Cwik Presents to Oxford (UK) Hayek Society

 On October 22, 2020, Paul F. Cwik gave a lecture to the Oxford Hayek Society.  The topic is the current state of the Macroeconomy.  Some Austrian Business Cycle theory is used to support the analysis.  The link to the lecture is here: https://www.facebook.com/BritishConservation/videos/3549109898445519/

How Does a Barber Thrive?

            Yesterday I had to cut my own hair (again--thanks COVID).  I cannot say that I did a great job, but it got me thinking about barbers.  How much has the job of a barber changed over the past several decades?[1]  I don’t think it has changed too much.  So what does a barber need?  A chair.  A cloth and a strip of paper that tucks under into the collar.  Scissors.  An electric clipper and attachments.  A comb and some blue liquid to drop the comb into.  And maybe a water squirt bottle.  Maybe.  And not much more.

            So here is my question: As the world progresses, how does the barber thrive?  I can imagine a company which comes out with a new product, expands into new markets and thrives.  I can also see a scenario where a company cuts its costs, thereby increasing its profitability and thrives.  However a barber, not a chain of barber shops, can’t really come out with new products nor expand into new markets.  And it isn’t likely that the barber is able to cut his costs year-after-year to enhance his profit margins.  So how does a barber thrive?  In other words, how does the barber increase his standard of living when he doesn’t have the same paths open to him as other businesses do?  Let’s explore some possibilities.

            If the barber raises his prices each year, would he then be able to raise his standard of living?  Let’s think that through.  First of all, it is probably true that the barber’s prices do rise, but this is most likely due to inflation.  As the money supply expands, each dollar loses some of its value.  This drop in purchasing power requires the barber to raise his prices to keep pace.  So the real question is not whether the barber can raise his prices each year, but can he raise his prices faster than inflation and make a larger profit?  To answer this question, we first have to recognize that demand curves slope downward.  That means as the price falls, people will want more; and as the price rises, people will want less.  So as the barber raises his prices faster than the rate of inflation, he will lose some business.  It comes down to which change is bigger: quantity or price.  A business’s revenue is Price × Quantity.  If the change in price (say +10%) is larger than the loss in quantity (-5%), then the revenue will increase.  Economists call this situation inelastic demand.  Whenever a company faces inelastic demand, raising prices will lead to an increase in revenue.  However, there comes a point where the demand stops being inelastic.  And so companies (even in complete absence of competition) stop raising their prices when they reach that last point of inelasticity.

            So let’s assume that our smart barber has found that point.  Now what?  He can’t raise his price any further without losing too many customers.  In fact, let’s assume that barbers found that most profitable point long ago.  Let’s say they found it some time back in the 1950s.  How can we explain that the barbers’ standard of living has improved even though they can’t raise prices faster than inflation, can’t diversify into other markets, and don’t really have any mechanisms to consistently cut costs?

            What can the barber do to raise his standard of living?  The simple answer is nothing.  There is nothing that he can do, all by himself, to raise his standard of living.  He needs the help of others.  And this truth is the miracle of the market.  Markets help people and improve lives without intending to do so.

            The barber’s life improves every time another person introduces a good idea to the market.  When that other person figures out a new way to cut his own costs, he is able lower his price.  He doesn’t lower his price to help the barber.  He does it to gain market share and increase profits.  Nevertheless, the barber’s standard of living improves as the price falls.  Every time an entrepreneur improves a product, he does it for his own gain.  However, the barber benefits from that improvement, too.  As the smart phone replaces the flip phone, the barber’s life is improved.  As streaming services replace expensive cable and satellite providers, the barber’s life improves.  When a business launches a new product, it does so out of its own greed for profits.  However, the barber now has another option on which to spend his money. 

The barber’s life is improved, not because he has done anything different.  He hasn’t raised his prices, increased his revenue, increased his market share, nor cut his costs to increase profits.  Nevertheless, his standard of living improves year-after-year because of the help and cooperation of countless numbers of strangers that he could never meet even if he were to try. 

The miracle of the market is quite simply something that we too often take for granted.  It is invisible.  It is quiet.  It is humble and does not boast.  And it is possibly the most powerful force to improve human life the world has ever seen.  So before we throw it all away, let’s pause and think about why a barber thrives.

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[1] One caveat: I know nothing of women’s hair dressing.  I am only thinking about men’s barbering.

