Economics Explained — Part IV: Loose Ends and Finishing Touches

This is the fourth installment of a long post. I may revise it as I post later parts. The whole will be published as a page, for ease of reference. In Parts I, II, and III I necessarily omitted many topics that might seem relevant to the principles of economics and their application in the real world. I address a few of those topics in this coda.

Macroeconomics

Macroeconomic aggregates (e.g., aggregate demandaggregate supply) are essentially meaningless because they represent disparate phenomena.

Consider Chuck and Debbie, who discover that, together, they can have more clothing and more food if each specializes: Chuck in the manufacture of clothing, Debbie in the farming and cultivation of foodstuffs. Through voluntary exchange and bargaining, they find a jointly satisfactory balance of production and consumption. Chuck makes enough clothing to cover himself adequately, to keep some clothing on hand for emergencies, and to trade the balance to Debbie for food. Debbie does likewise with food. Both balance their production and consumption decisions against other considerations (e.g., the desire for leisure).

Chuck and Debbie’s respective decisions and actions are microeconomic; the sum of their decisions, macroeconomic. The microeconomic picture might look like this:

• Chuck produces 10 units of clothing a week, 5 of which he trades to Debbie for 5 units of food a week, 4 of which he uses each week, and 1 of which he saves for an emergency.
• Debbie, like Chuck, uses 4 units of clothing each week and saves 1 for an emergency.
• Debbie produces 10 units of food a week, 5 of which she trades to Chuck for 5 units of clothing a week, 4 of which she consumes each week, and 1 of which she saves for an emergency.
• Chuck, like Debbie, consumes 4 units of food each week and saves 1 for an emergency.

Given the microeconomic picture, it is trivial to depict the macroeconomic situation:

• Gross weekly output = 10 units of clothing and 10 units of food
• Weekly consumption = 8 units of clothing and 8 units of food
• Weekly saving = 2 units of clothing and 2 units of food

You will note that the macroeconomic metrics add no useful information; they merely summarize the salient facts of Chuck and Debbie’s economic lives — though not the essential facts of their lives, which include (but are far from limited to) the degree of satisfaction that Chuck and Debbie derive from their consumption of food and clothing.

The customary way of getting around the aggregation problem is to sum the dollar values of microeconomic activity. But this simply masks the aggregation problem by assuming that it’s possible to add the marginal valuations (i.e., prices) of disparate products and services being bought and sold at disparate moments in time by disparate individuals and firms for disparate purposes. One might as well add two bananas to two apples and call the result four bapples.

The essential problem, as discussed in the next section, is that Chuck and Debbie derive different kinds and amounts of enjoyment from clothing and food, and that those different kinds and amounts of enjoyment cannot be summed in any meaningful way. If meaningful aggregation is impossible for Chuck and Debbie, how can it be possible for an economy that consists of millions of economic actors and an untold variety of goods and services? And how is it possible when technological change yields results like this?

In hours worked at the average wage, the 13 electronics items in 1991 would have had a “time cost” of 290.4 hours of work at the average hourly wage then of \$10.52 (or 7.25 weeks or 36.3 days). Today, the \$200 iPhone would have a “time cost” of fewer than 10 hours (9.82) of work at the average hourly wage today of \$20.35, and just one day of work, plus a few extra hours.

The piece is six years old and out of date in its details. But it’s nevertheless representative of almost all goods that have been produced since the founding of the United States, and almost all means of production.

GDP, in other words, is nothing more than what it seems to be on the surface: an estimate of the dollar value of economic output. Even at that, it’s not susceptible of quantitative modeling. (See “Macroeconomic Modeling: A Case Study” at this post.) Nor can real economic output — as opposed to government spending — be pushed upward by government spending, as I explain at length here.

GDP is certainly not a measure of “social welfare”, as most economists will admit — but for the wrong reason. They point to the “intangibles” that aren’t counted in GDP, one of which is the actual amount of happiness that each person derives not only from things counted in GDP but from the many things that aren’t counted in it (e.g., marital happiness, the love of children for parents, the malaise that prevails in times of prolonged international strife). In admitting that much, economists hint at — but fail to mention — the deeper reason that GDP doesn’t measure social welfare is that there is no such thing.

I will explain the non-existence of social welfare after tackling its running-mate: social justice.

Social Justice

This discussion covers a lot of ground. Little of it fits within my strict definition of economics — the voluntary production and exchange of goods — but it bears directly on two important byproducts of economic activity: income and wealth.

Social welfare (discussed below) is the implicit desideratum of seekers of “social justice”. Thomas Sowell has a better term for it: cosmic justice.

The seekers of cosmic justice are not content to allow individuals to accomplish what they can, given their genes, their acquired traits, their parents’ wealth (or lack of it), where they were born, when they live, and so on. Rather, those who seek cosmic justice cling to the Rawlsian notion that no one “deserves” better “luck” than anyone else. (For a critique of John Rawls’s theory of economic and social justice, see this.)

But “deserves” and “luck” (like “greed”) are emotive, value-laden terms. Those terms suggest (as they are meant to) that there is some kind of great lottery in the sky, in which each of us participates, and that some of us hold winning tickets — which equally “deserving” others might just have well held, were it not for “luck.”

This is not what happens, of course. Humankind simply is varied in its genetic composition, personality traits, accumulated wealth, geographic distribution, etc. Consider a person who is born in the United States of brilliant, wealthy parents — and who inherits their brilliance, cultivates his inheritance (genetic and financial), and goes on to live a life of accomplishment and wealth, while doing no harm and great good to others. Such a person is neither more “lucky” nor less “deserving” than anyone else. He merely is who he is, and he does what he does. There is no question of desert or luck. (I address luck in this post and those linked to therein.)

