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ChatGPT on Hypernomics

ChatGPT is scary good. We are not far from dangerously strong AI
Elon Musk, X, 12/3/2022

A Google search is good, but a pointed question to ChatGPT is better. I asked it, “Why should a company or government agency use Hypernomics?” and it wrote:

Hypernomics, a powerful analytical approach leveraging hyperdimensional economics, offers companies and government agencies a transformative way to understand complex, multi-dimensional data. Here’s why they might choose to adopt Hypernomics:

ENHANCED DECISION-MAKING: Hypernomics helps organizations visualize and analyze data across numerous variables simultaneously, enabling a more nuanced understanding of factors affecting outcomes. This multi-dimensional insight supports more informed, strategic decisions, particularly when traditional two-dimensional analysis falls short.

IDENTIFYING MARKET OPPORTUNITIES: By analyzing consumer behavior, demographics, pricing, and product features, Hypernomics can uncover lucrative market gaps that would otherwise remain hidden, leading to more targeted products, services, and policies.

RISK MANAGEMENT & FORECASTING: With Hypernomics, organizations can better forecast potential risks and outcomes by understanding the interplay between various factors. This approach aids in scenario planning, helping agencies and companies anticipate and prepare for future scenarios.

RESOURCE OPTIMIZATION: Hypernomics can help governments allocate resources more effectively, for example, by optimizing infrastructure investment based on factors like population growth, economic activity, and regional needs. Companies can similarly use it to streamline operations, optimize supply chains, or refine pricing strategies.

COMPLEX PROBLEM-SOLVING: Complex issues, like climate change impacts or multi-market competition, require the analysis of many variables. Hypernomics enables organizations to solve such challenges more effectively, revealing connections and insights that other methods may overlook.

COMPETITIVE ADVANTAGE: For businesses, the ability of Hypernomics to analyze vast, interconnected datasets can provide a significant edge, offering insights that competitors may lack. Government agencies benefit by understanding societal needs comprehensively, improving public service delivery and policy impact.

The math behind Hypernomics, while complex, is essential to its application in real-world decision-making and enables organizations to envision relationships and dependencies that would otherwise go unnoticed, paving the way for a more profound and actionable understanding of their data. That math enables Hypernomics to deliver insights that are both broad in scope and granular in detail.

Hypernomics provides a framework to navigate and leverage multi-dimensional data, allowing companies and government agencies to move beyond traditional methods for a more comprehensive, insightful, and strategic approach to decision-making.

#chatgpt #hypernomics

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Stop Lying to Students

If you are out to describe the truth, leave elegance to the tailor. (On being reproached that his gravitation formula was longer and more cumbersome than Newton’s.)
Albert Einstein

So, I’ve combed through all the big sellers used as economics textbooks and discovered that they all agree that we should portray Demand the way they show it in Figure A. It has remained unchanged since Alfred Marshall wrote Principles of Economics in 1890.

The jury is in. The verdict read. Everyone agrees! It’s so simple! So self-evident! So elegant!

And yet, so wrong.

You’d think a world deep in the middle of its Information Age would want its Demand Curves to be informed with data. Figure (A) is not so drawn. If it were only the case that the convention in (A) was a harmless yet broadly accepted lie, I might be inclined to let it go.

But it isn’t. Students are being led astray. Markets aren’t that straightforward.

To analyze them, you need to do more work.

Figure (B) shows what happens when we do that work. Here, we examine the leading currencies of the day and make several mathematically informed discoveries about currency Demand. There is not a simple single line describing it. In (B), we see four different curves at play. There are others still, but we won’t entertain them now.

The Upper Demand Frontier was formed by the currencies of three Gulf states, plus the Euro, the British Pound, and the United States Dollar. This boundary describes the Price-Limited market boundary.

THE OUTER DEMAND FRONTIER reveals the market’s saturation limits. Adding more units to a given currency tends to depress its Value (sustainable price in United States Dollar equivalents) along this curve.

