Bureaucracy: The Lost Gem

• I have written an article about one of my favorite Mises books Bureaucracy.  It is found in the book: A Companion to Ludwig von Mises, p
• ublished by the Universidad Francisco Marroquin.  I hope that you enjoy reading it.

• 
  
  It was published in May 2020.  Here is a link to the chapter:

https://www.researchgate.net/publication/358672765_Bureaucracy_The_Lost_Gem

Wilson, Waldo, Woke CEOs, and Ways Forward

The Murray N. Rothbard Lecture by Paul Cwik. Recorded at the 2022 Austrian Economics Research Conference hosted at the Mises Institute in Auburn, Alabama, March 18–19, 2022.

Found here: https://www.youtube.com/watch?v=hPunveKSIGw

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.

Cwik Speaks at John Locke Foundation in Raleigh, NC

In early December, I was asked to present a lecture on the state of the Macroeconomy at the John Locke Foundation in Raleigh, NC.  Here is a recording of the presentation:

https://www.facebook.com/johnlockefoundation/videos/762162070878564/

Afterward, I was asked to do a short interview.  It is posted here: https://youtu.be/eNEIzn0FdrE

Cwik Lectures in Europe

Over the Summer of 2019, I was fortunate to be able to give a series of lectures in three different European countries: Poland, the Czech Republic, and Germany. 

I started the trip by delivering a lecture at Wroclaw University in Wroclaw, Poland.  On May 30, 2019, the talk I gave was called, "Macroeconomic Challenges: An Introduction to Austrian Macroeconomics."  This lecture was presented to faculty, graduate students, and undergraduate students.

With my host: Mateusz Machaj

Lecturing at Wroclaw University

On May 31, I participated as the featured guest in the Structure of Production and Capital Theory seminars.  There were about 15-20 dedicated Austrian economics students that attended all of the sessions.

Quite a special group of dedicated Austrian Economists

In Prague, my first lecture (June 25, 2019) at the CEVRO Institut, Prague, Czech Republic, was called, "Capitalism's Heroes: Prices, Profits and Losses."  The President of the Institut, Josef Šíma, was a very gracious host.  And I am proud to have been able to work with him and his faculty.

The beautiful CEVRO facility

There were about 50 general business students there and it was well received.  

The first lecture in Prague

The second lecture in Prague took place the following day, on Thursday June 26, and was to the advanced PPE students.  There were half a dozen of the school’s top students that attended my lecture on "The Yield Curve and the Structure of Production."

With the Advanced Graduate Student group

On the 4th of July I delivered my final European lecture at the Institut Für Wirtschaftsprüfung, Universität des Saarlandes in Saarbrücken, Germany.  My host Dr. Michael Olbrich went above and beyond normal hosting duties.  He took me and my family to the town of Trier, showed us around the university's town of Saarbrücken and even hosted a cook out with his faculty and staff.

The title of the talk was "Capitalism’s Heroes: Prices, Profits and Losses."  This lecture was presented to students, graduate students and faculty.  There were over 50 people in attendance.

No surprise, the students filled the back rows up first!

The faculty are in the front row

An action shot.

The faculty were so wonderful.

To all of those that worked with me and my family, who hosted us, those dealt with our emergencies, and to the students who endured my lectures, I want to say thank you.  Thank you for a wonderful time and experience.  I hope that it was as profitable for you as it was for me.

Inverted Yield Curves, Recessions, and You

(This article is also found here: https://mises.org/wire/inverted-yield-curves-recessions-and-you)

If one reads the headlines you might think that since the yield curve has inverted, the economy is in a recession, Trump will be swept from office and then the Progressives’ goals are right around the corner.  Not so fast!  While much of that may still happen, we are not there yet.

While some on the Left may be openly hoping for the economy to slip into a recession, we are not currently in a recession and whether we are heading for one requires some serious economic analysis.  To understand what an inverted yield curve means, we first need to understand what the yield curve is.

What is the Yield Curve?

            Often, when economists think of the economy, they simplify.  This action is necessary.  They try to focus on the important factors and set the less important and irrelevant factors aside.  Thus, a theory of how the economy works is an abstraction that tries to illustrate causal and connected links. 

            In many economic models, economists use a single interest rate to represent the whole intertemporal market.  Often they will theorize that when the interest rate rises, X will happen or if the Fed lowers the interest rate, then Y will be the result.  However, the real world does not have a single interest rate.  In fact, there are many interest rates.  When we separate interest rates across maturities, we get what is called “The Term Structure of Interest Rates.”  So across this structure, there will be an interest rate for a 3-month instrument, another interest rate for a 1-year instrument, a different one for a 10-year instrument, and so forth. 

