growth theory

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The Trouble with Words

Words are not ideas.  They are our means to capture ideas and make them tangible.  The problem is that words are a porous net that inevitably lets some accuracy slip away, but sometimes captures irrelevant detail that shines brightly in the moment and then dulls in the light of later thought.

Trying to define something so a discussion can follow without ambiguity in meaning sliding in and muddying things.  Slippery isn’t it?

How about this:

“I sometimes wish we could take the energy expended on these antimacassar hand-me-down “rules” and apply it to working out a way to use awkwardly broad words like inclusion, equity, liberty and racism more clearly. The ever-evolving meanings of these words has a way of creating genuine misunderstandings — try defining “neoliberalism” — to the point of actually impeding communication.”

That’s John McWhorter in the New York Times a couple of days ago.  He teaches linguistics.  

Try defining “neoliberalism”?

He’s been chatting to much with his fellow academics in the economics department.  They are the last people to ask.  Neoliberalism is easy to define.  It’s just that its definition keeps offending people who want to be neoliberal without having the recent taint associated with it rub off on them.  Or, at least that’s my opinion. 

And when I say neoliberal is easy to define I must remind you that it is a term used most often in discussions about the political-economy of the past forty to fifty years.  It is Reaganism.  It is Thatcherism.  It is Friedman.  It is Hayek.  It is all of the above and the various hangers-on who sought to destroy, or at least denigrate, anything social.  After all, as we have been reminded incessantly, social is one step away from tyranny.  I think “serfdom” is a word used somewhere to help us all understand the perils of social.

Academics, of course, love specificity.  They, like all technocrats, live in a world of precision bordering on the absurd.  They love argument over the finest of differences.   Whole careers can be made or destroyed by the finer parsing of something that previously had been commonplace, but imprecise.  

I am being harsh.  The problem is that technocrats adore the constant division of knowledge into ever smaller nooks and crannies.  They burrow into ever smaller divides and make themselves at home by substituting depth for breadth.  Anything that doesn’t fit within their enclave is tossed overboard presumably to land in someone else’s.  

And yet …

Economists are really terrible at definitions.  What, for instance is “labor”?  You might find it odd for something as central as labor — central that is to economic theory-making — could be so ill defined.

What, exactly is it?

All you have to do to understand the importance of this problem of definition is to spend some time loitering about in the abundance of literature concerning growth.

Theories of growth are central to the discipline of economics.  From the general perspective, having our technocrats come up with a good theory of growth, one that fits history and helps us navigate how to approach the future, seems to be a crucial element of the social value of economics.  It is certainly something that has exercised many of the best economists through the years.  From the earliest to the most recent ideas all sorts of reasons have been given for the explosion of activity that accumulated as growth since sometime a couple of hundred years ago.

And at the heart of most of those ideas is something called labor.

What is it?

Well, we are told, it sits alongside some other thing called “capital” as a primary factor in propelling us ever upward in our accumulation.  I wonder what economists mean by these two words.  Exactly.  They pride themselves in the elegance of their logic and mathematics.  They love expressing themselves in various formulaic combinations of quantities and so on.  But they insist on using words like labor to define those quantities.  

What, exactly, is a quantity of labor?

Instead of stopping and drilling into what this might be, we are asked to glide past and watch the virtuoso manipulation of it in various theoretical discussions of growth.

It’s as if fog can be cleared by representing it in a formula.  It can get a bit tiring looking through the murkiness all the while being told that things are crystal clear.  

I give Solow credit for being honest though.  Using imprecise terms will always produce unexplained or vague results.  In his case it produced a residual in his calculations that someone else called  a measure of our ignorance.  Others subsequently slapped a professional sounding name on this ignorance and called it “Total Factor Productivity” as if giving it a name made it somehow more precise.  

This measure of ignorance is really simply the way in which analysis, no matter how clever it looks, can be misleading when it is rooted in imprecision.  Not that it is avoidable.  Labor will always be elusive.  It is a melange of characteristics each of which has more or less importance depending on the objective of the analysis.  Is it skill?  Technique?  Energy?  Effort?  Simply a group of people?  A workforce?  The list goes on.  