THE INNER DEMAND FRONTIER exposes the minimum viable quantities of currencies given their prices. In essence, the world says that if you issue a currency, you are guaranteed at least its Value along this line.

THE JAPANESE YEN DEMAND CURVE (yes, there is one for every country shown; we’re only looking at this one for an example) shows how the price of that country’s currency should rise or fall as the number of units enters or disappears from the market. We obtain the slope of that curve when we solve for the Value of all currencies, which is a function of each country’s

1) Prime rate,
2) Foreign Exchange Reserves, and
3) Currency volume.

Yes, this method is “longer and more cumbersome” than the simple line it replaces. Relativity is more complex than Newtonian mechanics. But, without relativity, you don’t get a Global Positioning System (GPS). And who wants to navigate without that?

Navigating markets takes hard work that others don’t yet imagine they have to do. But market math reveals its truths once we make that effort.

We need students to understand the real world of markets, not some oversimplified paradigm that leaves them partially informed yet confident they know how they work.

#hypernomics #markets #marketanalysis

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The Semmelweiss Reflex – Rejecting New Evidence Opposing Established Norms

The new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.
Max Planck

Kurt Vonnegut called him “my hero.” His birth house is now a museum named for him. Many wrote about him, and last year, over 150 years after he died, there was a play about him in London. But Dr. Ignaz Semmelweiss did not enjoy this popularity when alive.

After earning his medical degree, Vienna General Hospital appointed him to their First Obstetrical Clinic in 1846. Made of 2 units, the 1st clinic, run by midwives, had a much lower mortality rate than the 2nd, operated by doctors. After much research, he suspected that doctors going from their cadaver lab directly to the maternity ward might have led to the transfer of “cadaverous particles” to maternity ward patients, as midwives in the 2nd clinic had no such contact with corpses. He suggested that doctors wash their hands. When they initiated that procedure in the first clinic, its mortality rates plummeted.

However, colleagues broadly mocked his hypothesis that only hygiene mattered. At the time, his theories lacked scientific explanation. That became possible after his death when Louis Pasteur and others developed the germ theory of disease.

Outraged by the apathy of his colleagues, he became dejected and drank heavily. He was committed to an insane asylum where guards beat him until his hand got gangrene, which quickly killed him.

The rejection of his observations was so severe that it came to be named the Semmelweiss Reflex, the affinity of people to cling to discredited beliefs.

I know something about that. I’ve taken my book to some big-name graduate schools. They won’t say it’s wrong. They just won’t read it. Thus, I’ve seen my paradigm-shifting observations undisputed but largely ignored. That reaction persists despite my undeniable mathematical evidence proving those previously held theorems false and incomplete.

At the lower left below, here’s an example homework problem for a current economics class that wants students to explain a “change in market equilibrium.”

Note the complete lack of data. Everything in the diagram is imaginary. Where is the information about the cars? Nonexistent. Oops.

Markets form with actual data, as shown in the lower right diagram. There, 18 electric car models for sale had points in Value Space (green spheres) describing their 1) Range, 2) Horsepower, and 3) Price, with matching points (red spheres) on the Demand Plane depicting their 3) Prices and 4) Quantities sold. There is no “equilibrium point,” as models enjoy “sustainable disequilibria” when prices exceed costs.

Unlike Dr. S, the rejection won’t drive me mad. But I am curious about the apathy.

And I wonder, as Semmelweiss did, who will wash their hands first?

#semmelweiss #hypernomics

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Position to Win by Finding Open Market Spaces

Hit ‘em where they ain’t.
Wee Willie Keeler

You may not have heard of Wee Willie Keeler, but he changed baseball.

With over 63 at-bats between each strikeout over his career, he could bunt any ball pitched to him. Because of him, baseball stopped allowing unlimited bunt fowls and made one with two strikes a strikeout. He hit .300 16 times and .400 once. His record of 206 singles in a season stood for over 100 years. When Joe DiMaggio set his 56-game National League hitting streak, he broke Keeler’s 45-game record. He used one of the largest bats in the league, weighing up to 46 ounces.