Being data driven into a ditch

(Originally posted for Carolina Journal on June 4th, 2020 here.)

Written by Paul F. Cwik and Abir Mandal

Governors across the nation announced that the coronavirus-related policies for closing businesses were based on “data driven” analyses by medical professionals. Next, they announced that the reopening phases also would be strictly “data driven.” Over and over, the officials said that they were being guided by “the science” and “the data.” Of course, being guided by science and data is appropriate in a time of crisis; we wouldn’t want it any other way.

However, what if the decision makers were getting only a small fraction of the overall picture? This is not to say what they had was wrong. The information was most likely the best available. Our question is, “What is the likelihood that good decisions can be made if only a small part of the overall picture is considered?” It would be like the chance a blind man has in guessing the weight of an elephant by only touching its trunk.

From the start, officials have been looking at incomplete data. The key statistics that a data driven analysis would need to have is the number of COVID-19 infections, the number of people who are hospitalized by COVID-19, and the number of deaths caused by the virus. If we had instantaneous data of those three variables, then creating an appropriate response would be a straightforward process. Unfortunately, data of this sort never actually occurs.

Taking the wrong path

Where did we go wrong? To get perfectly accurate results would require health care workers to test everyone. Unfortunately, we simply do not have enough tests. When we cannot test the entire population, we take a sample and extrapolate results. In essence, we create a model. Models require simplifying assumptions.

The first hurdle we needed to overcome was the issue that people may be infected and yet asymptomatic. As a result, health care workers had no way of knowing who to test. Since COVID-19 is a novel virus, for which our testing capacity has been and is likely still constrained, the next step would have been to test random people.

Unfortunately, medical necessity and proper statistical methods do not always line up. Medical workers needed to know if the patient in front of them was a risk to others and with a limited supply of tests (especially in March 2020) tests were restricted only to those who were symptomatic. The nonserious and asymptomatic cases were left out. Thus, the data that we were collecting was skewed from the very beginning. This sort of error is called sample selection bias.

Sample selection bias is where the data points of the test sample is not gathered in a random process. As we are observing now, making deductions and deriving estimates based upon biased data is misleading and can lead to disastrous consequences. In fact, it is precisely this bias that has led to the assumption of the death rate being between a range as wide as 0.5% and 16%, as calculated as a proportion of the total number of people tested positive for COVID-19. This estimate depends on the number of people tested positive, which in turn depends on the testing capacity of the country — hardly consistent across the world.

Governments around the world and in North Carolina have based their projections using such biased figures, implying that the disease was many-fold deadlier than the seasonal flu (which has about a 0.1% mortality rate). Unfortunately, this assumption should never have been taken as accurate, because the sample of people tested did not accurately reflect the population of those actually infected.

The rates of infection were unknown at the beginning. But estimates could have been roughly “ballparked” using the lab-derived figures for rates of infection and the empirical multiplier used each year by the CDC to estimate the annual flu load from confirmed cases. Policy makers, who were mostly led by a team of health experts, chose not to pause and do so. Therefore, the projected death rates are likely to be too high by a factor of 50 to 100 times, as now evidenced by the serology tests on the general population which test for COVID-19 antibodies.

Consequences of poor understanding

The overall result was massively inaccurate projections and apocalyptic scenarios. The number of infected people was projected from biased data. Using the number of people infected as the base, the projections of the number of ventilators needed and resulting deaths were grossly exaggerated. A statistician could have helped matters, in our opinion, by highlighting the dangers of conflating the case fatality rate with the overall mortality rate. The unfortunate result was that flawed models, which predicted between 500,000 deaths with social distancing completely implemented, and 2.2 million deaths if nothing were done in the United States, were touted as scientific truth.

The data that has now been released to the public show that these projections are clearly flawed. Furthermore, many government officials, including Gov. Roy Cooper, have simply refused to release the data and models used in making their executive orders. (See here and here.) When looking at more recent numbers, the death rate and hospitalization rates are likely not significantly different than that of an average or bad flu season.

It seems that government officials continue to use the inflated metrics to determine whether, for example, North Carolina should open. Additionally, the debate has shifted from “flattening the curve” to “stopping the spread.” Again, looking at the spread of the virus is also falling into the trap of sample selection bias. Today health departments are looking at the proportion of positive cases, which on the face of it sounds like a reasonable number at which to look. As the number of tests increase, even given a constant number of infections in a community, the number of positive tests would increase.