It’s all of the above.  Which is why absurdities like total factor productivity exist to mask the abundance of choice in its definition.  

The point being, I suppose, that economists are doomed to exist in a world lacking precision.  They seek to explain certain social activity and its outcomes by using a toolkit that hides their roots in the vagueness that all social activity begins with.  Our language.  No matter how hard we try we are stuck with words like labor that might appear to have clarity at any particular moment, but which slide into the shadows when pressed into service inside the workings of mathematical manipulation.  The technique demands accuracy that language cannot provide.

Isn’t that the reason why economists slid into mathematics in the first place?  To avoid the sloppiness of language?  And yet, in order to stay connected with their basic material they had to retain its essential vagueness.  Capital and labor.  Two horribly imprecise concepts whenever you try to pin them down.  Wonderful at a high level.  Awful at any level of detail.  Hence residuals.

Which is why I get so annoyed when critics argue that we ought not discuss neoliberalism because it lacks definition.  Nonsense.  It has as much precision as labor or capital.  If not more.  Economics exists, like it or not, deep in the world of language rather than within the purity of mathematics.  Its roots are social as much as physical.  Trying to ignore that is a mistake.  And one constant downside of existing in a social domain is that words and communication dominate, and infect, our analytical capacity.  

The pretense of economics is that it has managed, somehow, to remove itself into a more precise world where its various techniques have a rigor lacking in language.  Which is a doomed enterprise.  It hasn’t.  Solow’s residual bears witness to that failure.  So while economists might expound on topics such as growth, and they might imagine they have mastered the details of its workings, they haven’t.  

Their conversation continues.  In words.

Meanwhile, I think neoliberalism is a fine and mightily accurate concept.

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Dark Matter

The mysteries of growth elude us.

That’s the best conclusion to draw from reading Dietrich Vollrath’s book “Fully Grown”.  This is unfair to Vollrath whose thesis is simply that recent slower growth can be explained by taking a look at demographics.  Societies with a large elderly population as a percentage of their total are destined to grow more slowly.  All the huffing and puffing of anxious policy makers to encourage investment, savings, or any other conventional spur to growth won’t work.  That aging population is a deadweight that no amount of other effort can overcome.

Vollrath is very thorough in digging through every nook and cranny of what might increase or decrease growth rates.  He discusses all the usual topics.  Can we blame taxation or regulation?  Perhaps, but they’re not significant enough to explain what’s going on.  Baumol gets a look in and, yes, the great switch to services and away from manufacturing, is putting a brake on growth.  But it isn’t the biggest brake.  Not by far.  How about our overly concentrated industrial sectors: is our obsession with oligopoly slowing things down?  Of course it is.  Those corporate “moats” to create rents for the benefit of greedy shareholders and executives are diverting energy away from growth.  But that too is insufficient an explanation for what’s happening.  

There’s no point in reprising the entire book here.  Go read it yourself.

Here, though is the summary:  between 1950 and 2000 average annual growth was roughly 2.25%.  Between 2000 and 2016 that rate of growth dropped to 1.00% per annum.  Fully 1.00% of that 1.25% decline can be attributed to two big causes:  0.80% to the effects of smaller families and aging — aka “demographics” — and 0.20% to the switch to being a service economy.  These changes are called “successes” by Vollrath.  They are signs of society’s arrival at a new era of social satisfaction and success.  We have so improved our manufacturing capability that it chews up less of our resources, so even fairly major improvements in future productivity will fail to move the growth needle much.  Our prosperity has delivered opportunity also.  Lifestyles have adapted to the cornucopia.  We have smaller families.  We make different career choices.  We live longer.  The impact of this host of newly available options has altered the demographic framework within which economic activity takes place.  These are all “good things”.  They are signs of society reconstructing itself and settling into a comfortable, and different, set of arrangements.  The days of blistering growth are gone.  The rush for wealth is past.  Now it’s a question of valuing and enjoying the fruits of all that hard work.

Well, that’s the story Vollrath tells.

