Robber Baron Capitalism in Four Lessons – Part II: Hamilton’s Theory of the Business Cycle

Our series into Capitalism continues. In this, our purpose is in no small degree to wean you Libertarians of an Austrian bent away from Austrian economics and toward Alexander Hamilton’s superior vision of economics, Robber Baron Capitalism.

We now take aim at that pillar of Austrian economics, the Austrian theory of the business cycle, knock it down to size, and replace it with an explanatory model that builds on what you have learned in Part I.

We also expand on why, in Part I, we emphasized policy makers should view their nation’s economy from the prism of sectors.

The Austrian take on the business cycle is an interesting, but ultimately unsatisfactory, explanation of boom and bust. At most, their theory explains why fractional reserve banking can in some cases reinforce poor economic decision making.

But, as you will see, its explanatory power falls short in important areas.  Not the least of which is its explanation of boom-bust cycles and their remedy for it, a remedy which might be labeled an ideal Austrian Monetary System (AMS).

It is especially weak compared to the Hamiltonian theory of the business cycle we now introduce to you.

First we outline the respective assumptions behind the Hamiltonian and Austrian positions and the propositions that flow from those assumptions.

 

A Note on Empiricism, Regression Analysis and Praxeology

Although the remainder of this article will analyze business cycle theory from a game theory perspective that is more compatible with classic Austrian economic analysis than regression analysis, I am going to dedicate this one section to commenting on what are misunderstandings Austrians have about regression analysis and its implications for their theory of the business cycle.

One Austrian criticism of regression is that causation – especially in economic fields – cannot be proven through regression.

This is false.

The Gauss-Markov theorem has proven that causal relationships (not mere correlations) between an outcome variable (dependent variable) and influencing variables (independent variables) can be mathematically represented in any field of study – including economics as well as medicine, psychology, criminology, etc., etc., – so long as the variables in question are sufficiently quantifiable.

A more fundamental problem with Austrian thinking about regression is their misunderstanding of when regression is most useful as a scientific tool.

Austrians often claim regression cannot be used to refute their business cycle theory because economic variables and their correlations are too subtle and complex due to human action to be sure statistical conclusions are truly scientific conclusions.

It is true that the results of regression analysis become more questionable when used to study a causal relationship where the independent variables exercise weak-to modest influence over the dependent variable (although this too can be overcome with strong methodology and if the conclusion is repeatable in other studies).

However, this fact does not help the Austrian Business Cycle because the ABC is a single variable theory – i.e., one independent variable (monetary conditions) exercises overwhelming causal power over a dependent variable (economic growth and decline cycles).

For single variable theories (like the ABC) regression is a very powerful scientific tool because regression can easily detect if a causal relationship between variables overwhelms the impact of others; relationships such as the Austrian claim monetary conditions overwhelm the impact other economic factors exercise over the business cycle.

In the past, regression has been used to repeatedly prove single variable causal relationships in economics like the causal relationship between supply variables and demand variables.

If regression can be used to mathematically express the strong statistical relationship between supply and demand, then regression is also the right tool to use to prove or disprove whether the strength of the relationship between monetary variables and business cycle variables exists to an extent sufficient to justify Austrian theory.

Austrians might still claim that they have no burden to so much as respond to statistical objections to the ABC because their theory is true “a priori” and Austrians have already explained why it is “a priori” true with their own statements.

But whether or not the ABC can be expressed “a priori” does not protect it from statistical objections because other strong economic relationships can also be expressed in Austrian “a priori” statements yet also have been supported by regression analysis.

For instance, the relationship between supply and demand – a relationship which Austrians have also expressed and argued in favor of with “a priori” statements – has been supported in many studies using regression.

But Austrians have never claimed regression studies of supply and demand are faulty on grounds that supply-demand relationships can be expressed in true “a priori” statements.

The fact is a that any economic relationship that is “true a priori”, that exercises a powerful causal relationship to an economic phenomena, and that is quantifiable as money supply and growth cycles are, should also be expressible in terms of regression analysis.

That mainstream economists using regression have not found a convincing relationship between money supply and the business cycle as Austrians have predicted is, despite Austrian protestations to immunity, a strong argument against them.