However, this is where the trap of sampling bias occurs. The tests are still predominantly performed on those who are sick enough to seek testing. People who feel fine (and are not at risk) are not going out of their way to get testing. The collected results do not constitute a true representation of the state’s population and shows nothing about whether the disease’s spread in the community is increasing or decreasing. The only reasonable metric that the state should use is the number of hospitalizations due to COVID-19 like diseases.

Where to look

In our opinion, North Carolina officials should focus on the number of serious hospitalizations (as imperfect as it may be) as the primary metric for its policy making. However, we should not be myopic and only focus on one statistic.

Always, the goal is to use the data properly. Let’s consider the following scenario. Suppose that there is an outbreak of COVID-19 cases in Wake County, what should the government do? Should the entire state be shut down? Or more to the point, should we close Graham or Hyde counties if there is a spike in Wake County?

It is upon these questions that we see science and the law come together. When a political area engages in a lockdown, it is purposefully suppressing the citizen’s legal rights. Recently judges have been rolling back executive overreach by claiming that the restrictions of rights must be of the greatest concern. When rights are to be violated, it must be done in a manner that is targeted and not expansive, it must be short-term and not perpetual, and it must be done under scrutiny of the other governmental branches.

The science is required to assist the law by showing the least oppressive limits of a lockdown. The best statistic to start with is how is the most likely to die. Then who is the most at risk of suffering severe problems. Stemming from these we come to the number of serious hospitalizations. The capacity of hospitals is a limit that cannot be crossed. We have seen the results in Europe when people are denied beds or are “overflow” in hallways because this limit is crossed. Many needlessly suffer. The U.S. goal from the beginning has been to “flatten the curve.” Which curve? The curve of serious hospitalizations.

Setting a better policy

When focusing on serious hospitalizations, government officials at the local and county levels can look at the stress on the area’s hospitals and compare it to the area’s hospital capacity. There are significant differences between regional areas. For example, there are no hospitals in Hyde County but there are 10 in Wake County. Wake County has much more capacity than Hyde County, but it also has a much larger population. If there are 10 cases in Hyde County, a lockdown may be required. However, if there are 10 cases in Wake, a lockdown could be excessive. Using the data in this manner requires policies to be focused. Our concern is the overreach across the entire state.

Furthermore, there is no evidence that statewide lockdowns work. South Dakota did not lock down. Their numbers are no worse than states with the worst encroachments on the freedoms of movement of citizens. Sweden did not lock down. Its death rate of around 330 per million due to COVID-19 is slightly higher than the U.S.’s 295 per million. Sweden’s economy is projected to contract by 5.6%, but not as bad as the rest of Europe at -8.1%. When North Carolina began Phase Two on May 23, the state reported a “surge” in cases. However, this surge of 1,107 cases is an aggregate number of people who have tested positive and is based on a record-setting 26,000 tests. In terms of the number of cases tested positive as a proportion of total tests, the figure for that day is just 6.9%, lower than the dataset average of 7%. Additionally, there is no mention if these cases are in a single county, spread across the whole state, or in areas that have hospital capacity.

A better path

The largest consequence of this statistical illiteracy on the part of American policy makers is that we have essentially destroyed our economy. The irony is that antibodies and herd immunity, either via infection and recovery or gained through a vaccine, are the key to defeating the virus. Keeping ourselves locked up in isolation from each other would not really save lives because the virus is here to stay. Isolation and quarantining are only prolonging our misery. If statewide lockdown measures were not put in place, and instead we chose to protect the most vulnerable, the virus would spread throughout the population, harmlessly for most, while generating antibodies and herd immunity.

The very fact that a spike in the number of cases as our testing capacity increased did not correspond to a similar spike in deaths should have given our politicians pause. Government officials, like all people, are very reluctant to admit that they were wrong. The result of this stubbornness is an overreaching and illogical lockdown that continues today. We need to account for sample selection bias, meaning that we should not focus simply on the number of cases. For example, NC Department of Health and Human Services reports that the plurality of positive tested cases (43%) are for people between the ages 25 and 49. However, 64% of the deaths are 75+ years old. The probability of someone younger than 45 succumbing to the disease is so low, that it can be taken as zero.