He also points to one or two failures:  The other 0.25% of the decline in per annum growth can be attributed to changes in the structure of the economy.  It has become too rigid.  There is less churn both of workers and businesses.  The Schumpeterian engine is sputtering.  The slowing churn means that we are not re-allocating our resources towards higher productivity activity as effectively as we once did.  To some degree that’s because of those moats businesses like to build to generate extra profits.  And to some degree it is because we have lost the social mobility that  provided a boost to the growth engine in the early postwar years.  

That’s it.  That’s the story.

Underlying it though, and what intrigues me most, is the way in which economists have been slow to adapt to the unfolding drama.

Vollrath sweeps all the demographic factors under the heading of “human capital” and then, in his chapter 6 he moves on as follows …

“Having accounted for the role of human capital, we can now turn back to the other main source of growth slowdown, residual growth.”  

He then says we don’t actually know what this “residual” is.  There is, he says, no formal definition of it, so it remains, as Moses Abramovitz called it in 1955, a measure of our ignorance.

Naturally, since 1955 economists have worked assiduously to give explanations of what this residual is.  They have attempted to reduce our ignorance.  But, by and large, they have failed.  For Vollrath in 2020 to say that we have no formal definition of the residual is quite an indictment of the effort so far.  We remain remarkably ignorant after almost seventy years of work.

Why?

The problem is that as we follow in the footsteps of Solow and Swann, the twin originators of modern growth theory, we remain attached to their basic format.  They were being loyal to the tradition that the key factors contributing to growth were the same “labor” and “capital” that the profession has always used.  Never mind that neither of those two are well articulated.  What, exactly, is “labor”?  Is it the energy consumed in production?  Is it the skill of a worker?  Is it the time spent?  Is it all of those?  Or some combination?  Labor is never specified as tightly as economists love to claim all their formal work specifies the logical relationships in their modeling.  The elegance and logical completeness of their math is betrayed by the sloppiness of their definition of — or, rather, lack of definition of — their inputs.  The same can be said of “capital”.  So, when the work begins with a foggy duo of inputs it is hardly surprising that, no matter how impressive the subsequent math, out pops a very large and embarrassing “residual”.  

The problem with our ignorance is not the skill with which economists can manipulate and extend the math.  It is in our understanding or what, exactly, the factors of production are.  

This is why the ugly term “human capital” emerged.  As noted above Vollrath had to resort to using it.  It seems to be a grab bag of stuff that people do and learn during their lives.  Years of education, experience, various sorts of knowledge — however acquired — are all scooped up and mixed together in a fuzzy and imprecise melange that ought to embarrass a profession proud of its precision.  All we know is that it seems to be pretty important.  As are the various skills used to mix that melange with the machinery and other forms of fixed capital that we deploy in production.  Mixing human and fixed capital is also a skill  — non-economists call it organization or coordination — that is not reflected anywhere in the traditional production function.  In other words, there seems to be little space for inserting actual production into the factors deployed to estimate growth.  So we remain ignorant and stuck with our antique duo of labor and capital.  Whatever they are.

This ignorance is, of course, also a residual of the profession’s making.  It is stuck in the past.  Stubbornly stuck way up what a biologist would call a fitness peak, it has long lost the ability to reconstruct new versions of models to attack its key problems.  And, surely, figuring out why growth happens and at what pace, is a central problem for economics to solve.  But stuck as it is with its antiquated inputs its struggles on by attaching ever more elliptical and abstract circles to its original ignorance in a valiant attempt to rise higher in its understanding.

All science has opportunities to alter.  Observations arise that appear to negate or challenge an older idea.  So new ideas emerge to accommodate the science to the observation.  Economics, though, has avoided exploiting such moments.  Hence its antique nature.  We could, for instance, have used the Coase query in the 1930’s to build the existence of the firm as a centralized factor of coordination into our explanations of the economy.  But that appeared to violate the prior notion that markets were both perfect and unsurpassed at coordination.  So, rather than rebuild, economics shunted the firm into a side track under the rubric of “transaction costs” and forgot about it.  The side track was even given an imposing name — the New Institutional Economics. Later generations simply assumed the challenge had been met and that transaction costs explained the presence of firms so they could get on with their work oblivious to the gaping hole that business coordination implies in their perfect marketplaces.  Likewise, the discovery of the Solow residual was an opportunity to re-evaluate what the proper factors were in growth theory.  But a discipline so path dependent on the use of labor and capital was unable to re-invent itself.  Like transaction costs the residual was given a name that made it sound thought-through and vaguely academic — “total factor productivity” sounds like an imposing concept rather than a bucket of slop — and so we remain ignorant, but aligned with our roots.  