Such reasoning does not dissuade those who seek cosmic justice. Many of the seekers are found among the “80 percent”, and it is their chosen lot to envy the other “20 percent”, that is, those persons whose brains, talent, money, and/or drive yield them a disproportionate — but not undeserved — degree of fortune, fame, and power. The influential seekers of cosmic justice are to be found among the  “20 percent”. It is they who use their wealth, fame, and position to enforce cosmic justice in the service (variously) of misplaced guilt, economic ignorance, and power-lust. (Altruism — another emotive, value-laden term — does not come into play, for reasons discussed here and here.)

Some combination of misplaced guilt, economic ignorance, and power-lust motivates our law-makers. (Their self-proclaimed “compassion” is bought on the cheap, with taxpayers’ money.) They accrue power by pandering to seekers of cosmic justice and parasites who seek to gain from efforts to attain it. Thus politicians have saddled us with progressive taxation, affirmative action, and a plethora of other disincentivizing, relationship-shattering, market-distorting policies. It is supremely ironic that those policies have made most of persons (including many parasites) far worse off than they would be if government were to get out of the cosmic-justice business.

As Anthony de Jasay writes in “Risk, Value, and Externality”,

Stripped of rhetoric, an act of social justice (a) deliberately increases the relative share … of the worse-off in total income, and (b) in achieving (a) it redresses part or all of an injustice…. This implies that some people being worse off than others is an injustice and that it must be redressed. However, redress can only be effected at the expense of the better-off; but it is not evident that they have committed the injustice in the first place. Consequently, nor is it clear why the better-off should be under an obligation to redress it….

There is the view, acknowledged by de Jasay, that the better-off are better off merely because of luck. But, as he points out,

Nature never stops throwing good luck at some and bad luck at others, no sooner are [social] injustices redressed than some people are again better off than others. An economy of voluntary exchanges is inherently inegalitarian…. Striving for social justice, then, turns out to be a ceaseless combat against luck, a striving for the unattainable, sterilized economy that has built-in mechanisms … for offsetting the misdeeds of Nature.

In fact, “social justice” not only penalizes but also minimizes and ostracizes the kinds of persons who have been mainly responsible for economic (and artistic and social) progress in the Western world, namely, straight, white, heterosexual males of European origin and descent — including, notably, Ashkenzi Jews. Many members of the aforementioned group are themselves advocates of “social justice”, which is just another indication that they are among the spoiled children of capitalism who have lost sight of what got them to where they are — and it wasn’t kow-towing to lunacies like “social justice”.

SOCIAL WELFARE

Some proponents of cosmic justice appeal to the notion of social welfare (even some economists, who should know better) . Their appeal rests on two mistaken beliefs:

• There is such a thing as social welfare.
• Transferring income and wealth from the richer to the poorer enhances social welfare because redistribution helps the poorer more than it hurts the richer.

Having disposed elsewhere of the second belief, I now address the first one. I begin with a question posed by Arnold Kling:

Does the usefulness of the concept of a social welfare function stand or fall on its mathematical properties?

My answer: One can write equations until kingdom come, but no equation can make one person’s happiness cancel another person’s unhappiness.

The notion of a social welfare function arises from John Stuart Mill’s utilitarianism, which is best captured in the phrase “the greatest good for the greatest number” or, more precisely “the greatest amount of happiness altogether.”

From this facile philosophy (not Mill’s only one) grew the ludicrous idea that it might be possible to quantify each person’s happiness and, then, to arrive at an aggregate measure of total happiness for everyone (or at least everyone in England). Utilitarianism, as a philosophy, has gone the way of Communism: It is discredited but many people still cling to it, under other names.

Today’s usual name for utilitarianism is cost-benefit analysis. Governments often subject proposed projects and regulations (e.g., new highway construction, automobile safety requirements) to cost-benefit analysis. The theory of cost-benefit analysis is simple: If the expected benefits from a government project or regulation are greater than its expected costs, the project or regulation is economically justified.

Here is the problem with cost-benefit analysis — which is the problem with utilitarianism: One person’s benefit cannot be compared with another person’s cost. Suppose, for example, the City of Los Angeles were to conduct a cost-benefit analysis that “proved” the wisdom of constructing yet another freeway through the city in order to reduce the commuting time of workers who drive into the city from the suburbs. In order to construct the freeway, the city must exercise its power of eminent domain and take residential and commercial property, paying “just compensation”, of course. But “just compensation” for a forced taking cannot be “just” — not when property is being wrenched from often-unwilling “sellers” at prices they would not accept voluntarily. Not when those “sellers” (or their lessees) must face the additional financial and psychic costs of relocating their homes and businesses, of losing (in some cases) decades-old connections with friends, neighbors, customers, and suppliers.

How can a supposedly rational economist, politician, pundit, or “liberal” imagine that the benefits accruing to some persons (commuters, welfare recipients, etc.) somehow cancel the losses of other persons (taxpayers, property owners, etc.)? To take a homely example, consider A who derives pleasure from causing great pain to B (a non-masochist) by punching him in the nose. A’s pleasure cannot cancel B’s pain.

Yet, that is how cost-benefit analysis (utilitarianism) works, if not explcitly then implicitly. It is the spirit of utilitarianism (not to mention power-lust, arrogance, and ignorance) which enables politicians and bureaucrats throughout the land to impose their will upon us — to our lasting detriment.

Conclusion: Politics Trumps Economics

In sum, and despite all of the feel-good rhetoric to the contrary, the United States differs only in degree (but not in kind) from modern communism and socialism. It’s a “social democracy”, in which the demos (mob) dictates the economic (and social) order through its various political patrons. But the political patrons (including the affluent elites who play footsie with them) are in charge, make no mistake about it, and they freely demonize those segments of the demos which turn against them. They are able to do so because the franchise has been so extended (and will continue to be extended by untrammeled immigration) that they won’t run out of votes to advance their essential agenda, which is control of the social and economic affairs of all Americans.

Despite the advent of Donald Trump, and the lesson that it should have taught high-ranking politicos, most of them (regardless of party affiliation) remain wedded to the patronage system because it’s their path to power and riches.