Does it make sense to quarantine the people who are in their prime working age range? When we more closely examine the governor’s executive orders, we see that restaurants can open but not bars. Day camps are allowed to open, but not playgrounds. Salons can open but not gyms. For all the calls for data and science, Governor Cooper seems to have regressed to whimsy. Yes, precautions for the most vulnerable need to be taken, but it is past time for our state’s economy to be reopened. If we fail to open soon, it will be as President Trump mentioned: The cure for COVID-19 in North Carolina will turn out to be much worse than the disease itself.

Paul F. Cwik is the BB&T Professor of Economics and Finance at the University of Mount Olive. 

Abir Mandal is an assistant professor of economics at the University of Mount Olive.

The Road: Where we are, How we got here, and Which way to go

(Originally posted on Mises.org:   https://mises.org/wire/current-crisis-has-its-roots-central-bank)

            We have been locked down for weeks.  Classes have been cancelled.  Only essential activities are allowed.  While there is so much to cover and analyze, I want to focus on the economics of the situation.

            To understate it, the situation today is simply not good.  The Covid-19 crisis has caused the world to lock down the population, which essentially ceased most commerce.  While all businesses are affected in some way, a report by the US Chamber of Commerce shows that 24% of businesses are completely unable to conduct business in the emergency state, and further states that 43% of all small businesses are less than six months away (and 10% are less than one month away) from permanently closing their doors.  From their highs in February, the DJIA is down approximately 20% and the Nasdaq is down about 15%.  The initial claims for unemployment insurance since the US Department of Labor’s March 19^th report totals in excess of 22 million people.  A rough calculation places the current US unemployment rate above 17%.  Yes, the situation is not good.

             

How did we get here?

            The obvious answer is that a virus has swept across the globe and caused all of our woes.  While this is the proximate cause of the current recession, it is not the only cause.  In other words, our economic weakness didn’t start in February or March; it has been building for years. 

The most recent recession was over a decade ago.  Here is a quick history beginning with the 2007-08 recession.  In the period that is now called “the housing bubble,” banks bought assets that were backed by mortgages.  These mortgages were driven by politics and an expansionary monetary policy.  People were loaned mortgages that were simply beyond their means.  Eventually reality hit and borrowers started to default on the loans.  As the defaults piled up, the mortgage-backed assets lost value, resulting in the banks’ balance sheets showing that they were in the red.  (The value of their assets fell while their liabilities didn’t, which caused their net equity to plummet and in some cases even turn negative.)  This crisis generated a political response in the form of the Troubled Asset Relief Package (TARP) and the Federal Reserve’s secretive bank bailout was conducted through its facility accounts.

The lesson learned by the banking system was that even though profits are private, losses (if you are too big to fail) could be socialized (i.e., covered by the tax payer).  The consequence of this lesson was to continue to engage in riskier investments on larger margins and make oneself so large in the process that if anything happened, one would be deemed essential and bailed out.

A banking bubble is precisely what has happened since the end of the last recession.  In the years after 2009, the larger banks grew and acquired smaller banks.  Meanwhile the economy grew at an anemic annual rate of 1.6% between 2009 and 2016.

It was against this backdrop that the political winds shifted in 2016.  After Trump was elected, the Congress pushed through a cut in the corporate tax rate (from 35 to 21%).  While this repatriated some overseas profits and stimulated economic growth (averaging 2.5% annual real GDP growth since January 2017), it was not enough to overcome the underlying fragility built up by the previous malinvestments.  Over the summer and fall of 2017, corporate profits began to soften and lose steam.  In nine of the ten quarters since QIII:17, nonfinancial corporate business profit returns fell.  As a result, the value of the banks’ assets softened as well.

At this point, the profits weren’t negative in absolute terms, but they were shrinking from what they were just a year prior.  In other words, the economy was still growing, but it was slowing down.  As profits lessened, we saw y-t-y Real Private Fixed Investment fall from 5.2% in QII:18 to 0.1% in QIV:19. 

Making profits, retaining earnings, and reinvesting these funds into companies is a form of savings.  This fund of savings supports the investments made in the structure of production.  Without these savings, the economy falters.  An alternative way to temporarily prop up investment and consumption (without a firm foundation of savings) is through credit expansion.  However, the problem is that credit expansion creates the malinvestments which we have been building since the end of the previous recession.  At some point, the expansion has to give way to a crunch.  The economy was on the path towards this crunch long before Covid-19 became a reality. 

