit and debt in equal amounts, which consequently always add up to zero. Whenever money is created, it’s created as equal amounts of credit and debt.

Money creation always requires activity by two cooperating entities: a creditor and a debtor. Credit is created and transferred from the creditor to the debtor. An equal quantity of debt is created and flows from the debtor to the creditor. “Money” consists of these paired fluids, which flow through the economy via paired interactions between creditors and debtors. Money is created by an interaction that creates equal amounts of credit and debt, and the words “creditor” and “debtor” simply indicate the direction of flow.

Once created, the money flows around in the economy through paired transactions in which credit flows one way and debt the other.

Wealth

This visualization allows us to separate the concepts of “money” and “wealth.” Wealth refers to tangible and intangible assets, such as commodities and intellectual property. Wealth is very definitely not conserved. When a contractor builds a house, he or she creates wealth from, essentially, nothing. The contractor then sells the house to the new owner in a binary transaction that transfers credit to the contractor and debt to the owner.

We’ll leave out discussion of what happens to the wealth represented by the house, since this essay is about money, and money is not wealth.

The owner previously got the credit through a transaction with a lender in which money was created as a transfer of credit to the owner and debt to the lender. The lender can then, for example, package the debt up into something called a “collateralized debt obligation,” and exchange it with somebody else for an equivalent amount of credit. The lender then transfers that credit to another prospective home owner in exchange for an equivalent amount of debt, and the merry-go-round keeps turning.

Unlike wealth, which was created from nothing, the total of credit minus debt in the system remains zero at all times.

It is interesting to note that wealth appears through the creation of a pattern in the physical universe. For example, bricks used by a contractor to build a house start out as a less-organized pile. The contractor creates wealth by arranging those bricks in a house-like pattern. The owner has no use for the disorganized pile of bricks, but has a use for them when arranged as a house. Similarly, the contractor had no use for the raw clay that went into the bricks until the brick manufacturer rearranged it into the pattern we call “bricks.”

Historically, folks’ fascination with the credit side of money has led them to confuse “money” with “wealth.” They’re entirely different things. One is a medium of exchange related to entries in a bookkeeper’s ledger, the other is a real thing related to patterns in the physical world.

I hope this essay manages to help make sense of the money nonsense!

Stick to Your Knitting

Man knitting
Man in suit sticking to his knitting. Photo by fokusgood / Shutterstock

6 June 2019 – Once upon a time in an MBA school far, far away, I took a Marketing 101 class. The instructor, whose name I can no longer be sure of, had a number of sayings that proved insightful, bordering on the oracular. (That means they were generally really good advice.) One that he elevated to the level of a mantra was: “Stick to the knitting.”

Really successful companies of all sizes hew to this advice. There have been periods of history where fast-growing companies run by CEOs with spectacularly big egos have equally spectacularly honored this mantra in the breach. With more hubris than brains, they’ve managed to over-invest themselves out of business.

Today’s tech industry – especially the FAANG companies (Facebook, Amazon, Apple, Netflix and Google) – is particularly prone to this mistake. Here I hope to concentrate on what the mantra means, and what goes wrong when you ignore it.

Okay, “stick to your knitting” is based on the obvious assumption that every company has some core expertise. Amazon, for example, has expertise in building and operating an online catalog store. Facebook has expertise in running an online forum. Netflix operates a bang-up streaming service. Ford builds trucks. Lockheed Martin makes state-of-the-art military airplanes.

General Electric, which has core expertise in manufacturing industrial equipment, got into real trouble when it got the bright idea of starting a finance company to extend loans to its customers for purchases of its equipment.

Conglomeration

There is a business model, called the conglomerate that is based on explicitly ignoring the “knitting” mantra. It was especially popular in the 1960s. Corporate managers imagined that conglomerates could bring into play synergies that would make conglomerates more effective than single-business companies.

For a while there, this model seemed to be working. However, when business conditions began to change (specifically interest rates began to rise from an abnormally low level to more normal rates) their supposed advantages began melting like a birthday cake left outside in a rainstorm. These huge conglomerates began hemorrhaging money until vultures swooped in to pick them apart. Conglomerates are now a thing of the past.

There are companies, such as Berkshire Hathaway, whose core expertise is in evaluating and investing in other companies. Some of them are very successful, but that’s because they stick to their core expertise.

Berkshire Hathaway was originally a textile company that investor Warren Buffett took over when the textile industry was busy going overseas. As time went on, textiles became less important and, by 1985 this core part of the company was shut down. It had become a holding company for Buffett’s investments in other companies. It turns out that Buffett’s core competence is in handicapping companies for investment potential. That’s his knitting!

The difference between a holding company and a conglomerate is (and this is specifically my interpretation) a matter of integration. In a conglomerate, the different businesses are more-or-less integrated into the parent corporation. In a holding company, they are not.

Berkshire Hathaway is known for it’s insurance business, but if you want to buy, say, auto insurance from Berkshire Hathaway, you have to go to it’s Government Employees Insurance Company (GEICO) subsidiary. GEICO is a separate company that happens to be wholly owned by Berkshire Hathaway. That is, it has its own corporate headquarters and all the staff, fixtures and other resources needed to operate as an independent insurance company. It just happens to be owned, lock, stock and intellectual property by another corporate entity: Berkshire Hathaway.

GEICO’s core expertise is insurance. Berkshire Hathaway’s core expertise is finding good companies to invest in. Some are partially owned (e.g., 5.4% of Apple) some are wholly owned (e.g., Acme Brick).

Despite Berkshire Hathaway’s holding positions in both Apple and Acme Brick, if you ask Warren Buffet if Berkshire Hathaway is a computer company or a brick company, he’d undoubtedly say “no.” Berkshire Hathaway is a diversified holding company.

It’s business is owning other businesses.