What this all means, as I once explained to a very smart economist, is that politics trumps economics. Ignoring politics (and being ignorant of it) while trying to understand and explain economics is like ignoring the heart while trying to explain the circulatory system without which there is no life.

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Further Reflections on the Keynesian Multiplier

In “Keynesian Multiplier: Fiction vs. Fact“, I piggyback on the insights of Murray Rothbard and Steven Landsburg to show that the fiscal multiplier is fool’s gold. In addition to showing this mathematically and empirically, I address the mechanics of the multiplier:

How is it supposed to work? The initial stimulus (∆G) [an exogenous — unfunded — increase in government spending] creates income (don’t ask how), a fraction of which (b) [the marginal propensity to consume] goes to C [consumption spending]. That spending creates new income, a fraction of which goes to C. And so on. Thus the first round = ∆G, the second round = b(∆G), the third round = b(b)(∆G) , and so on. The sum of the “rounds” asymptotically approaches k(∆G) [where k is the multiplier]….

Note well, however, that the resulting ∆Y [change in real, inflation-adjusted GDP] isn’t properly an increase in Y, which is an annual rate of output; rather, it’s the cumulative increase in total output over an indefinite number and duration of ever-smaller “rounds” of consumption spending.

The cumulative effect of a sustained increase in government spending might, after several years, yield a new Y — call it Y’ = Y + ∆Y. But it would do so only if ∆G persisted for several years. To put it another way, ∆Y persists only for as long as the effects of ∆G persist. The multiplier effect disappears after the “rounds” of spending that follow ∆G have played out.

The multiplier effect is therefore (at most) temporary; it vanishes after the withdrawal of the “stimulus” (∆G). The idea is that ∆Y should be temporary because a downturn will be followed by a recovery — weak or strong, later or sooner.

Further,

the Keynesian investment/government-spending multiplier simply tells us that if ∆Y = \$5 trillion, and if b = 0.8, then it is a matter of mathematical necessity that ∆C = \$4 trillion and ∆I + ∆G = \$1 trillion. In other words, a rise in I + G of \$1 trillion doesn’t cause a rise in Y of \$5 trillion; rather, Y must rise by \$5 trillion for C to rise by \$4 trillion and I + G to rise by \$1 trillion. If there’s a causal relationship between ∆G and ∆Y, the multiplier doesn’t portray it.

And the clincher:

Taking b = 0.8, as before, the resulting value of kc is 1.25. Suppose the initial round of spending is generated by C instead of G. (I won’t bother with a story to explain it; you can easily imagine one involving underemployed factories and unemployed persons.) If ∆C = \$1 trillion, shouldn’t cumulative ∆Y = \$5 trillion? After all, there’s no essential difference between spending \$1 trillion on a government project and \$1 trillion on factory output, as long as both bursts of spending result in the employment of underemployed and unemployed resources (among other things).

But with kc = 1.25, the initial \$1 trillion burst of spending (in theory) results in additional output of only \$1.25 trillion. Where’s the other \$3.75 trillion? Nowhere. The \$5 trillion is phony. What about the \$1.25 trillion? It’s phony, too. The “consumption multiplier” of 1.25 is simply the inverse of b, where b = 0.8. In other words, Y must rise by \$1.25 trillion if C is to rise by \$1 trillion. More phony math.

The essential falsity of the multiplier can be found by consulting the equation of exchange:

In monetary economics, the equation of exchange is the relation:

MV = PQ

where, for a given period,

M is the total nominal amount of money supply in circulation on average in an economy.

V is the velocity of money, that is the average frequency with which a unit of money is spent.

P is the price level.

Q is an index of real expenditures (on newly produced goods and services).

Thus PQ is the level of nominal expenditures. This equation is a rearrangement of the definition of velocity: V = PQ/M. As such, without the introduction of any assumptions, it is a tautology. The quantity theory of money adds assumptions about the money supply, the price level, and the effect of interest rates on velocity to create a theory about the causes of inflation and the effects of monetary policy.

In earlier analysis before the wide availability of the national income and product accounts, the equation of exchange was more frequently expressed in transactions form:

MVT = PT

where,

VT is the transactions velocity of money, that is the average frequency across all transactions with which a unit of money is spent (including not just expenditures on newly produced goods and services, but also purchases of used goods, financial transactions involving money, etc.).

T is an index of the real value of aggregate transactions.

(Note the careful — but easily overlooked — qualification that quantities are for “a given period”, as I point out in the first block-quoted passage. One cannot simply add imaginary increases in real output over an unspecified span of time to an annual rate of output and obtain a new, annual rate of output.)

If the values for M, V, P, and Q are annual rates or averages, then MV = PQ = Y, the last of which I am using here to represent real GDP.

If the central government “prints” money and spends it on things (i.e., engages in deficit spending financed by the Federal Reserve’s open-market operations), then ∆G (the addition to the rate of G) = ∆M (the average annual increase in the money supply). What happens as a result of ∆M depends on the actual relationships between M and V, P, and Q. They are complex relationships, and they vary constantly with the state of economic activity and consumers’ and producers’ expectations. Even a die-hard Keynesian would admit as much.

If new economic activity (Y) is relatively insensitive to  ∆G, as it is for the many reasons detailed here, it is equally insensitive to ∆M. For one thing — one very important thing — ∆M may be absorbed almost entirely by an increase in VT without a concomitant increase in Q. That is to say, ∆G necessarily implies (in the short run) an increase in transactions velocity (VT) and it is most likely to be spent on resources that are already employed (i.e, either on things that were already being produced or by displacing private purchases of things that were already being produced).

The equality MV = PQ long predates Keynes’s General Theory, in which he introduces the multiplier, and so it was well known to Keynes. As it happens, the equality is at the heart of his multiplier:

The state of the economy, according to Keynes, is determined by four parameters: the money supply, the demand functions for consumption (or equivalently for saving) and for liquidity, and the schedule of the marginal efficiency of capital determined by ‘the existing quantity of equipment’ and ‘the state of long-term expectation’ (p 246).