That Austrians make little to no attempt to answer statistical objections to the ABC demonstrates a great weakness on the part of Austrian thinking, and rightly justifies mainstream economic disregard for Austrian economics.

Austrians would be well advised to seek advice from statisticians to better understand that regression analysis is in fact relevant to the ABC.  So far, their refusal has only led to statisticians discounting Austrians because of Austrian failure to even consider the substantial statistical objections to their central theory.

 

Hamiltonian Theory

Hamiltonian Assumptions

• If producers align their operations to satisfy any boom in customer demand for any kind of good or service a cluster of economic errors will necessarily occur that will lead to a bust because producers can never under any circumstances consistently, mathematically, project exactly how much demand there currently is or will be at a future point.

Hamiltonian Propositions

1. Booms in demand are usually concentrated around a specific economic sector or group of sectors that have particular resources and operations more capable of satisfying this demand than other sectors (e.g., the resources of the housing sector are better positioned to satisfy housing demand than the health sector, etc. etc.)
2. More sector resources will be devoted to satisfying a boom sector(s) the more customer demand increases.
3. Downstream sectors that indirectly support booming sectors (e.g. raw material supply sectors that support booming factory production) will themselves align their production to support booming demand in the leading sector(s).
4. So long as the lead sector(s) is booming its supporting sectors will proportionally expand.
5. When a sector or sectors boom strongly enough, the boom can drive total national economic growth upwards.
6. Eventually booming demand will cool off as utility to the customer is reached.
7. When customer demand falls, producers that once directly met this demand reduce the resources, workers, inventory and capacity, etc., etc., dedicated to meeting this demand.
8. Downstream sectors that supported the lead sector(s) during the boom respond to the leading sector’s slowdown by also cutting back on their own resources, workers, inventory and capacity.
9. Missing demand projections is what causes resources to be malinvested and this malinvestment is the cause of the general cluster of business errors that lead to bust.
10. If the decline in demand affects enough sectors strongly enough the broader economy will also contract.
11. Loose monetary policy is insufficient cause to increase production if the business believes the action does not bring enough business value.
12. Capital goods are especially hard hit when demand falls because reallocating capital resources is more time consuming than reallocating other resources is (e.g., firing workers in the marketing sector during a bust can be done faster than a manufacturer can shutdown a manufacturing plant).
13. Thus, the only way to prevent boom and bust cycles is for producers to anticipate customer demand exactly in advance so that excessive resources are not over-allocated when demand plateaus and then declines.
14. Because it is impossible for any producer to project customer demand exactly economic busts are impossible to eliminate, regardless of whether an Austrian Monetary System (or any other monetary system) is in place or not.

 

Hamiltonian Arguments Against the Austrian Business Cycle

In a very basic way both Hamiltonian and Austrian business cycle theories agree economic declines are the result of market signals encouraging producers to indulge speculative bubbles by overinvesting (malinvesting/misallocating) their resources during a boom.

The point where Austrian theory falls short lies in its simplistically assigning the cause of overinvestment to “faulty” signals created by monetary stimulus under fractional reserve banking. This has given rise to a number of flimsy assumptions and questionable logic that deserve to be challenged.

First, Austrians exaggerate how much more accurate projections of customer demand would be absent excessive FRB monetary stimulus. And let there be no doubt how important accurate demand projections are to preventing distortions in the structure of production that lead to busts. To eliminate these distortions customer demand must be projected beforehand with perfect accuracy by the producer so the producer’s resources are exactly aligned at all the right times with demand. If demand and production are not exactly aligned at the right time a general cluster of malinvestment develops because producers either produce too little or too much relative to what perfect demand estimates would justify.

While Austrians are right to point out excessive quantitative easing distorts market signals it does not follow that an Austrian monetary system would eliminate faulty signals to a point where perfect demand projections are feasible. This is because perfect demand projections are inherently impossible to make regardless of what monetary system – or any type of economic system whatsoever – exists. Too many other random variables aside from monetary conditions impact demand for a producer to ever make consistently perfect projections (Note we are talking about consistent projections. On very rare occasions models of customer demand do estimate demand precisely ahead of time. But these instances are one-time statistical coincidences which the models are unable to repeat with the same accuracy).