To paraphrase James Coburn’s line from Stanley Donen’s 1963 film Charade: “[Mrs. Buffett] didn’t raise no stupid children!”

Why Giant Corporations?

All this giant corporation stuff stems from a dynamic I also learned about in MBA school: a company grows or it dies. I ran across this dynamic during a financial modeling class where we used computers to predict results of corporate decisions in lifelike conditions. Basically, what happens is that unless the company strives to its utmost to maintain growth, it starts to shrink and then all is lost. Feedback effects take over and it withers and dies.

Observations since then have convinced me this is some kind of natural law. It shows up in all kinds of natural systems. I used to think I understood why, but I’m not so sure anymore. It may have something to do with chaos, and we live in a chaotic universe. I resolve to study this in more detail – later.

But, anyway … .

Companies that embrace this mantra (You grow or you die.) grow until they reach some kind of external limit, then they stop growing and – in some fashion or other – die.

Sometimes (and paradigm examples abound) external limits don’t kick in before some company becomes very big, indeed. Standard Oil Company may be the poster child for this effect. Basically, the company grew to monopoly status and, in 1911 the U.S. Federal Government stepped in and, using the 1890 Sherman Anti-Trust Act, forced its breakup into 33 smaller oil companies, many of which still exist today as some of the world’s major oil companies (e.g., Mobil, Amoco, and Chevron). At the time of its breakup, Standard Oil had a market capitalization of just under $11B and was the third most valuable company in the U.S. Compare that to the U.S. GDP of roughly $34B at the time.

The problem with companies that big is that they generate tons of free cash. What to do with it?

There are three possibilities:

  1. You can reinvest it in your company;

  2. You can return it to your shareholders; or

  3. You can give it away.

Reinvesting free cash in your company is usually the first choice. I say it is the first choice because it is used at the earliest period of the company’s history – the period when growth is necessarily the only goal.

If done properly reinvestment can make your company grow bigger faster. You can reinvest by out-marketing your competition (by, say, making better advertisements) and gobbling up market share. You can also reinvest to make your company’s operations more effective or efficient. To grow, you also need to invest in adding production facilities.

At a later stage, your company is already growing fast and you’ve got state-of-the-art facilities, and you dominate your market. It’s time to do what your investors gave you their money for in the first place: return profits to them in the form of dividends. I kinda like that. It’s what the game’s all about, anyway.

Finally, most leaders of large companies recognize that having a lot of free cash laying around is an opportunity to do some good without (obviously) expecting a payback. I qualify this with the word “obviously” because on some level altruism does provide a return in some form.

Generally, companies engage in altruism (currently more often called “philanthropy”) to enhance their perception by the public. That’s useful when lawsuits rear their ugly heads or somebody in the organization screws up badly enough to invite public censure. Companies can enhance their reputations by supporting industry activities that do not directly enhance their profits.

So-called “growth companies,” however, get stuck in that early growth phase, and never transition to paying dividends. In the early days of the personal-computer revolution, tech companies prided themselves on being “growth stocks.” That is, investors gained vast wealth on paper as the companies’ stock prices went up, but couldn’t realized those gains (capital gains) unless they sold the stock. Or, as my father once did, by using the stock for collateral to borrow money.

In the end, wise investors eventually want their money back in the form of cash from dividends. For example, in the early 2000s, Microsoft and other technology companies were forced by their shareholders to start paying dividends for the first time.

What can go wrong

So, after all’s said and done, why’s my marketing professor’s mantra wise corporate governance?

To make money, especially the scads of money that corporations need to become really successful, you’ve gotta do something right. In fact, you gotta do something better than the other guys. When you know how to do something better than the other guys, that’s called expertise!

Companies, like people, have limitations. To imagine you don’t have limitations is hubris. To put hubris in perspective, recall that the ancients famously made it Lucifer’s cardinal sin. In fact, it was his only sin!

Folks who tell you that you can do anything are flat out conning your socks off.

If you’re lucky you can do one thing better than others. If you’re really lucky, you can do a few things better than others. If you try to do stuff outside your expertise, however, you’re gonna fail. A person can pick themselves up, dust themselves off, and try again – but don’t try to do the same thing again ‘cause you’ve already proved it’s outside your expertise. People can start over, but companies usually can’t.

One of my favorite sayings is:

Everything looks easy to someone who doesn’t know what they’re doing.

The rank amateur at some activity typically doesn’t know the complexities and pitfalls that an expert in the field has learned about through training and experience. That’s what we know as expertise. When anyone – or any company – wanders outside their field of expertise, they quickly fall foul of those complexities and pitfalls.

I don’t know how many times I’ve overheard some jamoke at an art opening say, “Oh, I could do that!”

Yeah? Then do it!

The artist has actually done it.

The same goes for some computer engineer who imagines that knowing how to program computers makes him (or her) smart, and because (s)he is so smart, (s)he could run, say, a magazine publishing house. How hard can it be?

Mark Zuckerberg is in the process of finding out.

Fed Reports on U.S. Economic Well-Being

Federal Reserve Building
The Federal Reserve released the results of its annual Survey of Household Economics and Decisionmaking for calendar year 2018 last week. Image by Thomas Barrat / Shutterstock

29 May 2019 – Last week (specifically 23 May 2019) the Federal Reserve Board released the results of its annual Survey of Household Economics and Decisionmaking for CY2018. I’ve done two things for readers of this blog. First, I downloaded a PDF copy of the report to make available free of charge on my website at cgmasi.com alongside last year’s report for comparison. Second, I’m publishing an edited extract of the report’s executive summary below.

The report describes the results of the sixth annual Survey of Household Economics and Decisionmaking (SHED). In October and November 2018, the latest SHED polled a self-selected sample of over 11,000 individuals via an online survey.