As an aside, one consequence if the original Solow model is that, eventually, capital will not contribute to growth at all.  Why?  Because of the depreciation of old capital.  Some time in the future all new capital investment will be consumed by replacing the older stuff.  It will, on the margin, have zero growth effect.  This ought to focus minds.  If capital is then off the table, and the residual remains opaque, economists are reduced to relying on labor as an explanation of growth.  And that is hardly new.  I believe it was Adam Smith who said: “The most decisive mark of prosperity of any country is the increase of the number of its inhabitants.”  Apparently what was correct in 1776 will be the revelation of theory in the near future.  Have we not learned anything since?

I suppose it is inappropriate to go on.  Nothing will change.  Solow, I think was sensible enough to realize the mess his residual was implying.  He probably thought it would disappear after suitable subsequent research.  But all that research has done is to explore what might be in the bucket of slop, but it hasn’t replaced it with anything resembling the sort of crisp and elegant definitions that economics like to present to the public as being part of its modus operandi.  

The effort goes on though.  Perhaps something will emerge.  Our libraries groan under the weight of volumes dedicated to papers analyzing various growth models.  All sorts of  potential factors get discussed: culture is a recurring theme.  Education is another.  Energy and information pop up now and again.  The list of possible replacements for labor and capital is long.  Heck, even technology made it into the mainstream, not as something that drops to earth from the skies — in its “exogenous” form — but as something that appears within the system by way of innovation — in its “endogenous” form.  The words themselves imbue the concepts with gravity.  Who knew innovation was a thing?  Who knew it was part of the competitive business landscape?  Critics like myself ought shut up when confronted with such sparkling insights.  Nobel prizes have been dished out for the insight that business innovates in order to get a leg up in a competitive stetting.  No. Seriously, who knew that innovation might be taking place within an economy?  And not, presumably, being transported here from Mars.  

I know.  I am being snarky.  Rightly so.  I felt bad for Vollrath in his chapter 6 as he explained why economists use the residual as an actual thing instead of an admission of ignorance.  You would think that after seven decades or so of hard work he wouldn’t have to.

As a footnote: in 2012 Ignacio Palacios-Huerta published a collection of essays written by leading economists predicting the future.  Solow was a contributor.  His essay was titled “Stray Thoughts on How It Might Go”.  It is a lesson in well-informed but humble speculation by someone who has mastered the concept of growth.  The extraordinary rise in prosperity during the twentieth century he mentions at the outset sets the scene well — then he ranged across a series of topics such as the environment, inequality, resource depletion, and development in other less economically developed nations, each of which might affect the replication of that growth.  As I read it I began to wonder why some of those things never made it into his formal theorizing.  He clearly thought of them as pertinent.  So where are they in growth theory?  If they are important enough to chat about in a short speculation on the next hundred years, if they have that sort of relevance, ought they not be somewhere in the models?  Maybe then the residual would shrink a bit.

For someone such as Solow to be as openly inconsistent a this, and yet feel comfortable with it, presumably because the press of staying within the tried and true lanes of theory prevents him from being truly novel, is quite depressing.  We are stuck both with his theory and with his residual.  And not a very good understanding of growth as a consequence.  

Then again, physics has “dark matter” so economics is not alone.  It’s just that dark matter sounds so much more interesting than “residual”.  

OK.  Let’s call it total factor productivity and just pretend we know what it is.

I hope nobody notices our ignorance.

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The Vollrath Debate

I am about to begin reading Dietrich Vollrath’s “Fully Grown — Why a Stagnant Economy Is a Sign of Success”

Before I embark I thought I would collect a few of my own observations to provide a framework for thinking about his thesis.