            Furthermore, a general slowing of the economy also occurred as Real GDP y-t-y growth fell from 3.2% in QII:18 to 2.3% in QIV:19.

With declining profits, a slowdown in investment for future growth, and a slowing economy, the banks’ asset values continued to decline, assets which were highly leveraged.  By law, a large bank must maintain 10% as required reserves.  As the value of the assets depreciated, the banks had to make up that difference to maintain the balance on their balance sheet, resulting in borrowing from other banks.  As we see in the figure below, the short-term rates started to climb in 2015/16, but accelerated their climb in 2017 and 2018.  Part of this climb was due to Federal Reserve monetary tightening, but a large part of it was coming from the banks looking to shore up their crumbling accounts by borrowing funds.

The result of this scramble for funds was a brief semi-inverted yield curve in the summer (June – Sept) 2019.

Today, an inverted yield curve is a financial sign of a forthcoming recession.  As I have shown in my Sept. 5^th article “Inverted Yield Curves, Recessions and You,” a recession was projected to take place between October 2020 and April 2021. 

To counteract and stop the yield curve from fully inverting, the Fed took an unusual step and did something it had not done since October 8^th, 2008.  In September 2019, the Fed injected massive amounts of liquidity into the repo market.  These injections continue today. 

Furthermore, the Fed declared (on March 26^th) that banks no longer needed to maintain a 10% reserve ratio.  The reserve ratio was waived entirely and set to zero.  The combined result of these two actions was intended to make the banks financially sound.  Instead these actions signal an underlying fragility of the fractional reserve system based upon a fiat money.     The bottom line is that, in this crisis, the banks are being bailed out yet again.  What is wrong with the current policy is that by bailing out the banks, they have not learned the correct lesson that investment contains risk.  If these risks are transferred to the taxpayer, the banks will simply continue to build up malinvestments as they get new cash infusions.

The current path is wrong

            Austrian Business Cycle theory explains that for the economy to establish a sound foundation, it must get rid of the malinvestments which have built up in the market.  Simply put, the economy requires a liquidation of the malinvestments.  If there are a lot of malinvestments to be liquidated, then collectively that process is known as a recession.  In an economic downturn, companies go out of business.  This step is unfortunate, painful and sadly necessary.  A person with a cavity needs to see a dentist and have the tooth drilled before a firm foundation can be established.  No one likes to get their teeth drilled, but if they don’t go through the short-term pain, the long-term problems fester and grow. 

            The method of converting from a recession to a recovery is through the liquidation process.  Imagine a store that is unable to sustain itself.  What happens?  It closes, of course, but the story doesn’t end there.  What happens next is the liquidation process, best illustrated through an example.

            Imagine a boutique cupcake shop that has a weekly shortfall of $1,000.  (I am just using $1,000 as an example, the real number would be much larger.)  If the company has a gross margin of 25%, the store would have to sell an additional $4,000 in total sales to make up the shortfall.  If the government is going to stimulate demand by giving money to consumers, then the government would have to give these customers $4,000 per week to prevent the store from closing.  As we can see, demand-side stimulus is expensive.  If, instead, the government cut the store’s taxes by $1,000 per week, it could achieve the same result.  Thus, tax cuts are better policy than demand-side stimulus.

            However, let us suppose that this cupcake company still fails.  The next step is that the bank (and other creditors) foreclose on the shop.  The company has a liquidation sale.  The ovens, tables, chairs, and even the curtains are sold to whomever might purchase them.  The money is allocated to the claimants (creditors and equity holders) in accordance with Chapter 7 of the Federal Bankruptcy Reform Act of 1978.  The claimants are paid according to the absolute priority rule where the common stockholders are the last in line.  (It should come as no surprise that the lawyers always get paid first.)

            Notice that the equipment—the ovens, tables and the chairs—don’t simply disappear.  They are sold to other users.  In these liquidation sales, the buyers are not paying top prices.  In fact, during the economic downturn, prices tend to fall (deflation).  When these new buyers purchase this liquidated capital equipment, they are converting malinvestments into proper investments.  The more flexible the capital is the faster it can be added to other parts of the economy and the quicker the economy can recover.  If, however, the capital equipment is very specific and specialized, then those tools might simply be thrown away and their total value is lost.  To simplify our cupcake store example, suppose that a single buyer purchases the whole store.  Since this buyer has purchased this store for a fraction of the original price, the new owner can make the very same products, sell them at the previously listed prices, but instead of losing $1,000 per week, the store could very well make a profit because its cost structure is much lower.