Along with the survey-results report, the Board published the complete anonymized data in CSV, SAS, STATA formats; as well as a supplement containing the complete SHED questionnaire and responses to all questions in the order asked. The survey continues to use subjective measures and self-assessments to supplement and enhance objective measures.

Overall Results

Survey respondents reported that most measures of economic well-being and financial resilience in 2018 are similar to or slightly better than in 2017. Many families have experienced substantial gains since the survey began in 2013, in line with the nation’s ongoing economic expansion during that period.

Even so, another year of economic expansion and the low national unemployment rates did little to narrow the persistent economic disparities by race, education, and geography. Many adults are financially vulnerable and would have difficulty handling an emergency expense as small as $400.

In addition to asking adults whether they are working, the survey asks if they want to work more and what impediments they see to them working.

Overall Economic Well-Being

A large majority of individuals report that, financially, they are doing okay or living comfortably, and overall economic well-being has improved substantially since the survey began in 2013

  • When asked about their finances, 75% of adults say they are either doing okay or living comfortably. This result in 2018 is similar to 2017 and is 12%age points higher than 2013.

  • Adults with a bachelor’s degree or higher are significantly more likely to be doing at least okay financially (87%) than those with a high school degree or less (64%).

  • Nearly 8 in 10 whites are at least doing okay financially in 2018 versus two-thirds of blacks and Hispanics. The gaps in economic well-being by race and ethnicity have persisted even as overall wellbeing has improved since 2013.

  • Fifty-six percent of adults say they are better off than their parents were at the same age and one fifth say they are worse off.

  • Nearly two-thirds of respondents rate their local economic conditions as “good” or “excellent,” with the rest rating conditions as “poor” or “only fair.” More than half of adults living in rural areas describe their local economy as good or excellent, compared to two-thirds of those living in urban areas.

Income

Changes in family income from month to month remain a source of financial strain for some individuals.

  • Three in 10 adults have family income that varies from month to month. One in 10 adults have struggled to pay their bills because of monthly changes in income. Those with less access to credit are much more likely to report financial hardship due to income volatility.

  • One in 10 adults, and over one-quarter of young adults under age 30, receive some form of financial support from someone living outside their home. This financial support is mainly between parents and adult children and is often to help with general expenses.

Employment

Most adults are working as much as they want to, an indicator of full employment; however, some remain unemployed or underemployed. Economic well-being is lower for those wanting to work more, those with unpredictable work schedules, and those who rely on gig activities as a main source of income.

  • One in 10 adults are not working and want to work, though many are not actively looking for work. Four percent of adults in the SHED are not working, want to work, and applied for a job in the prior 12 months. This is similar to the official unemployment rate of 3.8% in the fourth quarter of 2018.

  • Two in 10 adults are working but say they want to work more. Blacks, Hispanics, and those with less education are less likely to be satisfied with how much they are working.

  • Half of all employees received a raise or promotion in the prior year.

  • Unpredictable work schedules are associated with financial stress for some. One-quarter of employees have a varying work schedule, including 17% whose schedule varies based on their employer’s needs. One-third of workers who do not control their schedule are not doing okay financially, versus one-fifth of workers who set their schedule or have stable hours.

  • Three in 10 adults engaged in at least one gig activity in the prior month, with a median time spent on gig work of five hours. Perhaps surprisingly, little of this activity relies on technology: 3% of all adults say that they use a website or an app to arrange gig work.

  • Signs of financial fragility – such as difficulty handling an emergency expense – are slightly more common for those engaged in gig work, but markedly higher for those who do so as a main source of income.

Dealing with Unexpected Expenses

While self-reported ability to handle unexpected expenses has improved substantially since the survey began in 2013, a sizeable share of adults nonetheless say that they would have some difficulty with a modest unexpected expense.

  • If faced with an unexpected expense of $400, 61% of adults say they would cover it with cash, savings, or a credit card paid off at the next statement – a modest improvement from the prior year. Similar to the prior year, 27% would borrow or sell something to pay for the expense, and 12% would not be able to cover the expense at all.

  • Seventeen percent of adults are not able to pay all of their current month’s bills in full. Another 12% of adults would be unable to pay their current month’s bills if they also had an unexpected $400 expense that they had to pay.

  • One-fifth of adults had major, unexpected medical bills to pay in the prior year. One-fourth of adults skipped necessary medical care in 2018 because they were unable to afford the cost.

Banking and Credit

Most adults have a bank account and are able to obtain credit from mainstream sources. However, sub- stantial gaps in banking and credit services exist among minorities and those with low incomes.

  • Six percent of adults do not have a bank account. Fourteen percent of blacks and 11% of Hispanics are unbanked versus 4% of whites. Thirty-five percent of blacks and 23% of Hispanics have an account but also use alternative financial services, such as money orders and check cashing services, compared to 11% of whites.

  • More than one-fourth of blacks are not confident that a new credit card application would be approved if they applied—over twice the rate among whites.

  • Those who never carry a credit card balance are much more likely to say that they would pay an unexpected $400 expense with cash or its equivalent (88%) than those who carry a balance most or all of the time (40%) or who do not have a credit card (27%).

  • Thirteen percent of adults with a bank account had at least one problem accessing funds in their account in the prior year. Problems with a bank website or mobile app (7%) and delays in when funds were available to use (6%) are the most common problems. Those with volatile income and low savings are more likely to experience such problems.

Housing and Neighborhoods

Satisfaction with one’s housing and neighborhood is generally high, although notably less so in low-income communities. While 8 in 10 adults living in middle- and upper-income neighborhoods are satisfied with the overall quality of their community, 6 in 10 living in low- and moderate-income neighborhoods are satisfied.

  • People’s satisfaction with their housing does not vary much between more expensive and less expensive cities or between urban and rural areas.

  • Over half of renters needed a repair at some point in the prior year, and 15% of renters had moderate or substantial difficulty getting their landlord to complete the repair. Black and Hispanic renters are more likely than whites to have difficulties getting repairs done.