Adjusting the money supply is the domain of monetary policy. The effect of a change in the quantity of money is considered at p. 298. The change is effected in the first place in money units. According to Keynes’s account on p. 295, wages will not change if there is any unemployment, with the result that the money supply will change to the same extent in wage units.

We can then analyse its effect from the diagram [reproduced below], in which we see that an increase in M̂ shifts r̂ to the left, pushing Î upwards and leading to an increase in total income (and employment) whose size depends on the gradients of all 3 demand functions. If we look at the change in income as a function of the upwards shift of the schedule of the marginal efficiency of capital (blue curve), we see that as the level of investment is increased by one unit, the income must adjust so that the level of saving (red curve) is one unit greater, and hence the increase in income must be 1/S'(Y) units, i.e. k units. This is the explanation of Keynes’s multiplier.

Here’s the diagram:

If that is the explanation of Keynes’s multiplier, it is even more backward than the usual explanation that I shredded earlier. All it says is that if the real money supply (M̂) is increased (i.e., not translated into higher prices) due to an exogenous increase in government spending, the real interest rate (r̂) decreases. And if the decrease in the real interest rate leads to an increase in investment, Y must rise by enough to preserve the theoretical relationship between Y and saving (S) and investment (I).

In this case, Keynes depicts the multiplier as the effect of an increase in I resulting from an increase in M, which is really an increase in G (∆G) under the condition of less than full employment (whatever that is). The increase in I is made possible by the decrease in the real rate of interest. That’s odd, because the popular view of the multiplier is that it is the rise in real GDP that is directly attributable to a rise in government spending. Will the real multiplier please stand up?

Regardless, the relationship between the increase in I and the increase in Y is no less tautologous than it is in the usual explanation of the multiplier.Simply put, the increase in I is the increase that must result if Y increases, given an ex-post relationship between I and Y. There is no causality, except in the imagination of the proponent of increased government spending.

We are back where we started, with a mythical multiplier that explains nothing.

Unorthodox Economics: 5. Economic Progress, Microeconomics, and Microeconomics

This is the fifth entry in what I hope will become a book-length series of posts. That result, if it comes to pass, will amount to an unorthodox economics textbook. Here are the chapters that have been posted to date:

1. What Is Economics?
2. Pitfalls
3. What Is Scientific about Economics?
4. A Parable of Political Economy
5. Economic Progress, Microeconomics, and Macroeconomics

What is economic progress? It is usually measured as an increase in gross domestic product (GDP) or, better yet, per-capita GDP. But such measures say nothing about the economic status or progress of particular economic units. In fact, the economic progress of some economic units will be accompanied by the economic regress of others. GDP captures the net monetary effect of those gains and losses. And if the net effect is positive, the nation under study is said to have made economic progress. But that puts the cart of aggregate measures (macroeconomics) before the horse of underlying activity (microeconomics). This chapter puts them in the right order.

The economy of the United States (or any large political entity) consists of myriad interacting units. Some of them contribute to the output of the economy; some of them constrain the output; some of them are a drain upon it. The contributing units are the persons, families, private charities, and business (small and large) that produce economic goods (products and services) which are voluntarily exchanged for the mutual benefit of the trading parties. (Voluntary, private charities are among the contributing units because they help willing donors attain the satisfaction of improving the lot of persons in need. Voluntary charity — there is no other kind — is not a drain on the economy.)

Government is also a contributing unit to the extent that it provides a safe zone for the production and exchange of economic goods, to eliminate or reduce the debilitating effects of force and fraud. The safe zone is international as well as domestic when the principals of the U.S. government have the wherewithal and will to protect Americans’ overseas interests. The provision of a safe zone is usually referred to as the “rule of law”.

Most other governmental functions constrain or drain the economy. Those functions consist mainly of regulatory hindrances and forced “charity,” which includes Social Security, Medicare, Medicaid, and other federal, State, and local “welfare” programs. In “The Rahn Curve Revisited,” I estimate the significant negative effects of regulation and government spending on GDP.

There is a view that government contributes directly to economic progress by providing “infrastructure” (e.g., the interstate highway system) and underwriting innovations that are adopted and adapted by the private sector (e.g., the internet). Any such positive effects are swamped by the negative ones (see “The Rahn Curve Revisited”). Diverting resources to government uses in return for the occasional “social benefit” is like spending one’s paycheck on lottery tickets in return for the occasional \$5 winner. Moreover, when government commandeers resources for any purpose — including the occasional ones that happen to have positive payoffs — the private sector is deprived of opportunities to put those resources to work in ways that more directly advance the welfare of consumers.

I therefore dismiss the thrill of occasionally discovering  a gold nugget in the swamp of government, and turn to the factors that underlie steady, long-term economic progress: hard work; smart work; saving and investment; invention and innovation; implementation (entrepreneurship); specialization and trade; population growth; and the rule of law. These are defined in the first section of “Economic Growth Since World War II“.

It follows that economic progress — or a lack thereof — is a microeconomic phenomenon, even though it is usually treated as a macroeconomic one. One cannot write authoritatively about macroeconomic activity without understanding the microeconomic activity that underlies it. Moreover, macroeconomic aggregates (e.g., aggregate demand, aggregate supply, GDP) are essentially meaningless because they represent disparate phenomena.

Consider A and B, who discover that, together, they can have more clothing and more food if each specializes: A in the manufacture of clothing, B in the production of food. Through voluntary exchange and bargaining, they find a jointly satisfactory balance of production and consumption. A makes enough clothing to cover himself adequately, to keep some clothing on hand for emergencies, and to trade the balance to B for food. B does likewise with food. Both balance their production and consumption decisions against other considerations (e.g., the desire for leisure).