And he did it all despite his diminutive size of 5’ 4 1/2” and weighing just 140 pounds.

His famous adage of “hit ‘em where they ain’t” applies not only to batting but also to marketing new products. It makes little sense to try to copy a competitor and offer a virtually identical product for a lower price when one can offer the market a new item that it wants, doesn’t have, and can afford.

To do that, we’ll need to describe our markets thoroughly.

In the case below, we’ll start with a fully assembled dataset describing the USG purchases of air-to-surface glide bombs (brown) and missiles (blue) over the 20 years beginning in 1997 and ending in 2016.

Imagine we are trying to sell a new missile. What can we give the market that it doesn’t already have?

In (A), we plot the range of the missiles in the set on the horizontal axis and their prices on the vertical axis. Instantly, we discover a critical fact: a substantial gap in missile prices. The USG has purchased cheaper and more expensive devices; it stands to reason that they might buy a new missile within this space with the appropriate features. In the same plot, we see that a similar opening exists relative to the range of these devices.

Figure (B) offers the same kind of insight that (A) does while looking at a different independent variable, launch mass. While the price gap in (B) is the same as in (A), in this view, we discover a sizable gap in the market’s launch masses. By interpolation, given that it performs well, a new product with mass in this gap will likely find a market.

(C) finds that the market for Air-to-Surface missiles has Upper and Inner Demand Frontiers. If we wanted to build, say, a missile that could sell as many as 28K units for an average price of $300K over 20 years, we find (once we do regression analysis considering 1) mass, 2) speed, 3) range, and 4) quantities sold, and set the Values for those first three independent variables, not shown here) this market has a Product Demand Curve that forms for each item. With a slope of -0.208, it is analogous to an 86.6% learning curve.

Thus, if a supplier can demonstrate a steeper learning curve than that throughout the program, they have the potential to meet their 28K unit limit goal at $300K along the Upper Demand Frontier.

#hypernomics #pricetowin #gapanalysis

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Solving the 1st Half of the Problem to Get to the 2nd

A problem well stated is a problem half-solved.
Charles F. Kettering

A few months ago, I wrote about the ill-fated AGM-183A hypersonic missile. While its engineering parameters were well-known, its budget limitations were not. Funded to about $1.7B for its development, Lockheed Martin said its first unit cost would be about $42M. At the same time, the Congressional Budget Office thought the USG would be able to afford 100 of them at their eventual per-unit price of $15M to $18M. As a variation of the chart below revealed (C), the chance of that happening was significantly less than one in one million quadrillion, as that price put it at 108 Standard Deviations past the market’s Upper Demand Frontier. Eventually, budget realism entered the picture, and the United States Air Force stopped funding the program. In the process, it validated their Demand Frontier.

For all the work we spend extending the boundaries of engineering, we must understand that trying to exceed a well-defined Demand Frontier by leaps and bounds never works.

To know what we can do, we must first know what we can’t. That’s part of the 1st half of the problem. The AGM-183A didn’t get past that.

LM did quite a bit better with its stealthy AGM-158B, also known as the JASSM-ER, in (A) below. At the time of the study, it was the most expensive air-to-surface missile in the industry. In the 20 years shown in (C) (1997-2016), LM sold 275 units at an inflation-adjusted 2024 price of $2.5M, with the AGM-158B helping to form the market’s Upper Demand Frontier. Note that that curve is relatively flat, with a slope of -0.533. That meant the USG spent more money on the market’s lower-priced part than its upper bit.

A recent headline noted that Russia knocked down over 150 Ukrainian drones. The ineffectiveness indicates the need for missiles to be invisible to the enemy. Getting smaller and stealthier will help.

Enter the prospect of much smaller, less expensive, and (presumably stealthy) cruise missiles, the air-to-surface (specifically, anti-ship) ordnance proposed by American defense startup Ares Industries shown in (B). Designed to attack smaller vessels, the company has set a target price of $300K per missile. Of course, whether or not they pull this off remains to be seen, but the attempt is admirable, as the low price enables the purchase of up to tens of thousands of units over two decades (C). It would add flexibility in the inventory, letting operators swap expensive devices for cheaper ones when smaller packages can do the job.