            When we look at a very specific type of term structure, where the default risk is at zero, we are looking at what is called “The Yield Curve.”  In the US economy, there is really only one market where we find zero default risk and that is the market for US Treasury Bills, Notes and Bonds.  The reason why there is zero default risk is that if you go to cash in your US Treasury Bond, you will always be able to get dollars.  Since the dollar is fiat money, meaning that it is not backed by gold, the US government can always create more dollars to honor its obligation.  (Of course the value of the dollar will be eroded by the money creation, but that’s a different story.) 

If we plot out the different maturities across the horizontal axis and the percentage rate of returns on the vertical, then we will have a graphical vision of the Yield Curve.  Typically, the short-term rates are lower than the long-term rates.  Graphically, we would see an upward slope.  There are two major reasons for this: inflation risk and liquidity preference.  Inflation risk is the risk that stems from the fear that the value of the dollar will depreciate over time.  As we look at the historical inflation rates we see that the value of the dollar has been continuously eroded since we left the gold standard.  Liquidity preference stems from an uncertain future.  (See Figure 1.)

An investor might reason in this way, “I want to invest my money, but what if something happens and I need cash?”  This reasoning reflects the fact that it is better to be liquid than not.  When we add a term structure to the investment, we see that this risk changes over the various time horizons.  So what is the risk of something happening where I will need cash in the next 3 months?  Now compare that risk with tying up money for one or two years.  Then compare that risk with tying up money for 30 years.  As the length of maturity increases, the risk of something unexpected happening also increases.  Thus, as we look further into the future, we see a higher degree of compensation to cover this ever-increasing risk. 

So while there are different segments along the yield curve, each segment is not independent from other segments.  This interconnection comes from arbitrage.  If an investor is able to make more money in one segment, he can easily sell in one area and buy in another.  Thus, the yield curve is interconnected through supply, demand and arbitrage.  An inverted yield curve is where the short-term rates are higher than the long-term rates, i.e., it is downward sloping.

Where are we now?

            Is it true that the yield curve has inverted?  The answer to this is like many answers in economics, it is both a “Yes” and a “No”.  On August 5, 2019, the daily rate of the 10-year bond fell to 1.75%, while the 1-year bond rose to 1.78%.  (Incidentally, the 2-year bond, which the press was talking about, has not closed above the 10-year rate between August 1 and August 26, 2019.)  According to the US Treasury, the 1-year bond has closed above the 10-year bond every day since August 5^th, but the largest gap has only been 0.21%.  Additionally, the 10-year rate has closed less than the 3-month rate every day since the middle of May 2019 (with the lone exception of July 23, 2019).  So right now, I would say that the yield curve is flat, but it has been trending toward an inversion for quite some time. 

           

Why does any of this matter?

If we strictly look at the data, we see that an inverted yield curve is an excellent predictor of an oncoming recession.  However, there is a difference in the types of data that we use.  On any particular day, anything can happen.  For example on August 21, the last place Detroit Tigers beat the Houston Astros (with Justin Verlander pitching) with baseball’s biggest upset in 15 years (odds were between +435 and +560 for Houston).  The point is a daily number is too erratic to make meaningful predictions.  As a result, I use monthly averages.

If we look at the monthly data, we see that prior to every recession since 1955, the yield curve inverted four to six quarters prior to the onset of the recession.  See Figure 2.

            In Figure 2, the yellow vertical bars represent recession.  The lines are the differences between the various long-term rates (10, 20 and 30 years) and the two short-term rates (3 months and 1 year).  When the difference falls below zero, the yield curve has inverted.

Now the real question is whether there are any false positives, where the difference is less than zero and there is no yellow bar.  The answer is yes, there was one in 1966-67.  However, depending on which dataset one looks at, there was either one quarter of negative growth (or nearly negative) in 1967.  Recessions are typically categorized by at least two quarters of negative growth and so I believe that the relationship holds.

            If we take a closer look at the yield curve spread and add some straight line projections, we get Figure 3.

What we see here is that whole curve is flattening.  Furthermore, if everything continues along these straight lines (which never actually happens) we should expect to see the yield curve truly invert around October or November of 2019.  And if history follows the past, we should then expect to see the economy in a recession 4 to 6 quarters later, meaning that somewhere between October 2020 (around election time) and April 2021, the economy will be contracting.

            Is this a fait accompli?  Is this story written in stone?  By all means, “No.”  History may rhyme, but it is not fatalistic.  To understand where we are headed, we need two things, the facts and, secondly, the context within to put the facts in order to understand them.  In other words, we need some data and a theory.

The Data

To start, we will take a look at the monthly rates of US Treasuries from 1953 until August 2019.  See Figure 4.

Figure 5 shows a close up view between 2003 and August 2019.

What we see is that while the long-term rates have come down a little bit, it is jump in the short-term rates has flattened and may eventually invert the yield curve.  It appears that by 2016, the increase in short-term rates was well underway.