Second, Austrians cannot explain why general clusters of errors accumulate in particular areas of the economy without making reference to demand.

The Austrian explanation of how human behavior reacts to easy credit is, roughly –

1 – Loose credit encourages producers and consumers to misread market signals.
2 – Producers and consumers use excess credit to speculate.
3 – A general cluster of errors in the structure of production arises from this excess credit.

But credit availability is not a sufficient explanation – on purely praxeological grounds – for what human actions led to this cluster of production errors.

In cases where FRB monetary policy is excessively loose, this excess of credit is available to fund speculation in any business action. But not all business actions attract the same level of speculative mania which lead to production distortions. In fact, only a small number of possible business actions that could employ credit are taken at all.

For example, Austrians claim easy credit encourages excessive speculation in new technological innovations. But Austrian theory fails to explain why speculators and producers chose a specific innovation or group of innovations to speculate on – there are always many innovative technologies businesses do not act on. Why is it that certain kinds of innovations attract hot money, thus concentrating a cluster of economic errors in a specific sector or group of sectors, while other innovations did not attract speculation despite FRB generated credit being available for any activity?

For speculative and production actions to be made there must be a perception that a particular economic activity is in or will be in demand and that satisfying demand provides business value to the producer.

Easy credit by itself can sometimes make the difference in whether a producer engages in a marginally profitable activity. But unprofitable activities will largely remain unattractive to speculation while profitable activities will still invite speculative bubbles for reasons unrelated to credit conditions. Even under tighter conditions preferred by Austrians, producers will still often feel the business value of satisfying growing demand will justify taking loans at higher interest rates.

Thus the correct and more complete Hamiltonian explanation of how credit influences the business cycle is –

1 – Loose credit can encourage producers and consumers to misread market signals and overproduce, but credit in isolation is insufficient grounds to explain why producers overproduce.
2 – Producers and consumers speculate on a boom in customer demand regardless of whether credit is loose or tight.
3 – A general cluster of errors in the structure of production arises from the attempt to satisfy once booming demand when this demand cools off.
4 – Because demand cannot be projected perfectly in advance due to random factors, boom and bust cannot be eliminated through changes to the credit environment or any kind of change whatsoever in the economic environment.

Only customer demand for a specific type or types of goods or services explains why a cluster of errors occurred in the location they did. Without acknowledging particular surges in demand, the explanatory power of the Austrian outline fails.

Acknowledging demand heavily influences the business cycle undermines the strength of Austrian theory because demand adds numerous other variables to their one-variable explanation:  Anything that is an obstacle to projecting demand perfectly will contribute to malinvestment. Since the reasons projections cannot be made perfectly are essentially infinite, the explanatory power of a credit driven business cycle sinks to irrelevance.

Third, Austrians never take into account that credit conditions might be too tight under an Austrian monetary system. If Austrians point out an excess of FRB generated credit often contributes to over-speculation in an innovative technology, why do they assume under the restrictive conditions Austrians prefer that credit cannot be too low for certain producers to take benefit society by investing resources into innovative technology?

In reality interest rates are, like economic value, subjective because different economic actors will react subjectively to the same credit conditions in very different ways.

Under the tighter lending conditions of an Austrian monetary system, any cash rich business would still be able afford to speculate with credit more than small businesses, or startup businesses that usually run at losses for a number of years. Therefore there cannot be any numerically “correct” credit conditions to set for an ideal Austrian monetary system, or any other type of monetary system. There are only a set of tradeoffs between different types of credit conditions that will still lead to malinvestment.

Moreover their belief in an objectively “correct” credit environment (e.g., interest rates, supply of money, etc. etc…) exists contradicts Austrian skepticism of quantitative economic empiricism itself.  If it is true there are “correct”, numeric, values that should be represented in the credit environment, those “correct” metrics must be subject to quantitative and empirically based methodologies.

To suggest there are objectively “correct” credit conditions cannot be reconciled with Austrian logic that assumes the subjectivity of economic value.