A and B’s respective decisions and actions are microeconomic; the sum of their decisions, macroeconomic. The microeconomic picture might look like this:

• A produces 10 units of clothing a week, 5 of which he trades to B for 5 units of food a week, 4 of which he uses each week, and 1 of which he saves for an emergency.
• B, like A, uses 4 units of clothing each week and saves 1 for an emergency.
• B produces 10 units of food a week, 5 of which she trades to A for 5 units of clothing a week, 4 of which she consumes each week, and 1 of which she saves for an emergency.
• A, like B, consumes 4 units of food each week and saves 1 for an emergency.

Given the microeconomic picture, it is trivial to depict the macroeconomic situation:

• Gross weekly output = 10 units of clothing and 10 units of food
• Weekly consumption = 8 units of clothing and 8 units of food
• Weekly saving = 2 units of clothing and 2 units of food

You will note that the macroeconomic metrics add no useful information; they merely summarize the salient facts of A and B’s economic lives — though not the essential facts of their lives, which include (but are far from limited to) the degree of satisfaction that A and B derive from their consumption of food and clothing.

The customary way of getting around the aggregation problem is to sum the dollar values of microeconomic activity. But this simply masks the aggregation problem by assuming that it is possible to add the marginal valuations (i.e., prices) of disparate products and services being bought and sold at disparate moments in time by disparate individuals and firms for disparate purposes. One might as well add two bananas to two apples and call the result four bapples.

The essential problem is that A and B will derive different kinds and amounts of enjoyment from clothing and food, and those different kinds and amounts of enjoyment cannot be summed in any meaningful way. If meaningful aggregation is impossible for A and B, how can it be possible for an economy that consists of millions of economic actors and an untold, constantly changing, often improving variety of goods and services?

GDP, in other words, is nothing more than what it seems to be on the surface: an estimate of the dollar value of economic output. It is not a measure of “social welfare” because there is no such thing. (See “Social Welfare” in Chapter 2). And yet it is a concept that infests microeconomics and macroeconomics.

Aggregate demand and aggregate supply are nothing but aggregations of the dollar values of myriad transactions. Aggregate demand is an after-the-fact representation of the purchases made by economic units; aggregate supply is an after-the-fact representation of the sales made by economic units. There is no “aggregate demander” or “aggregate supplier”.

Interest rates, though they tend to move in concert, are set at the microeconomic level by lenders and borrowers. Interest rates tend to move in concert because of factors that influence them: inflation, economic momentum, and the supply of money.

Inflation is a microeconomic phenomenon which is arbitrarily estimated by sampling the prices of defined “baskets” of products and services. The arithmetic involved doesn’t magically transform inflation into a macroeconomic phenomenon.

Economic momentum, as measured by changes in GDP, is likewise a microeconomic phenomenon disguised as a macroeconomic, as previously discussed.

The supply of money, over which the Federal Reserve has some control, is the closest thing there is to a truly macroeconomic phenomenon. But the Fed’s control of the supply of money, and therefor of interest rates, is tenuous.

Macroeconomic models of the economy are essentially worthless because they can’t replicate the billions of transactions that are the flesh and blood of the real economy. (See “Economic Modeling: A Case of Unrewarded Complexity“.) One of the simplest macroeconomic models — the Keynesian multiplier — is nothing more than a mathematical trick. (See “The Keynesian Multiplier: Fiction vs. Fact”.)

Macroeconomics is a sophisticated form of mental masturbation — nothing more, nothing less.

Keynesianism: Upside-Down Economics in the Collectivist Cause

A recent post, “Government in Macroeconomic Perspective,” is dauntingly long and replete with equations. The equations are simple ones, but may be off-putting to readers who are allergic to mathematical notation. Herewith is an abridged version of the post. Please refer to the original for details of the argument and references to supporting material.

A nation’s aggregate economic activity usually is measured by its Gross Domestic Product (GDP). I accept GDP as an aggregate, monetary measure of national output. But it is impossible to sum the true value of the myriad economic transactions that GDP is supposed to represent because each transaction means something different to the participants in the transaction; that is, the true value of economic goods is subjective.

GDP, nevertheless, affords a rough measure of the general level of a nation’s material output, that is, the rate at which goods and services are being produced (exclusive of such important things as “household production”). All things being the same, a large fraction of a nation’s citizens — but certainly not all of them — will be better off materially if GDP is growing and worse off if it is shrinking. Governmental activities have led to an economy that produces a small fraction of its potential output. And yet, the true believers in big government seek to make it larger and ever more destructive.

Government spending – beyond a certain level — does not increase GDP, but generally redistributes and decreases it. Government spending is beneficial up to the point where it becomes a drain on GDP; that is, at the point where government exceeds a minimal, protective role and acts in ways that discourage productive effort.

Government spending enables governmental activities of five types:

1. transfer payments to individuals (e.g., Social Security), which impose costs because the payments transfer income to those who did not earn from those who did;
2. de facto transfer payments, namely, the compensation of government employees, and the compensation that flows to the employees, shareholders, and creditors of government contractors – all of which must be financed by private-sector entitites;
3. purchases of consumables and capital that are used directly by government in the provision of government services (e.g., fuel for government vehicles, electricity for government buildings, government vehicles, and government buildings);
4. the continuation, initiation, modification, and enforcement of tax codes, regulations, administrative procedures, statutes, ordinances, executive orders, and judicial decrees; and
5. the financing of items 1 – 4.

The net effect of items 1 and 2 is almost certainly a reduction of GDP. Why? The diversion of income to the unproductive (e.g., persons on Social Security) and counterproductive (e.g., government employees who write and enforce regulations) – by whatever means (taxing or borrowing) is bound to disincentivize work, saving, innovation, and investment. That causes GDP to be lower than it otherwise would be, but the effect is multiplicative, not merely a matter of addition or subtraction. (A Keynesian would argue that the actions encompassed in item 1 tend to raise GDP because the recipients of nominal transfer payments probably have higher marginal propensities to consume than do the persons from whom the transfer payments are exacted. This facile claim overlooks the disincentivizing effects of taxation on the more productive components of an economy, and on the resulting reduction in work effort and growth-producing investment.)