  • Three percent of non-homeowners were evicted, or moved because of the threat of eviction, in the prior two years. Evictions are slightly more common in urban areas than in rural areas.

Higher Education

Economic well-being rises with education, and most of those holding a post-secondary degree think that attending college paid off.

  • Two-thirds of graduates with a bachelor’s degree or more feel that their educational investment paid off financially, but 3 in 10 of those who started but did not complete a degree share this view.

  • Among young adults who attended college, more than twice as many Hispanics went to a for-profit institution as did whites. For young black attendees, this rate was five times the rate of whites.

  • Given what they know now, half of those who attended a private for-profit institution say that they would attend a different school if they had a chance to go back and make their college choices again. By comparison, about one-quarter of those who attended public or private not-for-profit institutions would want to attend a different school.

Student Loans and Other Education Debt

Over half of young adults who attended college took on some debt to pay for their education. Most borrowers are current on their payments or have successfully paid off their loans.

  • Among those making payments on their student loans, the typical monthly payment is between $200 and $299 per month.

  • Over one-fifth of borrowers who attended private for-profit institutions are behind on student loan payments, versus 8% who attended public institutions and 5% who attended private not-for-profit institutions.

Retirement

Many adults are struggling to save for retirement. Even among those who have some savings, people commonly lack financial knowledge and are uncomfortable making investment decisions.

  • Thirty-six percent of non-retired adults think that their retirement saving is on track, but one-quarter have no retirement savings or pension whatsoever. Among non-retired adults over the age of sixty, 45% believe that their retirement saving is on track.

  • Six in 10 non-retirees who hold self-directed retirement savings accounts, such as a 401(k) or IRA, have little or no comfort in managing their investments.

  • On average, people answer fewer than three out of five financial literacy questions correctly, with lower scores among those who are less comfortable managing their retirement savings.

The forgoing is an edited extract from the Report’s Executive Summary. A PDF version of the entire report is available on my website at cgmasi.com [ http://cgmasi.com ] along with a PDF version of the 2017 report, which was published in May of 2018 and based on a similar survey conducted in late 2017. Reports dating back to the first survey done in late 2013 are available from the Federal Reserve Board’s website linked to above.

Why Target Average Inflation?

Federal Reserve Seal
The FOMC attempts to control economic expansion by managing interest rates. Shutterstock.com

8 May 2019 – There’s been a bit of noise in financial-media circles this week (as of this writing, but it’ll be last week when you get to read it) about Federal Reserve Chairman Jerome Powell’s talking up shifting the Fed’s focus to targeting something called “average inflation” and using words like “transient” and “symmetric” to describe this thinking. James Macintosh provided a nice layman-centric description of the pros and cons of this concept in his “Streetwise” column in Friday’s (5/3) The Wall Street Journal. (Sorry, folks, but this article is only available to WSJ subscribers, so the link above leads to a teaser that asks you to either sign in as a current subscriber or to become a new subscriber. And, you thought information was supposed to be distributed for free? Think again!)

I’m not going to rehash what Macintosh wrote, but attempt to show why this change makes sense. In fact, it’s not really a change at all, but an acknowledgement of what’s really been going on all the time.

We start with pointing out that what the Federal Reserve System is mandated to do is to control the U.S. economy. The operant word here is “control.” That means that to understand what the Fed does (and what it should do) requires a basic understanding of control theory.

Basic Control Theory

We’ll start with a thermostat.

A lot of people (I hesitate to say “most” because I’ve encountered so many counter examples – otherwise intelligent people who somehow don’t seem to get the point) understand how a thermostat works.

A thermostat is the poster child for basic automated control systems. It’s the “stone knives and bearskins” version of automated controls, and is the easiest for the layman to understand, so that’s where we’ll start. It’s also a good analog for what has passed for economic controls since the Fed was created in 1913.

Okay, the first thing to understand is the concept of a “set point.” That’s a “desired value” of some measurement that represents the thing you want to control. In the case of the thermostat, the measurement is room temperature (as read out from a thermometer) and the thing you’re trying to control is how comfortable the room air feels to you. In the case of the Fed, the thing you want to control is overall economic performance and the measurement folks decided was most useful is the inflation rate.

Currently, the set point for inflation is 2% per annum.

In the case of the thermostat in our condo, my wife and I have settled on 75º F. That’s a choice we’ve made based on the climate where we live (Southwestern Florida), our ages, and what we, through experience, have found to be most comfortable for us right now. When we lived in New England, we chose a different set point. Similarly, when we lived in Northern Arizona it was different as well.

The bottom line is: the set point is a matter of choice based on a whole raft of factors that we think are important to us and it varies from time to time.

The same goes for the Fed’s inflation set point. It’s a choice Fed governors make based on a whole raft of considerations that they think are important to the country right now. One of the reasons they meet every month is to review that target ‘cause they know that things change. What seems like a good idea in July, might not look so good in August.

Now, it’s important to recognize that the set point is a target. Like any target, you’re trying to hit it, but you don’t really expect to hit it exactly. You really expect that the value you get for your performance measurement will differ from your set point by some amount – by some error or what metrologists prefer to call “deviation.” We prefer deviation to the word error because it has less pejorative connotations. It’s a fact of life, not a bad thing.

When we add in the concept of time, we also introduce the concept of feedback. That is what control theorists call it when you take the results of your measurement and feed it back to your decision of what to do next.

What you do next to control whatever you’re trying to control depends, first, on the sign (positive or negative) of the deviation, and, in more sophisticated controls, it’s value or magnitude. In the case of the thermostat, if the deviation is positive (meaning the room is hotter than you want) you want to do something to cool it down. In the case of the economy, if inflation is too high you want to do something to reduce economic activity so you don’t get an economic bubble that’ll soon burst.