The next question that we should be asking is, “What is it that is driving up short-term rates?”  In order to find the answer, we first need to know where to look and that knowledge comes from economic theory.

The Theory

            In 2004, I finished my dissertation examining the relationship between the yield curve and economic downturns.  What I found is that this is a very complex relationship.  The reason why short rates are changing is simply due to changes in supply and demand. The difficulty lies in tracing those root causes of these changes.  In order for the short-term rates to climb, there must either be a decrease in the supply of loanable funds, an increase in the demand for loanable funds, or a combination of both forces.

Is there a decrease in the supply of short-term funds on the market?  While the Fed has been engaged in some monetary tightening, interest rates have been at historically low levels since 2008.  (Take another look at Figure 5 above and focus on the short-term rates between 2009 and 2016.)  Furthermore, in July the FOMC (the Federal Open Market Committee sets the targets for short-term interest rates) officially reversed course and announced lowered the targeted rates from the 2¼ – 2½% range to the 2 – 2 ¼% range.  So, it is safe to say that it rise in short-term interest rates is not really a function of tightening supply.  Thus, it must be a function of demand.

The question we need to next investigate is, “Why is there more demand for Short-term Loanable funds?”  It is here that things become complex.  We must first start with the Austrian Business Cycle Theory (ABCT).

The ABCT says that economic recessions can be caused by an expansion of artificial credit.  This expansion leads to relative decrease in the interest rate (yes, we are assuming a single interest rate here).  The relative decrease in the interest rate will cause several things.  First, it will cause a shift from savings towards consumption.  Secondly, it will not simply cause an increase in investment spending (overinvestment), but it will also cause a misdirection of the capital spent (malinvestment). 

As the credit expansion follows its course, it causes an artificial economic boom.  During the boom, there is expansion throughout the entire economy, however there are concentrations in two particular sections of the economy: the early stages and the final stages of the production process.  The early stages are where we are clearing land and pouring concrete foundations.  As a result, if we make a mistake, these can become very costly.  The final stages of economic production are those closest to the consumers.  While these later stages are also subject to the business cycle, the severity of fluctuations at these stages are less than those of the earlier stages.

In my dissertation and in a subsequent article, I argue that as we near the peak of the economic expansion, profit margins will be squeezed by rising input prices.  As input prices climb, businesses will seek short-term financing to complete their projects.

An Illustration

            Suppose that you are a home builder and the interest rate stands at 6% (as it did in 2001).  You have looked at the market and expect the return on your building and selling of homes will yield a 4% rate of return.  Of course, you do not put your money into this project.

            Now suppose that the interest rate has fallen from 6% to 1% (as it did in 2003).  What will you do?  If you do nothing, your competitors will leave you standing in the dust.  You must keep up with your competitors and thus you choose to invest.  Suppose that while you want to make 6 houses, there are only enough bricks for 4.  Can you start 6 foundations?  Yes, of course.  No one in the economy really knows how many “bricks” (available resource inputs) exist in the current and near future economy.  And so as an entrepreneur, you follow the market signals and start 6 foundations.  As you and your competitors start to use the bricks, the price of these bricks starts to climb.  As the price of bricks climbs, the funds at your disposal no longer cover the costs of completing the 6 houses.  Without getting the bricks, the houses will remain incomplete and the project will be a huge loss.  It is imperative that your company gets those bricks.  And so your home building company is willing to borrow short-term money at higher and higher rates in order to complete something and reap at least a little return from the project.

Back to the Data

So according to the theory outlined above, we are positing that the interest rates are climbing in the short-run because of input price increases, which are squeezing profit margins.  So, the next step is to look at input prices.  Unfortunately, the data that is collected by US governmental institutions were designed from a Keynesian perspective.  Thus, the data that an Austrian would like to look at doesn’t really exist, at least not in a format that we would prefer.  Nevertheless, there are some general statistics that we can use.  I have pulled six statistics from the Federal Reserve Economic Data which pertain to commodity prices: PPI: All Commodities, Global Price Index of All Commodities, PPI: Construction Materials, PPI: Construction Machinery, PPI: Iron and Steel, and PPI: Plastics and Synthetic Rubber.

           If we look at the short-term interest rates in Figure 5, we see that they start to climb in 2016.  What does tracking these commodity prices from 2016 through 2019 show us?  In each category we see prices rising, just as the theory predicts.  Furthermore, if we look three years before 2016 and examine the range between 2013 and 2016, what do we see? As summarized in Table 1 below, in four of the six categories, the prices were falling.  The two categories were the prices were increasing (PPI: Construction Materials and PPI: Construction Machinery), we see that the rate of increase has accelerated after 2016.