In (C), since Glide Bombs cost a fraction (about 1/8 for the same payload*velocity and range) of missiles, planners can afford to buy more of these devices than powered missiles. One could imagine a future in which stealthy glide bombs dropped from unmanned drones would lower operational costs and pilot risk while increasing mission success rates.

Russian Sub
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Uphill to Stupid: Universality Abounds

All schools and colleges have two great functions: to confer and conceal valuable knowledge.
Mark Twain

Some writers have gained more attention than their ideas merit. It takes little thought to discard them.

Take Karl Marx and his school of thought, for example. In his Communist Manifesto, he wrote, ” Modern bourgeois society… is like the sorcerer who is no longer able to control the powers of the nether world.” Later, in his Capital: A Critique of Political Economy, Marx stated, “So far, no chemist has ever discovered exchange-value in …a diamond.” He wants you to believe that the bourgeois economy runs by magic.

Hypernomics knows better. And so do you. A diamond’s value is a function of its carats, color, clarity, and cut. Marx certainly knew of the Hope Diamond and that it was worth more than smaller stones. He was pulling the wool over readers’ eyes. There is not a lick of sorcery in diamond valuations. Thus, his view about diamonds is downhill of stupidity. He was more sinister than that. Instead, he concealed valuable knowledge. This would-be sleight of hand had implications for states that followed his lead.

In 1985, the USSR artificially constrained all salaries to 400 rubles or less per month (Alexeev, Michael V., et al., “Income Distribution in the USSR in the 1980s,” 27 Nov 1992), defying conventional (i.e., non-Marxist) economic wisdom. Doctors made little more than janitors. It made sense to the central planners. And then their economy collapsed—not despite their best efforts, but because of them.

When it comes to Valuing physical products (like a flawless, colorless, round, brilliant two-carat diamond or an Oscar II nuclear cruise missile submarine weighing nearly 15K tons with a top speed of 32 knots) instead of people, there’s no option other than Hypernomics.

In (C) below, the angled plane projects the value of Russian nuclear submarines using performance and price data from 20 and 57 ship classes in the United States and Russia, respectively. The equation used for that surface has a p-value of 9.85E-40. In (B), reflecting the same equation with its step function, the US pays about 60% more for the same tonnage and speed as comparable Russian boats, likely due to factors not considered separately in this equation (such as safety, max depth, comfort, etc.). All navies have behaved like that since they began.

With (A), the US and Russian navies abide by statistically significant but distinctly different Demand Frontiers, each with a p-value of about 0.03. Demand comes not from Marxist rants but from how all buyers purchase goods as their prices change. The slopes may change, but the central tenet does not.

When next you meet a Marxist, tell them the Eastern Bloc buys naval vessels the same way as the West. In other words, they buy like the bourgeoisie. And that is so bourgeois.

Which, despite the would-be disparaging tone, is a good thing.

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Seeing Problems from a Distance and Getting To No. 1

I have been trying to point out that in our lives chance may have an astonishing influence and, if I may offer advice to the young laboratory worker, it would be this—never neglect an extraordinary appearance or happening. It may be—usually is, in fact—a false alarm that leads to nothing but may, on the other hand, be the clue provided by fate to lead you to some important advance.
Sir Alexander Fleming

Knowledge and science are nothing but perception.
Plato

I had the great fortune of seeing The Rolling Stones in concert on Wednesday and having gone to concerts for decades, it was the best I had ever seen. The high-resolution video screen, at 55m wide and over 14m tall, was almost worth the price of admission by itself. But, of course, all eyes eventually trained themselves on Ronnie Woods, Keith Richards, and Mick Jagger. Jagger, now 80, skipped about the stage like a grade schooler, belting out one monumental hit after another with a voice seemingly untouched by age. I cannot recommend this show enough. I’d tell my friends to see them before they’re gone, but then I said the same thing the last time I saw them—in 1981.