Austrians believe simultaneously –

1 – In modern FRB monetary systems, quantitative metrics of the credit environment are often objectively, numerically, quantitatively, wrong because credit is too easy.
2 – Economic actors base their actions on their own subjective interpretation of what they consider is economically valuable; and that what one actor subjectively considers valuable is usually valued differently in the preference rankings of a different actor.
3 – If FRB monetary systems are replaced with a restrictive Austrian monetary system, actors that make subjective decisions will stop making the “objectively wrong” decisions they made under FRB and instead make enough “objectively correct” decisions to eliminate the business cycle.

This “objective truth” in #1 that Austrians cling to leads to complete incoherence throughout the rest of their business cycle analysis.

It results in them making objective, quantitative value judgements about economic activity that are inherently subjective in nature.

For example Austrians often blame FRB managed credit systems for causing “too much” investment with cheap credit into technological innovation which then leads to malinvestment and bust.

But by saying there is “too much” investment in technology makes the mistake of objectively and quantitatively passing judgment on the value of an activity that is, by their own ideology, subjective.

On what basis can Austrians claim technological investments are objectively excessive? For some businesses investing in technology with borrowed money gave them a long term competitive advantage that was more valuable (to them) than whatever losses they suffered during the crash. Others that did not take advantage of easy credit to upgrade their technology led to their going out of business.

Also the assumption that tightening credit will prevent malinvestment in technology is wrong because not investing in technology may well lead to a crash. A small nation whose monetary system is Austrian and which is dependent for economic growth on agriculture will crash if it cannot borrow enough to upgrade its agricultural technology relative to a foreign agricultural economy that uses FRB and outcompetes them in farm productivity.

Hamiltonians accept that interest rates are inherently “subjective”, therefore there is no “correct” monetary system. There are only tradeoffs between monetary systems.  An Austrian monetary system simply creates new problems that do not stop boom-bust, nor prove that FRB is inherently worse than alternatives.

Just as Austrians clumsily try to have it both ways with objectivity and subjectivity, they also make a hash of their simultaneous rejection of empiricism generally but selective use of empiricism elsewhere.

For example, Austrians may claim that instead of the Federal Reserve setting rates at 1.5%, an Austrian monetary system would “correctly” set rates at 15%; or the money supply should be 30% of what it is.

Even claiming Fed rates are “too low”, while not suggesting what they “should be”, is a quantitative judgment.

But since Austrians insist the ability of economists to derive objective truths from quantitative and empirical methods is very limited, how can Austrians claim to know what are “correct” or “wrong” credit conditions without making quantitative arguments for what they should be?

Obviously, Austrians cannot claim what “correct” values should be given they reject quantitative methodology. Without empiricism, Austrians can never justify their rationale for why such metrics are numerically too high or too low to prevent malinvestment.

And if they were to do an about face on empiricism, they would be inviting quantitative testing into their theory of how credit conditions relate to the business cycle.

The Austrian’s ideal monetary system would substantially depend on a precious metal standard (we’ll assume gold, but the argument will be as applicable if a different precious commodity is used).

Unfortunately for them there is no necessary causal relationship between the price of gold (or any other precious metal or rare commodity) and what it should cost a business to borrow.

The price of gold is, like all other prices of all other goods and services, an aggregated reflection of how different gold customers subjectively value gold according to each customer’s different hierarchy of preferences. Among the uses of gold that are factored into its market price are its industrial applications. If Austrians had their way how heavy industry uses gold in certain mechanical processes would, by helping limit the supply of gold, partly influence what rate a food processor, raw material supplier, biotech companies, and pharmaceuticals can borrow at to fund their operations.

But why should gold’s industrial uses impact borrowing? How does it lead to better business decision making? It cannot because there is no logical connection between its industrial applications and borrowing.

And if a substitute for gold’s industrial uses were found, the price of gold would fall and credit would become looser.  Why should a decline in gold’s industrial usages increase the supply of money?  Again, there is no logical connection between gold’s loss of favor in manufacturing and what rate other companies should borrow.

Finally, Austrians claim their credit theories best explain why capital goods are so hard hit during busts. It is not clear why they insist on this because Austrian theory isn’t needed at all. Capital goods suffer during booms simply because reallocating investments in physical assets like factories (if they can be reallocated at all) is inherently more time consuming than reallocating other forms of expenses such as reductions in staffing, cutting advertising buys, or selling liquid investment assets.