What confuses some presidents is the idea that rising economic activity isn’t always good. Presidents like boom times ‘cause they make people feel good – like a sugar high. Populist presidents typically fail to recognize (or care about the fact) that booms are invariably bubbles that burst disastrously. Just ask the people of Venezuela who watched their economy’s inflation rate suddenly shoot up to about a million(!) percent per annum.

Booms turn to busts in a heartbeat!

This is where we want to abandon the analogy with a thermostat and get a little more sophisticated.

A thermostat is a blunt instrument. What the thermostat automatically does next is like using a club. At best, a thermostat has two clubs to choose from: it can either fire up the furnace (to raise the room temperature in the event of a negative deviation) or kick in the air conditioner (in the event that the deviation is positive – too hot). That’s known as a binary digital control. It’s gives you a digital choice: up or down.

We leave the thermostat analogy because the Fed’s main tool for controlling the economy (the Fed-funds interest rate) is a lot more sophisticated. It’s what mathematicians call analog. That is, instead of providing a binary choice (to use the club or not), it lets you choose how much pressure you want to apply up or down.

Quantitative easing similarly provides analog control, so what I’m going to say below also applies to it.

Okay, the Fed’s control lever (Fed funds interest rate) is more like a brake pedal than a club. In a car, the harder you press the brake pedal, the more pressure you apply to make the car slow down. A little pressure makes the car slow down a little. A lot of pressure makes the car slow down a lot.

So, you can see why authoritarians like low interest rates. Autthoritarians generally have high-D personalities. As Personality Insights says: “They tend to know 2 speeds in life – zero and full throttle… mostly full throttle.”

They generally don’t have much use for brakes!

By the way, the thing governments have that corresponds to a gas pedal is deficit spending, but the correspondence isn’t exact and the Fed can’t control it, anyway. Since this article is about the Fed, we aren’t going to talk about it now.

When inflation’s moving too fast (above the set point) by a little, the Fed governors – being the feedback controller – decide to raise the Fed funds rate, which is analogous to pushing the brake pedal, by a little. If that doesn’t work, they push it a little harder. If inflation seems to be out of control, as it did in the 1970s, they push it as hard as they can, boosting interest rates way up and pulling way back on the economy.

Populist dictators, who generally don’t know what they’re doing, try to prevent their central banks (you can’t have an economy without having a central bank, even if you don’t know you have it) from raising interest rates soon enough or high enough to get inflation under control, which is why populist dictatorships generally end up with hyperinflation leading to economic collapse.

Populist Dictators Need Not Apply

This is why we don’t want the U.S. Federal Reserve Bank under political control. Politicians are not elected for their economic savvy, so we want Fed governors, who are supposed to have economic savvy, to make smart decisions based on their understanding of economic causes and effects, rather than dumb decisions based on political expediency.

Economists are mathematically sophisticated people. They may (or may not) be steeped in the theory of automated control systems, but they’re quite capable of understanding these basics and how they apply to controlling an economy.

Economics, of course, has been around as long as civilization. Hesiod (ca. 750 BCE) is sometimes considered “the first economist.” Contemporary economics traces back to the eighteenth century with Adam Smith. Control theory, on the other hand, has only been elucidated since the early 1950s. So, you don’t really need control theory to understand economics. It just makes it easier to see how the controls work.

To a veteran test and measurement maven like myself, the idea of thinking in terms of average inflation, instead of the observed inflation at some point in time – like right now – makes perfect sense. We know that every time you make a measurement of anything, you’re almost guaranteed to get a different value than you got the last time you measured it. That’s why we (scientists and engineers) always measure whatever we care about multiple times and pay attention to the average of the measurements instead of each measurement individually.

So, Fed governors starting to pay attention to average inflation strikes us as a duh! What else would you look at?

Similarly, using words like “transient” and “symmetric” make perfect sense because “transient” expresses the idea that things change faster than you can measure them and “symmetric” expresses the idea that measurement variations can be positive or negative – symmetric each side of the average.

These ideas all come from the mathematics of statistics. You’ve heard of “statistical significance” associated with polling data, or two polling results being within “statistical error.” The variations I’m talking about are the same thing. Variations between two values (like the average inflation and the target inflation) are statistically significant if they’re sufficiently outside the statistical error.

I’m not going to go into how you calculate a value for statistical error because it takes hours of yammering to teach it in statistics classes, and I just don’t have the space here. You wouldn’t want to read it right now, anyway. Suffice it to say that it’s a well-defined concept relating to how much variation you can expect in a given data set.

While the control theory I’ve been talking about applies especially to automated control systems, it applies equally to Federal Reserve System control of economic performance – if you put the Federal Open Market Committee (FOMC) in place of the control computer that makes decisions for the automated control system.

So,” you ask, “why not put the Fed-funds rate under computer control?”.

The reason it would be unreasonable to fully automate the Fed’s actions is that we can’t duplicate the thinking process of the Fed governors in a computer program. The state of the art of economic models is just not good enough, yet. We still need the gut feelings of seasoned economists to make enough sense out of what goes on in the economy to figure out what to do next.

That, by the way, is why we don’t leave the decisions up to some hyperintelligent pandimensional being (named Trump). We need a panel of economists with diverse backgrounds and experiences – the FOMC – to have some hope of getting it right!

Luddites’ Lament

Luddites attack
An owner of a factory defending his workshop against Luddites intent on destroying his mechanized looms between 1811-1816. Everett Historical/Shutterstock

27 March 2019 – A reader of last week’s column, in which I reported recent opinions voiced by a few automation experts at February’s Conference on the Future of Work held at at Stanford University, informed me of a chapter from Henry Hazlitt’s 1988 book Economics in One Lesson that Australian computer scientist Steven Shaw uploaded to his blog.