As someone prone to figuring out how buyers work in markets, I stared into the seats numerous times. Like everyone else, We purchased our tickets online and weighed the distance and angle to center stage against the prices offered for each seat. Ticket prices ranged from about $80 to over $6400. Sitting up 14 rows above the floor in the far end zone of So-Fi, I noticed a lack of uniformity in how the seats filled up. In (A) and (B) below, I found a pair of matching seat banks on either side of the venue that never filled in like the rest of the facility. Those seats were better than ours, closer to the stage, but the added cost didn’t justify us buying a seat there. That’s the way we saw it.

Everyone else saw it the same way. They sat vacant until the show started.

Simply put, the prices for those seats put people off. They were too high.

Now, in a place with over 70,000 people for a football game, losing revenue on a few hundred seats is not a big deal to The Rolling Stones.

However, it points to a central tenet of my book, Hypernomics: Using Hidden Dimensions to Solve Unseen Problems: buyers ultimately determine prices for all products based on their features.

A few months after its release, on July 11, 2024, that book reached Number 1 on the Amazon Best Sellers list in its Macroeconomics section (C).

If you manage The Rolling Stones and know rock fans worldwide will come to their concerts, you needn’t worry about the finer points of getting your product and its price right.

But if you don’t run the Stones and want to understand how the economic world works, read my book. It doesn’t so much change the world as it reveals it.

You’ll want to read it before you leave 500 seats vacant.

#hypernomics #value #therollingstones

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Saturday Morning Quarterbacking: First-Person Shooter Games

Common sense always speaks too late. Common sense is the guy who tells you you ought to have had your brakes relined last week before you smashed a front end this week. Common sense is the Monday morning quarterback who could have won the ball game if he had been on the team. But he never is. He’s high up in the stands with a flask on his hip. Common sense is the little man in a grey suit who never makes a mistake in addition. But it’s always somebody else’s money he’s adding up.
Raymond Chandler

Lots of people can tell you what you should have done after the fact.

You should have anticipated the cornerback jumping the route. Didn’t the situation call for an extra blocker on the strongside tackle when you ran a sweep his way? Why didn’t you expect they would run a blitz when they tended to do that on every fourth down? That’s what Monday Morning Quarterbacking is.

What about Saturday Morning Quarterbacking? Wait. What? What is that? Well, that’s a series of studies one puts into place to anticipate what will happen Sunday, based on the distant past, near past, and present. And for that, we’ll need data.

As any researcher knows, when it comes to data, Mick Jagger warned us, “You can’t always get what you want, but if you try sometimes, well, you might find you get what you need.”

Sometimes, large, important pieces of a picture help to envision the whole.
In (A), I wanted to get some idea of the Demand for video games, specifically the ones of “First Person Shooter” ilk. I chose that group because it is one of the most popular video game categories, with scores of titles from which to choose. I didn’t have the time to study all of them. So, I picked 26 leading titles and made some exciting discoveries.

Most surprising to me was the Outer Demand Frontier. With a slope of -1.33, more money is at the top of this line than at the bottom. Note Call of Duty—Modern Warfare 3 (COD—MW3). It helps form that Frontier, and with $2.22B in revenue, it exceeds the revenues of all but a handful of films. Apex Legends was at the low end of that line and commanded revenues of $1.21B, and, at the same time, also helped form part of the Inner Demand Frontier, which has a very flat slope (-0.404).

Figure B shows us that in fantasy, as in reality, those who play the games must make some tradeoffs. My son showed me some of the dials one can set in these games. You can have extremely high resolution or ultra-fast frame rates, but you can’t have both. Depth of field is crucial, too, and you may want to set it to the farthest reaches possible, which we might call “X.” There, you will find that your frame rate and resolution limits are lower than if you were to set the depth of field to 0.5X.

Players in the game, either the people with the controllers or the game developers, need to see how all features work in concert.

And they need to do that on Saturday morning.