Hamiltonian theory of allocation and reallocation trends more than adequately explains the impact of busts on capital goods.

 

 

 

Austrian Business Cycle Theory Compared to Hamiltonian Business Cycle Theory

There is no quantitative method to find an objectively “correct” interest rate because different economic actors will act differently to the same interest rate – whether set by an ideal Austrian monetary system or FRB-

Alexander Hamilton’s Theory of the Business Cycle – Instead of the credit driven cycle suggested by Austrians, Hamiltonians argue the business cycle is demand driven.  In Hamiltonian theory economic boom and bust cycles are a function of changes in consumer demand for a type, or types, of goods and/or services. These cycles are usually concentrated in one or more specific sector(s) during both the upswing and downswing phases.

In the triangle of value signals, the consumer, producer, and economic environment, the consumer signals the demand they wish producers to meet.

Hamilton’s Second Law of Economics – How Efficient Processes are is a Function of a Triangle of Value Signals from the Customer, Producer, and Business Environment

Production processes are efficient if they allocate a minimal amount of resources (relative to alternative processes) to produce the most valuable (in the opinion of the customer) goods or services.

The producer interprets these customer value signals.

If the producer believes satisfying customer demand is valuable enough to the producer considering the producer’s business environment, the producer adjusts their operations and allocates resources towards meeting demand.

As mentioned in Part I, the act of satisfying particular types of demand in one sector requires the producer to establish processes and allocate resources that differ in type and kind from resources used in other sectors.  Therefore meeting types of demand creates different types of sectors:

Types of customer demand leads to the creation of different sectors because different types of consumer demand frequently require producers to design different types of processes in order satisfy different demands: The medical industry exists to satisfy medical needs; the financial sector exists to satisfy financial needs, the housing sector exists to satisfy housing needs. Each of these sectors have developed substantially different types of medical, financial, and housing processes to satisfy the demand in their respective sectors.

Because satisfying different types of desires requires different types of business processes, different sectors ultimately allocate different types of resources in their business operations that are often not needed in other sectors: Medical processes are allocated medical resources, financial processes are allocated financial resources, housing processes are allocated housing resources.

Because what consumers, producers, and the economic environment indicate is valuable is constantly changing, producers must continuously reallocate resources and fine tune business operations to align with signaled changes in demand and environment.

This reallocation of resources and process fine tuning by the producer never ceases.

Because time is required for producers to adjust to new value signals, there is always a time lag between the moment when value is signaled by the customer and the environment, and when the producer can act on this new information.

Just as trains moving at top speed cannot stop on a dime, businesses cannot reallocate on a dime during a boom or downturn because it takes time to alter the course of their planned business operations.

In mathematical terms, how quickly and efficiently reallocation is performed is a function of how liquid a producer’s assets are and how quickly a producer can redirect other resources (land, labor, material…) dedicated to old business activities to new activities. Sometimes resources in an old business action can be reallocated to new purposes.

But, usually, at least some resources cannot be reallocated because they are not recoverable from the old business action.  For instance, salaries paid to workers that suddenly obsolete software cannot be recovered to produce up to date software.

When a sector booms because of increasing demand, producers in that sector reallocate more and more resources to activities that satisfy this increasingly valuable demand.

This sector momentum naturally produces a reinforcement cascade through the rest of the economic system during rapid expansion.  This cascade becomes self-reinforcing for downstream businesses that indirectly or directly support the boom sector:  Sectors – such as raw material suppliers, financial services, marketing, staffing agencies, etc… – that are downstream or complementary to the producers in boom sectors also devote more of their resources and operations towards supporting the boom sector.

The more demand there is and the more resources are allocated to the boom sector, the greater the influence this sector has over national economic performance.

Sector momentum also naturally cascades throughout the economy when previously booming sectors turn to bust.

Downturns occur whenever demand for a good or service, no matter the reason for decline, reaches diminishing utility to the consumer. As utility is reached, demand falls below what producers projected demand would be. When demand misses expectations, producers must decide how to reallocate resources, if resources should be sold off, or if the producer can remain in business.