            In this liquidation process, the banks would lose a part of the value of their loans.  Through these liquidation sales, they will only get a fraction of the value loaned out.  These losses should be made painful to the banks due to their miscalculations.  However, the recent actions taken by the Federal Reserve has protected the banks from these painful lessons.

A new path

            The takeaway points are these: the bubble was caused by massive credit expansion.  The recession was inevitable, and the proximate cause was the forced closures due to Covid-19.  As the economy falls into recession, a continual inflating of the money supply bubble will not create a foundation for future economic growth.  Expanding the money supply will only delay the inevitable and ultimately make the situation even worse.  Furthermore, demand-side stimulus will not produce the “V-shaped” recovery.  Economic growth is generated by saving, investment and capital formation. 

            A three-pronged recipe emerges to quicken a solid and sustainable recovery.   The first ingredient is to build up savings relative to spending.  Savings are the cushion for a falling economy.  It is savings that bidders use to buy the liquidating businesses.  Without buyers of the liquidating capital, the recession cannot be converted into a recovery.  Thus, policies that can quicken a recovery are those that stimulate savings (not spending).

            One troubling point is how little Americans save.  In February 2020, the personal savings rate in the US was 8.2% of disposable personal income.  One of the most prominent features of the CARES Act of 2020 was the personal cash injections directly into people’s accounts.  The argument was that people needed that money to pay for rent, food and other basic necessities.  In contrast, the 2000/2001 tax rebate, as argued by President Bush, was for consumer spending.  In fact, the Bush stimulus was considered a failure because so few people spent the money on consumption.  Unfortunately, neither the 2000/1 nor the 2020 policies help to build up our savings fund.  The better approach is for the government to reverse its spend-and-inflate policies.  The cutting of taxes on activities that defer consumption will ultimately lead us out of the recession more quickly.

The second ingredient is deflation.  Economists have correctly associated deflation with recessions, but they have wrongly concluded that if we avoid deflations, we avoid recessions.  If a deflation is artificially created by a government, then yes, a recession will be the result.  However, deflation is the natural way in which an economy repairs itself.  It does so on two fronts.  The first is through the liquidation process.  In our example, the store had an oven.  Suppose that it was originally purchased at a price of $5,000.  If the new buyer spends $3,000 to acquire it, he has $2,000 which he could allocate to other factors of production.  Thus, as capital equipment prices fall, it becomes easier for new entrepreneurs to get started in the recovery process.  The second way in which deflation is beneficial is for the consumers.  As prices fall, their purchasing power grows.  This increase in purchasing power is especially important for those who are now unemployed.  If the weekly grocery budget was $300 per week, now the same amount of food can be purchased for less.

            The third ingredient is anything that can expedite the liquidation process.  Laws should be reformed to make the bankruptcy process easier.  Additionally, mergers and acquisitions should also be made easier. 

            During this crisis, it is unfortunate that many people are using this opportunity so advocate for socialism, nationalization, and the adoption of modern monetary policy.  Every time socialism has been tried, it has failed to produce enough wealth for its people.  The nationalization of industries have failed because bureaucracies simply cannot engage in economic calculation.  And while modern monetary theory may seem new and novel, it is nothing more than the repackaging of the ideas of the “monetary-cranks” of the nineteenth century.  It is now more critical than ever to return to what we know works—free markets.  History shows us time and time again that free markets generate sustained economic growth.  Adam Smith found the formula as early as 1755.

Little else is requisite to carry a state to the highest degree of opulence from the lowest barbarism, but peace, easy taxes, and a tolerable administration of justice; all the rest being brought about by the natural course of things. All governments which thwart this natural course, which force things into another channel, or which endeavour to arrest the progress of society at a particular point, are unnatural, and to support themselves are obliged to be oppressive and tyrannical.

It is not a coincidence that when nations liberalized trade and opened markets, there was an explosion of wealth for all—the rich, the poor and everyone in between.  This simple insight set off an upsurge of growth that has had a greater impact on humanity than any virus, natural disaster, or war.  It is time to simply let individuals be free.