Similarly, the diversion of resources to items 3 and 4 cannot be thought of as additions to or subtractions from GDP, but as multiplicative, because of the same kind of disincentivizing leverage. For example, one effect of item 4 is the unobserved but very real burden placed on the private sector by federal regulations. It has been estimated, reliably, that those regulations impose a hidden cost greater than 15 percent of GDP.

Then there is item 5: financing. In the end, it matters not whether governmental activities are financed by borrowing or taxation, and if by borrowing, whether the lenders are domestic or foreign. This is because it is government spending that diverts resources from private uses, and it is government spending that enables destructive governmental activities (e.g., the writing and enforcement of regulations).

Government long ago became larger than necessary to perform its minimal protective functions. Consider what has happened since 1890, when the early legislative “accomplishments” of the Progressive Era – the establishment of the Interstate Commerce Commission in 1887 and the passage of the Sherman Antitrust Act in 1890 – began to weigh on the economy.

Real GDP (in year 2005 dollars) was \$319 billion in 1890; it had risen to \$13.3 trillion in 2011 — a compound growth rate of about 3.1 percent. But real GDP in 2011 would have been more than \$104 trillion had growth continued at an annual rate of 4.9 percent after 1890 (the rate of growth from 1866 through 1890). What happened? The heavy hand of government (at all levels) — especially after 1929 — made itself felt by discouraging work, discouraging the saving that makes investment possible, discouraging innovation, and (even to the extent that innovation persists) discouraging the investments required to bring innovation on line. How? It begins with the diversion of resources to governmental activities, and is compounded by the cumulative disincentivizing effects of taxes, regulations, administrative procedures, statutes, ordinances, executive orders, and judicial decrees.

Defenders of big government will say that the rate of growth could not have been sustained at something like 5 percent. But such an assertion, if it is based on anything other than ignorance, is based on a simple, sub-exponential model of growth, where returns on investment are diminishing. This model overlooks the effects of innovation and recombination (the use of previous innovations in new ways). If the model of ever-diminishing growth were correct, the U.S. economy would not have experienced rising growth in the first 20 to 25 years after the end of World War II. No, the defenders of sub-exponential growth must look to the Great Society — and to the continuous expansion of the regulatory-welfare state — if they wish to understand the artificially low rate at which the economy is growing: currently about 2 percent a year.

Despite what I have said here about the deleterious effects of bigger-than-minimal government, there are true believers who maintain that the greater the scope and scale of government, the better and richer America will be. These true believers evidently have not considered the cumulative effect  of big government on the incomes and wealth of Americans. As the preceding analysis suggests, those relatively few Americans who would not be better off with minimal government would be the beneficiaries of a pool of charitable giving that is vastly greater than the present pool.

That big government might be harmful, even to the “little people” who are its supposed beneficiaries, is of no account to its worshipers – as long as they run it, advise in the running of it, profit by it, or simply enjoy watching it run roughshod over the lives and fortunes of others. Power and the vicarious enjoyment of power are habit-forming drugs.

The ranks of true believers are peopled such left-wing economists as Brad DeLong, James K. Galbraith, and Paul Krugman. They adhere to and popularize two major rationalizations of big government — the Keynesian fallacy and the myth that government is the same as community.

In “A Keynesian Fantasy Land” I discuss six reasons for the ineffectiveness of Keynesian “stimulus”; in summary:

1. The “leakage” to imports

“Part of the extra spending stimulus fails to stimulate domestic income because as much as 0.3 of the multiplier might leak out through extra imports.” (Anthony de Jasay, “Micro, Macro, and Fantasy Economics,” Library of Economics and Liberty, December 6, 2010)

2. The disincentivizing effects of government borrowing and spending

Even if additional debt does not crowd out private-sector borrowing to finance business expansion, it will nevertheless inhibit investments in business expansion. This inhibiting effect is compounded by the reasonable expectation that many items in a “stimulus” package will become permanent fixtures in the government’s budget

3. The timing-targeting problem

The lag between the initial agitation for “stimulus” and its realization. In the extreme, the lag can be so great as to have no effect other than to divert employed resources from private to government uses. But even where there is a relatively brief lag, “stimulus” spending is essentially wasted if the result is simply to divert already employed resources from private to government uses.

A drop in AD usually is caused by an exogenous event, and that exogenous event usually is a credit crisis. Pumping money into the economy — especially when it results in the bidding up the prices of already employed resources — does not reinflate the punctured credit bubble that caused the slowdown.

5. Inequity, moral hazard, and their consequences

Favorable treatment of defaulters and failing companies generates considerable popular resentment, which — in the present instance — has found a vocal and politically potent outlet in the Tea Party movement. Favorable treatment of defaulters and failing companies also creates moral hazard; that is, it encourage unwise risk-taking that can (and probably will) spark future crises, leading the government to assume more obligations and impose more regulations, in a futile effort to change human nature.

6. The human factor

Those who cling to the Keynesian multiplier would like the world to comply with it. But the world does not because it is filled with people, whose behavior is not determined (or described) by a simplistic model but by their responses to incentives, their political predispositions, their informed and reasonable skepticism about the consequences of government intervention in economic matters, and — above all else — their fallibility.

In truth, the Keynesian multiplier is a mathematical fiction, as explained here, and government spending is in fact destructive of economic growth, as discussed here and in some of the posts listed at the end.

“We owe it to ourselves” is a phrase used by Paul Krugman (among others on the left). It is a variant of the stock rationale for socializing gains and losses: “We’re all in this together.” As if the citizens of the United States were members of an extraordinarily large community, with a perpetual town-hall meeting conducted by the government of the United States.