Table 1	Annual Percent Change 2013 - 2016	Annual Percent Change 2016 – 2019
PPI: All Commodities	-3.40%	+2.77%
Global Price Index of All Commodities	-23.01%	+9.81%
PPI: Construction Materials	+0.48%	+3.15%
PPI: Construction Machinery	+1.45%	+1.79%
PPI: Iron & Steel	-8.97%	+6.75%
PPI: Plastics and Synthetic Rubber	-7.50%	+2.96%

What should we look for next?

The takeaway from the analysis so far is that we are coming to the end of an economic boom and nearing the upper turning point of the business cycle.  The next phase in the business cycle is business failures and bankruptcies.  According to the ABCT, the areas that we should be looking for bankruptcies are in the early stages of production. 

There are some signs that bankruptcies are increasing.  We can see that there is a lot of economic distress in the farming sector, but this might be more the result of the trade tariffs than the normal course of the business cycle.  The Chinese know that a lot of political support for President Trump lies within the agricultural community and so they have specifically targeted their trade tariffs on this constituency group.

The overall point is that the data is not yet clear.  In fact, it is probably a little too early in the business cycle for a disproportionate amount of bankruptcies.  Bankruptcies occur all the time, in both good and bad economic times.  So, as the yield curve inverts over the next several weeks or months, we should expect to see a steadily rising amount of bankruptcies until we make the turn and the bottom falls out.

What can be done to mitigate the next recession?

Many people believe that the higher you go, the greater the fall.  When it comes to business cycles, it is simply not the case.  We can have a small upswing and a dramatic collapse, a large upswing followed by a mild recession, or anything in between.  The key market factor in determining the level of economic decline is the amount of savings.  Simply put, the larger the amount of savings, the smaller the downturn will be.  Thus, anything that can be done to stop discouraging savings should be done.  This is not to say that government should force savings to occur, but every policy where the government is currently encouraging spending over savings should be stopped.  For example, when the government decides to increase spending to stimulate consumption, it is shifting funds that would have been otherwise saved into spending.  The policies that the government enacts during the downturn will strongly affect the size and duration of the collapse.  Misguided policies, such as stimulus spending, actually prolong an economic downturn and delay a full recovery. 

Nevertheless, there are steps we can take that encourage savings.  Here are three examples.  First, we can cut the capital gains tax.  Savings are actually deferred consumption.  Since retained earnings are a form of deferred consumption, they are a type of savings.  So any policy that taxes or discourages retaining earnings should be abolished.  Secondly, if the US changes from the income tax to a consumption tax, there would be a disincentive to spend and thus a relative incentive to save.  And third, if the US Federal Government balanced budget by cutting spending, there would be an encouragement of savings.  Currently, the US Federal Government is borrowing money to finance its spending.  These “saved” funds are not actually saved, but spent by the US government.  By cutting the amount that the government spends, these funds will shift back into the private sector as investment funds.

Furthermore there are some additional steps that we could take to mitigate the recession.  First, we need to recognize that the artificial bubble was caused by the expansion of the money supply.  We need to stop this inflation.  Denationalizing and deregulating the money supply would be a step in the right direction.

Secondly, we could make the bankruptcy process easier.  The way in which we turn a recession into a recovery is by clearing out the misaligned capital structures and converting the malinvestments into proper investments.  In the last downturn, the Federal Government bailed out General Motors.  Suppose, instead, what would have happened if it did not bail out GM.  GM would have gone bankrupt.  It would have had to sell its assets to generate cash to pay its creditors.  Thus, GM would have had to sell Cadillac and Corvette.  Of course, Cadillac is not worth zero dollars.  There would be buyers for Cadillac, maybe Ford or Toyota or Elon Musk.  Whoever the ultimate buyer would be, that buyer would not have to pay top dollar for Cadillac (it is a going-out-of-business sale).  This new owner could then, on the very next day, turn on the very same machines, produce the very same car, and sell it at the very same price.  However, this new owner would be able make a profit where old GM could not.  Why?  It is because this new owner has a lower cost structure.  The new owner bought the capital in a fire sale.  This process is how we convert a recession into a recovery.  Thus, by making the bankruptcy process easier and faster, the economy can realign itself more quickly.  If we continue to follow this logic, if we also make mergers and acquisitions easier, we can reduce both the depth and the duration of the recession.

Many people have claimed that the Austrian approach leads government officials to “do nothing” in the face of a recession.  When the people are clamoring for “something to be done” the Austrians say, “No.”  But this this is simply an empty charge.  Outlined above are several positive steps that can be taken to reduce the size and scope of the recession. 

I do not know when we will reach the upper-turning point and start the economic slide into recession.  From this analysis, I can say that it is coming.  If history follows the same path, then sometime between October 2020 and April 2021, we should be in a recession.  The questions of how long it will last and how deep it will get depend upon our response and the policies we enact.  Since we know it is coming, we can prepare.  We can curb our personal spending and accumulate savings.  We have at least a little time to prepare.