I’m not going to get into the tangled web of potential copyright infringement that Shaw’s posting of Hazlitt’s entire text opens up, I’ve just linked to the most convenient-to-read posting of that particular chapter. If you follow the link and want to buy the book, I’ve given you the appropriate link as well.

The chapter is of immense value apropos the question of whether automation generally reduces the need for human labor, or creates more opportunities for humans to gain useful employment. Specifically, it looks at the results of a number of historic events where Luddites excoriated technology developers for taking away jobs from humans only to have subsequent developments prove them spectacularly wrong.

Hazlitt’s classic book is, not surprisingly for a classic, well documented, authoritative, and extremely readable. I’m not going to pretend to provide an alternative here, but to summarize some of the chapter’s examples in the hope that you’ll be intrigued enough to seek out the original.

Luddism

Before getting on to the examples, let’s start by looking at the history of Luddism. It’s not a new story, really. It probably dates back to just after cave guys first thought of specialization of labor.

That is, sometime in the prehistoric past, some blokes were found to be especially good at doing some things, and the rest of the tribe came up with the idea of letting, say, the best potters make pots for the whole tribe, and everyone else rewarding them for a job well done by, say, giving them choice caribou parts for dinner.

Eventually, they had the best flint knappers make the arrowheads, the best fletchers put the arrowheads on the arrows, the best bowmakers make the bows, and so on. Division of labor into different jobs turned out to be so spectacularly successful that very few of us rugged individualists, who pretend to do everything for ourselves, are few and far between (and are largely kidding ourselves, anyway).

Since then, anyone who comes up with a great way to do anything more efficiently runs the risk of having the folks who spent years learning to do it the old way land on him (or her) like a ton of bricks.

It’s generally a lot easier to throw rocks to drive the innovator away than to adapt to the innovation.

Luddites in the early nineteenth century were organized bands of workers who violently resisted mechanization of factories during the late Industrial Revolution. Named for an imaginary character, Ned Ludd, who was supposedly an apprentice who smashed two stocking frames in 1779 and whose name had become emblematic of machine destroyers. The term “Luddite” has come to mean anyone fanatically opposed to deploying advanced technology.

Of course, like religious fundamentalists, they have to pick a point in time to separate “good” technology from the “bad.” Unlike religious fanatics, who generally pick publication of a certain text to be the dividing line, Luddites divide between the technology of their immediate past (with which they are familiar) and anything new or unfamiliar. Thus, it’s a continually moving target.

In either case, the dividing line is fundamentally arbitrary, so the emotion of their response is irrational. Irrationality typically carries a warranty of being entirely contrary to facts.

What Happens Next

Hazlitt points out, “The belief that machines cause unemployment, when held with any logical consistency, leads to preposterous conclusions.” He points out that on the second page of the first chapter of Adam Smith’s seminal book Wealth of Nations, Smith tells us that a workman unacquainted with the use of machinery employed in sewing-pin-making “could scarce make one pin a day, and certainly could not make twenty,” but with the use of the machinery he can make 4,800 pins a day. So, zero-sum game theory would indicate an immediate 99.98 percent unemployment rate in the pin-making industry of 1776.

Did that happen? No, because economics is not a zero-sum game. Sewing pins went from dear to cheap. Since they were now cheap, folks prized them less and discarded them more (when was the last time you bothered to straighten a bent pin?), and more folks could afford to buy them in the first place. That led to an increase in sewing-pin sales as well as sales of things like sewing-patterns and bulk fine fabric sold to amateur sewers, and more employment, not less.

Similar results obtained in the stocking industry when new stocking frames (the original having been invented William Lee in 1589, but denied a patent by Elizabeth I who feared its effects on employment in hand-knitting industries) were protested by Luddites as fast as they could be introduced. Before the end of the nineteenth century the stocking industry was employing at least a hundred men for every man it employed at the beginning of the century.

Another example Hazlitt presents from the Industrial Revolution happened in the cotton-spinning industry. He says: “Arkwright invented his cotton-spinning machinery in 1760. At that time it was estimated that there were in England 5,200 spinners using spinning wheels, and 2,700 weavers—in all, 7,900 persons engaged in the production of cotton textiles. The introduction of Arkwright’s invention was opposed on the ground that it threatened the livelihood of the workers, and the opposition had to be put down by force. Yet in 1787—twenty-seven years after the invention appeared—a parliamentary inquiry showed that the number of persons actually engaged in the spinning and weaving of cotton had risen from 7,900 to 320,000, an increase of 4,400 percent.”

As these examples indicate, improvements in manufacturing efficiency generally lead to reductions in manufacturing cost, which, when passed along to customers, reduces prices with concommitent increases in unit sales. This is the price elasticity of demand curve from Microeconomics 101. It is the reason economics is decidedly not a zero-sum game.

If we accept economics as not a zero-sum game, predicting what happens when automation makes it possible to produce more stuff with fewer workers becomes a chancy proposition. For example, many economists today blame flat productivity (the amount of stuff produced divided by the number of workers needed to produce it) for lack of wage gains in the face of low unemployment. If that is true, then anything that would help raise productivity (such as automation) should be welcome.

Long experience has taught us that economics is a positive-sum game. In the face of technological advancement, it behooves us to expect positive outcomes while taking measures to ensure that the concomitant economic gains get distributed fairly (whatever that means) throughout society. That is the take-home lesson from the social dislocations that accompanied the technological advancements of the Early Industrial Revolution.

Don’t Panic!

Panic button
Do not push the red button! Peter Hermes Furian/Shutterstock

20 March 2019 – The image at right visualizes something described in Douglas Adams’ Hitchiker’s Guide to the Galaxy. At one point, the main characters of that six-part “trilogy” found a big red button on the dashboard of a spaceship they were trying to steal that was marked “DO NOT PRESS THIS BUTTON!” Naturally, they pressed the button, and a new label popped up that said “DO NOT PRESS THIS BUTTON AGAIN!”