To Hamiltonians, economic downturns are inherently unavoidable. Over time, demand projections must consistently overshoot or undershoot because there are too many random and non-quantifiable factors for the producer to know in advance when and exactly to what degree a booming sector will see demand taper off.

Indeed, economic value itself is inherently non-quantifiable.

Because projections almost always miss their targets (and when projections are forecasted exactly it is due to a fortunate statistical accident that is not repeated in future projections) some misallocation (malinvestment) of resources is inevitable.

Especially when a bust starts.

 

Economic recovery happens, and the boom cycle reestablishes itself, when a new demand emerges that is valuable for producer’s to serve.

Growth in Capitalistic economies is ultimately superior to Socialist economies because producers in Capitalism are ultimately reflecting the true desires signaled by the customer. Because customer desires are best reflected in Capitalism, Capitalistic systems ultimately enjoy lasting benefits in processes after economic boom and bust cycles have ended. The internet bubble and the industrial expansion of the 1920s all had positive impacts that long survived their respective crashes.

We note here that our theory holding that demand is the true driver controlling boom & bust resembles Schumpeter’s theory that technological innovation drives market cycles. We generalize Schumpeter’s point to argue that demand of any kind – whether driven by demand for technology, cultural preferences, or any other customer motivation – is the key explanatory factor.

The traditional Austrian counter to Schumpeter is to argue fractional reserve banking causes boom and bust because central banks hold interest rates at artificially low levels. These low interest rates then encourage malinvestment in technological innovation, such as malinvestment in the green energy sector.

The Austrian argument against Schumpeter is weak because low interest rates are not by themselves sufficient to determine what specific technology investors decide to malinvest in. The number of possible investments in technology are essentially infinite, but not all of these possibilities attract malinvestment when interest rates are excessively low.

In the case of green energy malinvestment, Austrian theory does not explain why the green energy sector was favored over traditional energy sectors. The easy credit directed towards green energy would have been just as easily directed towards more profitable oil and gas companies.

Hamiltonian theory explains why.  In Hamiltonian Capitalism investor actions are primarily explained by demand.

From a Hamiltonian viewpoint (as well as Schumpeter’s), malinvestment in green energy is the result of Liberal governments distorting normal consumer demand for energy towards politically favored green energy. Under normal market signalling conditions, “green” energy would not have enjoyed so much investment because that sector has not technologically matured to the point where it can substitute for classic energy industries.

Progressives substituting their perception of value for the customer’s normal preferences is the real culprit, not fractional reserve banking.

 

The Limits of Austrian Market Cycle Theory

What Austrians have misidentified as a flaw in fractional reserve banking is actually a side effect of Progressive economic policy.

Interest rates have been kept artificially low because economic growth across the West has been artificially suppressed by Progressive economics. Progressive policy, and any kind of Socialist economics, depresses economic growth because the network of value signalling between the consumer, producer, and economic environment is distorted by Leftist interference in the economy – usually by Liberals substituting their own subjective value preferences for the natural preferences of the consumer.

To compensate for lower growth, Progressive central bankers set interest rates low to make borrowing cheaper for business operations. This strategy reaches diminishing returns because low interest rates cannot compensate for the distortion of consumer demand signals.

Under Capitalism, interest rates would be less politicized (and therefore higher) because economic growth would be consistently higher. Hence, there would be no need for a gold standard linked to an Austrian monetary system in order to hold interest rates at traditionally healthier levels.

 

Application of Hamiltonian and Austrian Business Cycle Theories to Economic History

The two historical events for this demonstration are the 2000 tech bubble and the 2008 economic crisis.  These two examples will highlight how Hamiltonian theory provides superior analysis over Austrian.

First the 2000 tech bubble.

From a Hamiltonian standpoint the tech boom and bust is excellent proof the business cycle is primarily demand driven, not monetary driven (though money conditions are a factor).

The 1990s revolution in computing power sparked a dramatic increase in customer demand signals for computer technology from individual, private businesses, and government.

Technology companies that directly served consumers of computer technology reacted to customer demand signals by aligning their resources, employees, inventory, capacity, and operations to satisfy booming demand.