The big issues are those talked about by Baumol.  For some reason I cannot avoid looking at current discussions about the slower rate of productivity growth without thinking of Baumol.  We have moved from increasing productivity in agriculture through to doing the same in manufacturing and become used to the growth that such a journey can provide.  We have used our machines to augment and then replace our own effort.  The consequence has been monumental.  We live within immense prosperity.  The bounty of applying machinery has produced far more than we ever imagined possible.

Not only this, but the constant fear of an ever growing surplus of unemployed people has never arrived.  The journey wasn’t simple or without stress.  But it was worth it.  And the true naysayers have all been wrong.  We are better off.  

As we think about what comes next we must also recall that this is all very recent history.  Our rush into modern prosperity only began back in the late 1880s.  DeLong and others would argue that it is only since 1870 that we have truly been on this path.  In that context much of what we take as solid or traditional is actually only ephemeral and shallow rooted.  Growth as we think of it today is an artifact of very recent modernity.  We ought not take it as something permanent or lasting. 

That, in turn, ought give us pause.  Modern society and our current social arrangements might be more transient than we would wish.  Our re-shaping of traditions is still underway.  The journey is incomplete.  What does stagnation imply for the rest of the journery?

That this modern cornucopia has come without costs is, of course, nonsense.  Our environment is paying a heavy price.  There might be limits to what we can do.  Our issue is that we are addicted to prosperity.  Advocates of slowing down are unable to explain how we de-escalate our progress without sacrificing the political progress that came along with that prosperity.  After all, without greater prosperity the perspective that history provides is that we would plunge back into authoritarian living.  Democratic freedom and expression are the products of abundance.  Rich people don’t like sharing.  Elites protect their position.  There was a reason early economists assumed wages for the majority would tend towards subsistence.  If we slow growth the tension that prosperity has reduced will return.  Power will matter even more than usual.  And the elite will prevail.  Subsistence, but at a higher level, would also return as the norm for most.

This journey has taken us through two economics sectors.  It has dumped us in the third.  That is Baumol territory.

We know how to feed ourselves in abundance.  We know how to mass produce the artifacts we enjoy.  What about service?  How do we provide services within a productivity driven framework?  By definition we prize “service” as an unproductive activity.  We cherish the one-on-one provision of those activities we cluster under the name of services.  After all “personal service” is something we aspire to experience.  How do we mass produce the personal experience in the same manner wemass produce food and physical things?  Isn’t there a basic contradiction in the very idea?

So, as we become a much more service oriented economy, Baumol suggests we should expect slowing productivity gains and thus growth.  A stagnant economy might just be the triumphant end point for our journey.

Perhaps artificial intelligence can help.  But who gets to decide that?  And are we capable of measuring its impact?  Most of our measures of growth were developed in the heyday of mass production.  They were intensely industrial in their origins and influence.  Are they appropriate for the digital age?

The same can be said for our economic institutions.  Our major business firms are all constructed along lines fit for an industrial age.  They have not been re-invented for a digital age.  One look at the so-called controversy created by work-at-home during the pandemic illustrates the gap between what is taken as “proper” organization and what is possible under a digital regime.  The organization of work, indeed even the definition of work, needs to be re-evaluated.  We have an abundance of buildings that housed industrial era activity.  Do we really need them for digital activity?

This leads us to an even larger discussion.  Society itself has been re-built to accommodate industry.  Wasn’t that the entire issue that gave rise to economics and its variants in the 1800s?    Whither society as the machines came to dominate activity?  The degradation of life in those early periods of change produced provocative counterpoints as different as Marx and Polanyi.  Where are our modern equivalents?  Social reconstruction brought with it the political changes I noted above.  Will democracy as we know it, child that it is of the industrial era, survive into the digital era?

A digital world is one of free-flowing information.  Physical boundaries are irrelevant in such a context.  Yet our boundaries appear important to us.  How do we reconcile this?  Globalization of production was to the benefit of the owners of the capital necessary in mass production.  So we are currently re-evaluating its worth in light of the effects it had within our boundaries.  We appear to be hesitant about further globalization.  Yet a digital economy must surely be global.  Information and digital experience seem impossible to prevent from flooding across borders.  So is it simply economic institutions that need too be revamped for the future.  Perhaps our political institutions do also.