Eventually, they got the autopilot engaged only to find it was a stunt ship programmed to crash headlong into the nearest Sun as part of the light show for an interstellar rock band. The moral of this story is “Never push buttons marked ‘DO NOT PUSH THIS BUTTON.’”

Per the author: “It is said that despite its many glaring (and occasionally fatal) inaccuracies, the Hitchhiker’s Guide to the Galaxy itself has outsold the Encyclopedia Galactica because it is slightly cheaper, and because it has the words ‘DON’T PANIC’ in large, friendly letters on the cover.”

Despite these references to the Hitchhiker’s Guide to the Galaxy, this posting has nothing to do with that book, the series, or the guide it describes, except that I’ve borrowed the words from the Guide’s cover as a title. I did that because those words perfectly express the take-home lesson of Bill Snyder’s 11 March 2019 article in The Robot Report entitled “Fears of job-stealing robots are misplaced, say experts.”

Expert Opinions

Snyder’s article reports opinions expressed at the the Conference on the Future of Work at Stanford University last month. It’s a topic I’ve shot my word processor off about on numerous occasions in this space, so I thought it would be appropriate to report others’ views as well. First, I’ll present material from Snyder’s article, then I’ll wrap up with my take on the subject.

“Robots aren’t coming for your job,” Snyder says, “but it’s easy to make misleading assumptions about the kinds of jobs that are in danger of becoming obsolete.”

“Most jobs are more complex than [many people] realize,” said Hal Varian, Google’s chief economist.

David Autor, professor of economics at the Massachusetts Institute of Technology points out that education is a big determinant of how developing trends affect workers: “It’s a great time to be young and educated, but there’s no clear land of opportunity for adults who haven’t been to college.”

“When predicting future labor market outcomes, it is important to consider both sides of the supply-and-demand equation,” said Varian, “demographic trends that point to a substantial decrease in the supply of labor are potentially larger in magnitude.”

His research indicates that shrinkage of the labor supply due to demographic trends is 53% greater than shrinkage of demand for labor due to automation. That means, while relatively fewer jobs are available, there are a lot fewer workers available to do them. The result is the prospect of a continued labor shortage.

At the same time, Snyder reports that “[The] most popular discussion around technology focuses on factors that decrease demand for labor by replacing workers with machines.”

In other words, fears that robots will displace humans for existing jobs miss the point. Robots, instead, are taking over jobs for which there aren’t enough humans to do them.

Another effect is the fact that what people think of as “jobs” are actually made up of many “tasks,” and it’s tasks that get automated, not entire jobs. Some tasks are amenable to automation while others aren’t.

“Consider the job of a gardener,” Snyder suggests as an example. “Gardeners have to mow and water a lawn, prune rose bushes, rake leaves, eradicate pests, and perform a variety of other chores.”

Some of these tasks, like mowing and watering, can easily be automated. Pruning rose bushes, not so much!

Snyder points to news reports of a hotel in Nagasaki, Japan being forced to “fire” robot receptionists and room attendants that proved to be incompetent.

There’s a scene in the 1997 film The Fifth Element where a supporting character tries to converse with a robot bartender about another character. He says: “She’s so vulnerable – so human. Do you you know what I mean?” The robot shakes its head, “No.”

Sometimes people, even misanthropes, would prefer to interact with another human than with a drink-dispensing machine.

“Jobs,” Varian points out, “unlike repetitive tasks, tend not to disappear. In 1950, the U.S. Census Bureau listed 250 separate jobs. Since then, the only one to be completely eliminated is that of elevator operator.”

“Excessive automation at Tesla was a mistake,” founder Elon Musk mea culpa-ed last year “Humans are underrated.”

Another trend Snyder points out is that automation-ready jobs, such as assembly-line factory workers, have already largely disappeared from America. “The 10 most common occupations in the U.S.,” he says, “include such jobs as retail salespersons, nurses, waiters, and other service-focused work. Notably, traditional occupations, such as factory and other blue-collar work, no longer even make the list.

Again, robots are mainly taking over tasks that humans are not available to do.

The final trend that Snyder presents, is the stark fact that birthrates in developed nations are declining – in some cases precipitously. “The aging of the baby boom generation creates demand for service jobs,” Varian points out, “but leaves fewer workers actively contributing labor to the economy.”

Those “service jobs” are just the ones that require a human touch, so they’re much harder to automate successfully.

My Inexpert Opinion

I’ve been trying, not entirely successfully, to figure out what role robots will actually have vis-a-vis humans in the future. I think there will be a few macroscopic trends. And, the macroscopic trends should be the easiest to spot ‘cause they’re, well, macroscopic. That means bigger. So, there easier to see. See?

As early as 2010, I worked out one important difference between robots and humans that I expounded in my novel Vengeance is Mine! Specifically, humans have a wider view of the Universe and have more of an emotional stake in it.

“For example,” I had one of my main characters pontificate at a cocktail party, “that tall blonde over there is an archaeologist. She uses ROVs – remotely operated vehicles – to map underwater shipwreck sites. So, she cares about what she sees and finds. We program the ROVs with sophisticated navigational software that allows her to concentrate on what she’s looking at, rather than the details of piloting the vehicle, but she’s in constant communication with it because she cares what it does. It doesn’t.”

More recently, I got a clearer image of this relationship and it’s so obvious that we tend to overlook it. I certainly missed it for decades.

It hit me like a brick when I saw a video of an autonomous robot marine-trash collector. This device is a small autonomous surface vessel with a big “mouth” that glides around seeking out and gobbling up discarded water bottles, plastic bags, bits of styrofoam, and other unwanted jetsam clogging up waterways.