Consider the intellectual dishonesty of Krugman’s claim that “we” owe the debt of the U.S. government to “ourselves.” Who are “we”? If government borrows money and spends it on goodies for Congressman X, Y, and Z’s districts, how do I get my cut? Or does the happiness generated in Congressman X, Y, and Z’s districts simply radiate in waves across the country, eventually reaching me and making me feel better?

If the borrowed money makes (some) people in Congressman X, Y, and Z’s districts better off, why is it that “we” (i.e. the rest of us and/or our descendants) end up repaying the debt that made those others better off? I do not understand how I “owe it to myself” when (a) I didn’t ask to borrow the money and (b) I gained nothing as a result of the borrowing.

You might claim that my personal wishes are of no account because Congress and the president are duly elected by majorities of voters. But that is tantamount to saying that Congress and the president possess a kind of omniscient super-consciousness that somehow overrides the harm, hate, and discontent that flow from their acts.

The left succeeds, in large part, because apologists for big government — from Krugman to Obama — are skillful practitioners of slippery logic. An assumption here, an assumption there, and government spending is made out to be a source of enrichment. The hard truth is that government spending — and the big government that it supports — is the source of America’s impending impoverishment.

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Government in Macroeconomic Perspective

I. INTRODUCTION

A nation’s aggregate economic activity usually is measured by its Gross Domestic Product (GDP). I accept GDP as an aggregate, monetary measure of national output. But it is impossible to sum the true value of the myriad economic transactions that GDP is supposed to represent because each transaction means something different to the participants in the transaction; that is, the true value of economic goods is subjective. (See, for example, Peter Boettke’s “Austrian School of Economics,” at The Concise Encyclopedia of Economics., and my posts, “Subjective Value: A Proof by Example” and “Microeconomics and Macroeconomics.”)

GDP, nevertheless, affords a rough measure of the general level of a nation’s material well-being. All things being the same, a large fraction of a nation’s citizens — but certainly not all of them — will be better off materially if GDP is growing and worse off if it is shrinking. But no one who is paying attention to the state of the nation should mistake material progress for real progress. (See, for example, “I Want My Country Back.”)

The usual way of representing GDP is called the expenditure method. In simple form, it expresses GDP this way:

GDP = C + I + G + (X – M)

Note: “Gross” means that GDP measures production regardless of the various uses to which that production can be put. Production can be used for immediate consumption, for investment in new fixed assets or inventories, or for replacing depreciated fixed assets. “Domestic” means that GDP measures production that takes place within the country’s borders. In the expenditure-method equation given above, the exports-minus-imports term is necessary in order to null out expenditures on things not produced in the country (imports) and add in things produced but not sold in the country (exports). (Taken from “Gross domestic product” at Wikipedia. See also Mack Ott’s “National Income Accounts” at The Concise Encyclopedia of Economics.)

This equation has become so familiar that its correctness is taken for granted. But a bit of reflection reveals it as a model of inconsistency. The dichotomy between consumption and investment is sensible. But the goods acquired and sold in international trade are of the same two types; there is no reason to segregate them from consumption and investment. This is especially true because the sum of consumption and investment is greater than it would be in the absence of international trade. Government, on the other hand, is a net consumer of economic output, not a net producer of it, as the “+ G” term might suggest.

With that background, I will offer an alternative to the standard expenditure method of describing GDP. The journey is step-wise: from a closed economy without international trade or government to an economy with international trade, but without government, to an economy with both international trade and government. Along the way, I fully acknowledge the importance of government as a contributor to GDP, as long as its role is to foster beneficial exchange by maintaining the rule of law and defending Americans from predators, at home and abroad.

That said, government activities (as reflected in total government spending) have led to an economy that produces a small fraction of its potential output. And yet, the true believers in big government seek to make it larger and ever more destructive. I expand on these points at length in Part II, An Alternative Expenditure Model; Part III, The High Cost of Big Government; and Part IV, The Heart of the Problem: Big-Government Worship and Pseudo-Intellectualism. (Continued below the fold.) Continue reading

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Macroeconomics and Microeconomics

Macroeconomic aggregates (e.g., aggregate demand, aggregate supply) are essentially meaningless because they represent disparate phenomena.

Consider A and B, who discover that, together, they can have more clothing and more food if each specializes: A in the manufacture of clothing, B in the production of food. Through voluntary exchange and bargaining, they find a jointly satisfactory balance of production and consumption. A makes enough clothing to cover himself adequately, to keep some clothing on hand for emergencies, and to trade the balance to B for food. B does likewise with food. Both balance their production and consumption decisions against other considerations (e.g., the desire for leisure).

A and B’s respective decisions and actions are microeconomic; the sum of their decisions, macroeconomic. The microeconomic picture might look like this:

• A produces 10 units of clothing a week, 5 of which he trades to B for 5 units of food a week, 4 of which he uses each week, and 1 of which he saves for an emergency.
• B, like A, uses 4 units of clothing each week and saves 1 for an emergency.
• B produces 10 units of food a week, 5 of which she trades to A for 5 units of clothing a week, 4 of which she consumes each week, and 1 of which she saves for an emergency.
• A, like B, consumes 4 units of food each week and saves 1 for an emergency.

Given the microeconomic picture, it is trivial to depict the macroeconomic situation:

• Gross weekly output = 10 units of clothing and 10 units of food
• Weekly consumption = 8 units of clothing and 8 units of food
• Weekly saving = 2 units of clothing and 2 units of food

You will note that the macroeconomic metrics add no useful information; they merely summarize the salient facts of A and B’s economic lives — though not the essential facts of their lives, which include (but are far from limited to) the degree of satisfaction that A and B derive from their consumption of food and clothing.

The customary way of getting around the aggregation problem is to sum the dollar values of microeconomic activity. But this simply masks the aggregation problem by assuming that it is possible to add the marginal valuations (i.e., prices) of disparate products and services being bought and sold at disparate moments in time by disparate individuals and firms for disparate purposes. One might as well add two bananas to two apples and call the result four bapples.