This raises another important point: who gets to decide?   Do we really want to leave the reconstruction of society in the hands of those who own the machines?

Which returns me to stagnation.

Unless we find a way to maintain growth in wealth by reinventing our services, we appear doomed to slower growth and thus political tension.  In particular the perennial argument over the distribution of wealth will re-appear as the most potent driver of politics.  The owners of machines are not to be trusted in such an argument.  Perhaps that’s why they are racing to get ahead of our out-of-date political systems in the discussion over how power will be apportioned in future.

And we have already had a taste of what the rich actually feel about sharing power: the entire neoliberal reaction to the New Deal here in America tells you all you need to know.  They hate sharing.  They thus hate democracy and the redistribution it implies.

Oh, and where will economics fit in such a discussion?  After all modern economics has been purged of history and power precisely to sanitize it and make it useful in defense of the status quo as determined by the powerful.

So, I suppose, that’s what I will be looking for in Vollrath’s book.  How do we square democracy with stagnation?  Where will power reside?

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Addendum:

I have seen some people define some areas of the service economy as being “low value”.  This is an indicator of our problem.  They are “low value” in the context of our attempt to increase productivity in mass production or agriculture.  They are “low value” only in the sense that we cannot place a value on such a subjective phenomenon as the experience of watching a Shakespeare play.  We can only value it in our current methodologies in terms of measurable things like prices of entry, wages to actors, costs of production etc.  But is that a Shakespeare play’s true “value”?  This is a perennial question.  Measurability determines valuation.  The digital era elevates the immeasurable.  What does that mean for “value”?  For the economy?  For resource allocation?  For economics itself?  

We have a clue already in one of my favorite topics: total factor productivity.  That’s the black box that allows us to reconcile the traditional inputs to growth with the observed outcomes.  Information matters such more than economics takes into account.  Information that is, not in terms of messaging, but in terms of design and technique.  Information is in the way in which we get things done as well as in the way we talk about it.

Given a proper answer to this conundrum and perhaps we will not stagnate in a broader sense of “value” but only in the narrower sense of what we can measure.  It’s a computational and definitional problem. Does that matter?

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“L” is for Lumberjack

Pick up Daron Acemoglu’s outstanding textbook “Introduction to Modern Growth” and open it randomly to any page.  There before you will be a few lines of text scattered amongst a variety of mathematical equations of varying density, complexity, and inscrutability.  It really is a wonderful book and pulls together all the wisdom existing in economics concerning the causes of that most intriguing of all questions: why and how does the economy grow?

Along the way you can be exhilarated.  You can discover the font of eternality in the notion of perpetual youth. You can see the future stretch to infinite horizons.  You can mingle with your ancestors in overlapping generations.  And you can wallow in theorems, proofs, and sundry other entertaining and sometimes difficult flora and fauna of modern economics.  

Amazing stuff.

And not only exhilarating but solidly logical.  The purpose of the pages of mathematics is to extinguish sloppy thinking from mere narrative.  It is to expose the subtleties and connections that elude us in simple speech.  It surfaces those vague notions that clutter and make ambiguous what might appear to the less mathematical as acceptable explanations of the phenomena of growth.  

This is the triumph of the mathematization of economics.  No sloppy thinking is allowed.  The various models presented in Acemoglu’s book represent a complete tour through the subject.  They are a complete odyssey.  They begin with the iconic first steps of Solow, and move through everything that has followed.  The technical progress of the discipline is astonishing.  Model after model is presented and explained in a sequence that draws us through decades of intense discussion and argument.  The elegance and pure logic on display is a testimony the those decades and to the never ending quest to produce explanations for growth that suffer from none of the failings of a merely verbal exegesis of the subject.

I tip my hat to the effort.  It’s a breathtaking achievement.

Now.  

One more thing.

That “L”.

Labor?

I always thought that “L” was for lumberjack.  All these years I have been wrong.  Those amazing models are including “labor” not “lumberjacks”.  How wrong I was!

But labor it is.  