The first question that popped into my mind was “who’s going to own the thing?” I mean, somebody has to want it, then buy it, then put it to work. I’m sure it could be made to automatically regurgitate the junk it collects into trash bags that it drops off at some collection point, but some human or humans have to make sure the trash bags get collected and disposed of. Somebody has to ensure that the robot has a charging system to keep its batteries recharged. Somebody has to fix it when parts wear out, and somebody has to take responsibility if it becomes a navigation hazard. Should that happen, the Coast Guard is going to want to scoop it up and hand its bedraggled carcass to some human owner along with a citation.

So, on a very important level, the biggest thing robots need from humans is ownership. Humans own robots, not the other way around. Without a human owner, an orphan robot is a pile of junk left by the side of the road!

Reimagining Our Tomorrows

Cover Image
Utopia with a twist.

19 December 2018 – I generally don’t buy into utopias.

Utopias are intended as descriptions of a paradise. They’re supposed to be a paradise for everybody, and they’re supposed to be filled with happy people committed to living in their city (utopias are invariably built around descriptions of cities), which they imagine to be the best of all possible cities located in the best of all possible worlds.

Unfortunately, however, utopia stories are written by individual authors, and they’d only be a paradise for that particular author. If the author is persuasive enough, the story will win over a following of disciples, who will praise it to high Heaven. Once in a great while (actually surprisingly often) those disciples become so enamored of the description that they’ll drop everything and actually attempt to build a city to match the description.

When that happens, it invariably ends in tears.

That’s because, while utopian stories invariably describe city plans that would be paradise to their authors, great swaths of the population would find living in them to be horrific.

Even Thomas More, the sixteenth century philosopher, politician and generally overall smart guy who’s credited with giving us the word “utopia” in the first place, was wise enough to acknowledge that the utopia he described in his most famous work, Utopia, wouldn’t be such a fun place for the slaves he had serving his upper-middle class citizens, who were the bulwark of his utopian society.

Even Plato’s Republic, which gave us the conundrum summarized in Juvenal’s Satires as “Who guards the guards?,” was never meant as a workable society. Plato’s work, in general, was meant to teach us how to think, not what to think.

What to think is a highly malleable commodity that varies from person to person, society to society, and, most importantly, from time to time. Plato’s Republic reflected what might have passed as good ideas for city planning in 380 BC Athens, but they wouldn’t have passed muster in More’s sixteenth-century England. Still less would they be appropriate in twenty-first-century democracies.

So, I approached Joe Tankersley’s Reimagining Our Tomorrows with some trepidation. I wouldn’t have put in the effort to read the thing if it wasn’t for the subtitle: “Making Sure Your Future Doesn’t SUCK.”

That subtitle indicated that Tankersley just might have a sense of humor, and enough gumption to put that sense of humor into his contribution to Futurism.

Futurism tends to be the work of self-important intellectuals out to make a buck by feeding their audience on fantasies that sound profound, but bear no relation to any actual or even possible future. Its greatest value is in stimulating profits for publishers of magazines and books about Futurism. Otherwise, they’re not worth the trees killed to make the paper they’re printed on.

Trees, after all and as a group, make a huge contribution to all facets of human life. Like, for instance, breathing. Breathing is of incalculable value to humans. Trees make an immense contribution to breathing by absorbing carbon dioxide and pumping out vast quantities of oxygen, which humans like to breathe.

We like trees!

Futurists, not so much.

Tankersley’s little (168 pages, not counting author bio, front matter and introduction) opus is not like typical Futurist literature, however. Well, it would be like that if it weren’t more like the Republic in that it’s avowed purpose is to stimulate its readers to think about the future themselves. In the introduction that I purposely left out of the page count he says:

I want to help you reimagine our tomorrows; to show you that we are living in a time when the possibility of creating a better future has never been greater.”

Tankersley structured the body of his book in ten chapters, each telling a separate story about an imagined future centered around a possible solution to an issue relevant today. Following each chapter is an “apology” by a fictional future character named Archibald T. Patterson III.

Archie is what a hundred years ago would have been called a “Captain of Industry.” Today, we’d refer to him as an uber-rich and successful entrepreneur. Think Elon Musk or Bill Gates.

Actually, I think he’s more like Warren Buffet in that he’s reasonably introspective and honest with himself. Archie sees where society has come from, how it got to the future it got to, and what he and his cohorts did wrong. While he’s super-rich and privileged, the futures the stories describe were made by other people who weren’t uber-rich and successful. His efforts largely came to naught.

The point Tankersley seems to be making is that progress comes from the efforts of ordinary individuals who, in true British fashion, “muddle through.” They see a challenge and apply their talents and resources to making a solution. The solution is invariably nothing anyone would foresee, and is nothing like what anyone else would come up with to meet the same challenge. Each is a unique response to a unique challenge by unique individuals.

It might seem naive, this idea that human development comes from ordinary individuals coming up with ordinary solutions to ordinary problems all banded together into something called “progress,” but it’s not.

For example, Mark Zuckerberg developed Facebook as a response to the challenge of applying then-new computer-network technology to the age-old quest by late adolescents to form their own little communities by communicating among themselves. It’s only fortuitous that he happened on the right combination of time (the dawn of a radical new technology), place (in the midst of a huge cadre of the right people well versed in using that radical new technology) and marketing to get the word out to those right people wanting to use that radical new technology for that purpose. Take away any of those elements and there’d be no Facebook!

What if Zuckerberg hadn’t invented Facebook? In that event, somebody else (Reid Hoffman) would have come up with a similar solution (Linkedin) to the same challenge facing a similar group (technology professionals).

Oh, my! They did!

History abounds with similar examples. There’s hardly any advancement in human culture that doesn’t fit this model.

The good news is that Tankersley’s vision for how we can re-imagine our tomorrows is right on the money.

The bad news is … there isn’t any bad news!