The effort by these leading technology companies to satisfy demand caused a reinforcement cascade to external businesses downstream the production chain that supported lead businesses.  Downstream businesses that profited from technology demand included marketing businesses that advertised technology products, raw material suppliers, parts suppliers such as suppliers of microchips, energy companies, staffing firms, and any other downstream businesses the tech sector relied on to satisfy technology demand.

This reinforcement cascade created a dependency of downstream businesses on the boom enjoyed by frontline tech companies.

The act of meeting technology demand fed through the rest of the economy and caused the broad 1990s economic boom.

Towards the end of the 1990s, customer demand for technology tapered off as demand reached utility.  When utility was reached, customers no longer valued technology purchases as much as they had previously.

Technology demand plateaued and then fell.  As demand cooled off, frontline technology companies found they were over-allocated (malinvested) in resources, employees, inventory, capacity, and operations.  To align with lower demand, technology companies cut back on all of these.

Likewise, the drop in customer demand created a reinforcement cascade on downstream companies that once depended on supporting frontline technology companies.  They too cutback on resources, employees, inventory, capacity, and operations that had once supported their frontline customers.

The alignment of all these sectors and downstream sectors towards a lower equilibrium in technology demand is what led to the technology bust that caused a moderate recession in the early 2000s.

In Hamiltonian theory, the technology boom could not have been followed by anything except a bust unless the decline in technology demand could have been known exactly well in advance by technology producers.  Since perfect demand projections are impossible for producers to create, it was impossible (regardless of national credit conditions) to prevent the technology-led recession.

This is the Hamiltonian interpretation.

The standard Austrian interpretation of the technology bubble is that excessively generous monetary conditions caused companies to misread economic signals and  malinvest (overinvest) resources in the technology sector beyond what technology’s value truly was.

Even if we assume for the sake of argument that monetary policy was excessively loose, the Austrian explanation is inadequate because it runs into the objections already discussed to their theory.

Their first problem is that Austrians simultaneously reject the idea economic value is objectively quantifiable while also making objectively quantifiable judgments.  In the case of the tech bubble, Austrians claim the rate of investment in technology was “excessive”.  But claiming it was “excessive” is an objective quantitative judgment on the rate of technology investment.  This judgment contradicts the Austrian opinion that economic value is subjective.

By what right, then, can Austrians claim to know whether any company invested too much or too little in technology in the 1990s?  Some companies saved themselves from obsolescence by updating their operations with computers.  For them, the crash that followed was still worth their money.

They cannot logically claim economic value is subjective while at the same time making objective judgements about investment decisions.  But Austrians cannot help themselves because their internal logic forces them to make points contradictory to their own beliefs.

Second, the relevant Austrian praxeology statements are logically incomplete because they cannot explain why this artificial excess of credit was spent on technology speculation instead of speculation on some other good or service.

The same FRB generated stimulus that was used in technology speculation (both on the consumer end and producer’s) might also have been used for speculation on typewriter companies.

Why did computers receive so much speculative money while typewriter companies saw rapid declines in business?

The answer is simply that computer technology attracted great customer demand because it was seen as more valuable than typewriters for all sorts of reasons, most of them logical reasons like greater efficiency, faster productivity, etc.,

Only demand explains why speculative money – which could have been used for many other non-computer speculations – and the general cluster of errors that led to bust was drawn like a magnet to the computer industry specifically.

Austrian explanations can only mention the excess credit was available for speculative mania, not why a particular mania was chosen.

At least, not without referring to demand.

But Austrians cannot refer to demand’s true importance in their business cycle theory because demand is the result of countless factors that often have nothing to do with monetary policy.  Demand is influenced by everything from international trade, cultural preferences, natural disasters, and on into a basically limitless set of factors.

Moreover, demand cannot be projected exactly in enough in advance for overallocation to be avoided by producers, regardless of monetary policy.

Monetary policy can certainly influence demand up to a point, but it is only one variable of many other non-monetary variables that create total demand.

For Austrian theory to be correct, monetary policy must be the only relevant variable.  Demand driven cycles means monetary policy is only one of many.

Then there is the 2008 crash.

If demand in technology was arguably good, the demand cycle that led to the 2008 crash proves demand can be generated for bad reasons.

There were two demand-based factors that led to the 2008 crash.

One was the government encouraged home loans to underqualified home applicants, mostly justified to increase minority home ownership.