That’s clear enough.  I mean we wouldn’t want to specify what we mean by labor would we?  It might be lumberjacks.  It might also be brain surgeons.  Or gardeners.  Or machinists.  Or artists.  Or economists [no, not that one!].  Or … well just about anything.  

That doesn’t matter though.  Who needs precision?  Who needs to be clear when all that modeling logic offsets any vagueness in the thought process?  The point is to eliminate mistakes in logic.  The point to to elucidate hidden connections and threads of thought.  The fact that the very raw material being modeled is vague doesn’t matter.

Does it?

I think it does.

I wouldn’t allow such an element of vagueness to infest a story I wrote.  Not at least if I wanted to be clear.  If I wanted to hide my uncertainty, however, I might just lull the reader with an ambiguity of specification.  I might, for instance, use the word “labor” and let the reader decide whether the object being described or analyzed was a lumberjack.  Or a brain surgeon. Or a gardener.  After all they’re all the same.  No?

Anyway, it’s nice to see the humility of economists.  All that hard earned and expensive skill.  Especially the mathematics.  And they’re all so humble that they don’t mind being confused with lumberjacks.  Not at all.  They’re all the same.  No?  All labor is the same.  It must be.  Or at least it must be to economists.

With a simple all-inclusive “L” we can substitute anyone for anyone else.  We could, for example, hear a lumberjack opine on a real business cycles or watch an economist climb that one hundred foot red oak in my backyard and prune away all those dead branches.  Labor is all the same.  No?  A lumberjack would laugh at the absurdity of it all.  Why don’t economists?

No amount of mathematical wizardry can eliminate the fog if the objects being modeled are allowed to remain foggy.  Modeling fog, however sophisticated the mathematics, still produces fog.

Allow me to introduce you to Total Factor Productivity.  Some people call it a measure of our ignorance.  I prefer to think of it as a quantity of fog.

Q.E.D.

As they say.

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Say it Ain’t So

I am nothing if not annoying.  Allow me to elaborate.

Let’s be basic.

I mean really really basic.

Our model world initially consists of two people, Adam and Eve.  I know, it’s been done before.  But we are economists.  What are we interested in?  What problems that Adam and Eve face do we want to study?

Well, they need energy.  Human bodies, like all ordered structures, need flows of energy to maintain that structure.  The Second Law of Thermodynamics is the damndest thing.  It gets in the way.  But that’s life.  So what do Adam and Eve do?  They go look for energy, which in our speak we call food.  They avert death by searching for, finding, and consuming food.  Problem solved.

What do we make of this?

Demand — the need for a supply of energy — precedes its supply.  And that the search for, location of and ultimately the consumption of that energy requires more energy.  We are stuck in a loop.  We can summarize the search and location parts of the process as work.  And work requires its own source of energy.  

One thing leads to another as they say.  But cut to its absolute minimalist core, work is about sources of energy.  It is the application of energy to a task, which in a primitive sense is simply survival.  And the sum of all the work being done is the sum of all the energy gathered and processed to satisfy the demand for — energy.

I know.  This is absurd reduction.  But that’s where we need to go in order to clarify what an economy actually is.  It is the sum of work being done.  It is an energy flow.

In the fullness of time, of course, through serendipity and ingenuity, humans managed to supply themselves with a surplus.  That’s where life got complicated.  That led to conflict over who kept and/or consumed the surplus.  Sometimes it was some thug who managed to bully him or herself to the top and demanded tribute.  Other times it as a cultist who persuaded the gullible that they had contact with spirits and demanded tribute in order to translate the divine.  And yet other times it was simply a militarist thug who stole by dint of raw power.  

And that’s the way it was for millennia.  More than millennia.

Serendipity and ingenuity, though, are relentless.  The surplus grew.  More humans survived.  Not only did they survive, but they, through their imaginations, created a new category of requirement: they sought psychic satisfaction beyond mere survival.  This, too, requires energy.  It requires work.  Humans apparently like acquiring stuff, essential or not.  History does not lie — we do.  Even if it’s a trinket buried alongside an ancient inhabitant of some distant corner, it seems we have always liked to amass material things, it isn’t simply a capitalist plot.  And this requires work.  It requires energy.