#hypernomics #markets

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Market Limits and Infinite Dimensional Compression

Genius may have its limitations, but stupidity is not thus handicapped.
Elbert Green Hubbard

The International Cost Estimating and Analysis Association (ICEAA) recently held its annual Professional Development & Training Workshop in Minneapolis, Minnesota. This event, a cornerstone of professional development for our members, was a remarkable success. I submitted a paper to it, and it won the award for best paper overall.

“Market Dimensional Expansion, Collapse, Costs, and Viability” delved into several crucial yet under-explored areas. Dimensional expansion and collapse are vital to comprehending market evolution. In it, I unveiled a groundbreaking method to compress standard 3D Cartesian Coordinate Systems into as many as 16 dimensions. Theoretically, there is no upper limit to the number of dimensions that can be depicted using these methods. Equally significant was the exploration of multiple views on Demand Frontiers.

In (D), I plotted the ten-year demand figures for 95 Western Bloc business aircraft, with the horizontal axis for their quantities and the prices on the vertical. Several crucial limitations become evident when one does that.

An Outer Demand Frontier reflects the market’s saturation threshold. Any model attempting to exceed this line will find that the market has exhausted its buyers. One can drop one’s price and gain more sales, but this line is very steep and will soon intersect any Learning Curve associated with the aircraft model that forms it. Note that none of the planes in the study vastly exceeded this limit.

The Lower Demand Frontier reveals a market’s margin limitation. There are planes priced below this line but fall into the General Aviation category. They are not for business travel due to the stricter regulations by which Business Aircraft abide.

Inner Demand Frontiers are efficiency-limited. Planes to the left of this line are either 1) reconfigured airliners (where the main airliner line keeps the learning going), 2) ramping up production, 3) winding down their line, or 4) underwritten by governments. In this case, all Textron planes are going extinct, as the company gave up building these aircraft types. The Dassault planes benefited from a large subsidy from the French government, and Piaggio got the same treatment from the Italian state.

The Upper Demand Frontier is the limit that took down the Aerion AS2, as it attempted to go far beyond it. In a different market, this made the B-2 bomber stop at 21 units rather than the 132 vehicles the USAF sought.

In sum, it pays to know where your contest’s boundaries lie. In markets, as in competitive games, there are boundaries. In business, your buyers form those boundaries. Knowing what your buyers can and can’t afford is critical to developing a product with a chance for success.

In (A), I hold a 2D Demand Plane in one hand, and a 3D Value Space in the other. The paper I gave using this concept won the awards in (B), allowing me to speak to 450 People (C). Among other things, my paper addressed markets’ Demand Frontiers (D).

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The Premature End of the B-21

What did the President know, and when did he know it?
Howard Baker, Watergate Hearings.

Last month, in a hearing before the U.S. House Armed Services Committee, Lt. Gen. Richard G. Moore Jr., Deputy Chief of Staff for Plans and Programs, U.S. Air Force, reaffirmed the USAF’s commitment to buy 100 Northrop B-21 bombers by 2039. The Gen told the Committee he needed to get “predictable funding.”

That won’t happen. The 100-unit bit, that is. We’ve got the “predictable funding” covered.

On September 26, 2018, after giving an award-winning paper at an international annual conference (iceaaonline.com), I was asked to present it again to its Southern California chapter. The venue was a Northrop Grumman facility, with several NG people in attendance.

It turns out that the funding the Gen receives for bombers, fighters, and attack aircraft is very predictable. But its limits are far lower than Gen Moore imagines. The Demand Frontier for this market has been stable for over 25 years and will limit the purchase to just over 50 units. Even if the program makes its FY 2016 target of $610M/plane, it has a slim chance (< in 1M) of making 100.

When it stops in 2039, people will point to “changing environments.”

But the target was never in reach. We knew that in 2018.

When I related that to the crowd, nobody ran out the door, telling the company to “hold the presses” on the B-21 sales prediction. Why?

How long will it take a military branch unequaled in precise targeting to realize that the time to take aim at program requirements is when the program launches, not when it falls apart decades later?

#hypernomics #b21 #innovation