The second demand factor was banking demand for derivatives; a demand that was widespread for reasons largely unrelated to the government’s home ownership initiative.

By itself, the home building bubble had enough impact on downstream industries to send the rest of the economy into a moderate recession when it popped.

What turned it into a catastrophe was that when the home bubble began to deflate it set off a collapse in the derivatives markets.

At the time toxic derivative assets were stockpiled by banks.  The reason banks had so much demand for derivatives was because they were not subject to clear accounting rules of ownership.  Because no one knew for sure who owned what amount of derivatives, banks were attracted to the idea of using derivatives as extra leverage because they thought they could not be held to pay up on derivative losses.  In effect, the lack of accounting oversight masked the true risk of buying derivatives.

The problem with creating derivatives out of thin air came when the housing market deflated the derivatives market.

When derivative losses were called in the banking system froze up because no bank was sure whether they were legally accountable for the hundreds of billions (possibly trillions) of derivative losses due to lack of accounting regulations.

The problem the 2008 crash poses to Austrian theory is that the collapse was the result of a lack of government accounting regulations, not excess FRB credit.  If accounting regulators had established firm rules for derivative ownership the risk of derivatives could have been accounted for more easily.  Or, even better, derivatives as a financial asset could have been banned completely.

In effect, financial companies were acting somewhat like the money system had been privatized in an Austrian banking proposal because they were allowed to create their own derivative assets that were not regulated sufficiently by government.

If Austrians had their way, eliminated government oversight (by eliminating government itself), and privatized the banking system, the banks would use the lack of accounting oversight to create financial assets that would mask risk just like derivatives did.

The 2008 crash is really an example of not enough government action.  The Austrian fantasy that a completely private banking system absent government control would be more honest than FRB would not have prevented the 2008 crash.

 

The Policy Implications of Hamiltonian Business Cycle Theory

For Capitalists, Hamiltonian analysis brings important implications for policy.

If the government cannot eliminate bust cycles for the reasons already discussed, then government policy should follow a strategy that takes advantage of compound interest.  Just as an individual investment portfolio does not need to go up every year for compound interest to greatly increase the portfolio’s value over time, neither does government have to worry about the inevitable economic downturn.

The demand driven business cycle is an inherently self-correcting system; after a bust, malinvestment needs to be swept away so that producer assets can take advantage of the next demand-driven boom.

Intervening in the market in the hopeless task of “preventing” a bust often causes more damage than it prevents because propping up industries during a downturn gets in the way of reallocation of resources during the upswing.  In general, Darwinian “clearing of unfit businesses” makes the survivors that much better positioned to take advantage of boom times.

On the other hand, a severe enough downturn may clear out fit businesses.  There is no way for a government to know which businesses should be eliminated or kept because there is no objective way to know.

As far as this concerns monetary and stimulus policy, a general guiding rule should be that the government takes no action during a slight contraction, some small FRB and supply side stimulus during an average recession, and more aggressive monetary loosening and supply side stimulus during a severe recession or depression.

But these are temporary measures, and should be calibrated with the idea that too much government intervention in a downturn will crowd out investment that will be needed to create a boom.

Long term policy should be solidly environmental, not interventionist.

Since economic growth usually lasts longer than recessions, the government’s role should be to establish a sound business environment for the long-term and trust individual private sector actors to compensate for any contractions with solid GDP growth.

What makes a sound business environment is similar to what makes a sound investment portfolio – diversification.

Economies that are over-reliant on the growth of a single or few sectors (such as resource and agriculture dependent Brazil) are often victims of severe recessions when demand falls because there are few alternative sectors that pick up the slack for the nation.

Diversified economies like diversified portfolios, however, usually have multiple sectors taking serving numerous demands during booms.  They also take advantage of a broader array of national resources because diverse sectors use different types of resources to satisfy different types of demand.

If demand cannot be projected in advance, it is wiser to have an economy that is capable of supporting satisfying multiple types of demand because the odds that all types of demand will crash at the same time are reduced.  There is also a better chance of a diversified economy taking advantage of the new boom as soon as it emerges because diversified sectors have a better chance of having operations and resources of satisfying the emerging demand.