One thing leads to another and we arrive on the cusp of the industrial revolution and the arrival of machines.

Machines, that is, on a grand scale, specifically designed as engines of work that consume energy and produce stuff at a scale hitherto unattainable.  Work and energy.  At scale.

It’s right about here that economists appear on the scene.  They are fascinated by the abundance of stuff and the vagaries of its appearance.  Sometimes there are over-supplies.  Sometimes there are under-supplies.  How come?  They get obsessed over irrelevancies like the value of all this stuff.  What is “value”?  No one cares except economists.  They study the ebb and flow of stuff and start to wonder how it all comes into being.  

And they frame their conversation within the boundaries of what matters to them.  Not in any fundamental sense, but simply in the context of their lived experience.  

They worry not about work, but about labor.  Labor being a slippery concept, they introduce at the inception of their discussion a vague notion.  They mix the skill humans bring to work with the effort — the energy potential — that they bring.  So at the very outset skill and energy co-mingle into one blurry notion.  

They concern themselves with the way in which machines can either augment or displace labor.  So machines, being seen as a substitute for the vague concept of labor, also become vague.  What is a machine?  How do we describe it?  Is it a tool?  Is it an artifice of prior labor?  Is it a consequence of surplus?  Is it a cause of surplus?  Is it property?  The sideline discussion of value that preoccupied them at the time led them into various dead-ends, giving machines a definition was one such dead end.  Ultimately the machine emerged as “capital” uneasily conflated with the cash needed to purchase or call it into being.  

So the apparent need to pin down the source of value, a philosophical sideline that neither Adam nor Eve would have found interesting, led economists to label the ingredients of the process of work as labor and capital.  Energy and skill disappear.  The design of machines is treated as uninteresting or unappealing.  The flow of energy is subsumed into discussions about the various combinations of labor and capital, neither of which has any specificity, but they do match the political conversation surrounding the social effects of industrial growth.  Vague concepts are tolerated because the underlying economic reality of flows of energy directed by design towards the completion of work is not the subject for discussion.  Political economy is a discussion of employment, class conflict, and ultimately the question of who creates and owns “value” and “surplus”.

One thing leads to another and economics then attempts to enter a more scientific age by becoming more mathematical.  It carries forward the same discussion. And, crucially, it carries forward the same vague categories as its key ingredients.

So, it cannot be a shock or surprise, that when, at long last economists decide to study the growth of economies and attempt to develop models to explain that growth, their efforts flounder.  The most well known models suddenly expose great gaps in knowledge.  Those gaps, the unexplained residuals of the models, lay bare the accumulated ignorance that economists now must grapple with.  Indeed the more honest amongst the modelers admit that the residuals are a measure of their ignorance.

An ignorance that stems directly from the error outlined above.

Discussions begin about other factors contributing to growth.  Information and design of machinery is introduced through then backdoor called technology.

In order to consume, work must be done.

Energy is consumed in doing work.

Energy is directed by design towards the accomplishment of work. 

Design is information.

The totality of consumption permitted by the accomplished work is the totality of an economy.

Ergo: energy and information are the proper objects of study if we want to understand the growth of an economy.  Not labor and capital both of which are muddled, unappealing, and uninteresting combinations of energy and information.  In economics-speak neither labor nor capital is homogenous.  Treating them as such leads to error.  To whit: “total factor productivity”.

I am hardly the first to say such.

“… different types of labor are paid differently depending upon the utility of the product they produce … “  

That’s Jean-Baptiste Say letting Adam Smith know that treating labor as homogenous will get you into trouble.  And, indeed it has led economics astray.

Anyone serious about re-booting economics must surely re-visit its basic concepts.  Re-hashing the 1800s just won’t do.

Ultimately, of course, this is all about what we consider to be important to measure.  Political economy concerns itself with the social and political ramifications of economic activity.  So it defines that activity in terms amenable to that conversation.  But growth theory is different.  Its terms ought to be those amenable to understanding growth.  They may be different.  Having a conversation about what those differences might be is hardly unnecessary or unappealing.

And say what you like about Say.  He was saying something sensible.  If only he had understood that demand precedes supply …

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