The essential problem is that A and B will derive different kinds and amounts of enjoyment from clothing and food, and that those different kinds and amounts of enjoyment cannot be summed in any meaningful way. If meaningful aggregation is impossible for A and B, how can it be possible for an economy that consists of millions of economic actors and an untold variety of goods and services? And how is it possible when technological change yields results such as this?

GDP, in other words, is nothing more than what it seems to be on the surface: an estimate of the dollar value of economic output. It is not a measure of “social welfare” because there is no such thing.

Given that, why do I sometimes use GDP statistics? And, if GDP is really a meaningless aggregate, is there a valid, alternative way of depicting aggregate well-being? To be continued.

Modeling Is Not Science

The title of this post applies, inter alia, to econometric models — especially those that purport to forecast macroeconomic activity — and climate models — especially those that purport to forecast global temperatures. I have elsewhere essayed my assessments of macroeconomic and climate models. (See this and this, for example.) My purpose here is to offer a general warning about models that claim to depict and forecast the behavior of connected sets of phenomena (systems) that are large, complex, and dynamic. I draw, in part, on a paper that I wrote 28 years ago. That paper is about warfare models, but it has general applicability.

HEMIBEL THINKING

Philip M. Morse and George E. Kimball, pioneers in the field of military operations research — the analysis and modeling of military operations — wrote that the

successful application of operations research usually results in improvements by factors of 3 or 10 or more. . . . In our first study of any operation we are looking for these large factors of possible improvement. . . .

One might term this type of thinking “hemibel thinking.” A bel is defined as a unit in a logarithmic scale corresponding to a factor of 10. Consequently a hemibel corresponds to a factor of the square root of 10, or approximately 3. (Methods of Operations Research, 1946, p. 38)

This is science-speak for the following proposition: In large, complex, and dynamic systems (e.g., war, economy, climate) there is much uncertainty about the relevant parameters, about how to characterize their interactions mathematically, and about their numerical values.

Hemibel thinking assumes great importance in light of the imprecision inherent in models of large, complex, and dynamic systems. Consider, for example, a simple model with only 10 parameters. Even if such a model doesn’t omit crucial parameters or mischaracterize their interactions,  its results must be taken with large doses of salt. Simple mathematics tells the cautionary tale: An error of about 12 percent in the value of each parameter can produce a result that is off by a factor of 3 (a hemibel); An error of about 25 percent in the value of each parameter can produce a result that is off by a factor of 10. (Remember, this is a model of a relatively small system.)

If you think that models and “data” about such things as macroeconomic activity and climatic conditions cannot be as inaccurate as that, you have no idea how such models are devised or how such data are collected and reported. It would be kind to say that such models are incomplete, inaccurate guesswork. It would be fair to say that all too many of them reflect their developers’ policy biases.

Of course, given a (miraculously) complete model, data errors might (miraculously) be offsetting, but don’t bet on it. It’s not that simple: Some errors will be large and some errors will be small (but which are which?), and the errors may lie in either direction (but in which direction?). In any event, no amount of luck can prevent a modeler from constructing a model whose estimates advance a favored agenda (e.g., massive, indiscriminate government spending; massive, futile, and costly efforts to cool the planet).

NO MODEL IS EVER PROVEN

The construction of a model is only one part of the scientific method. A model means nothing unless it can be tested repeatedly against facts (facts not already employed in the development of the model) and, through such tests, is found to be more accurate than alternative explanations of the same facts.As Morse and Kimball put it,

[t]o be valuable [operations research] must be toughened by the repeated impact of hard operational facts and pressing day-by-day demands, and its scale of values must be repeatedly tested in the acid of use. Otherwise it may be philosophy, but it is hardly science. (Op. cit., p. 10)

Even after rigorous testing, a model is never proven. It is, at best, a plausible working hypothesis about relations between the phenomena that it encompasses.

A model is never proven for two reasons. First, new facts may be discovered that do not comport with the model. Second, the facts upon which a model is based may be open to a different interpretation, that is, they may support a new model that yields better predictions than its predecessor.

The fact that a model cannot be proven can be take as an excuse for action: “We must act on the best information we have.”  That excuse — which justifies an entire industry, namely, government-funded analysis — does not fly, as I discuss below.

MODELS LIE WHEN LIARS MODEL

Any model is dangerous in the hands of a skilled, persuasive advocate. A numerical model is especially dangerous because:

• There is abroad a naïve belief in the authoritativeness of numbers. A bad guess (even if unverifiable) seems to carry more weight than an honest “I don’t know.”
• Relatively few people are both qualified and willing to examine the parameters of a numerical model, the interactions among those parameters, and the data underlying the values of the parameters and magnitudes of their interaction.
• It is easy to “torture” or “mine” the data underlying a numerical model so as to produce a model that comports with the modeler’s biases (stated or unstated).

There are many ways to torture or mine data; for example: by omitting certain variables in favor of others; by focusing on data for a selected period of time (and not testing the results against all the data); by adjusting data without fully explaining or justifying the basis for the adjustment; by using proxies for missing data without examining the biases that result from the use of particular proxies.

So, the next time you read about research that purports to “prove” or “predict” such-and-such about a complex phenomenon — be it the future course of economic activity or global temperatures — take a deep breath and ask these questions:

• Is the “proof” or “prediction” based on an explicit model, one that is or can be written down? (If the answer is “no,” you can confidently reject the “proof” or “prediction” without further ado.)
• Are the data underlying the model available to the public? If there is some basis for confidentiality (e.g., where the data reveal information about individuals or are derived from proprietary processes) are the data available to researchers upon the execution of confidentiality agreements?
• Are significant portions of the data reconstructed, adjusted, or represented by proxies? If the answer is “yes,” it is likely that the model was intended to yield “proofs” or “predictions” of a certain type (e.g., global temperatures are rising because of human activity).
• Are there well-documented objections to the model? (It takes only one well-founded objection to disprove a model, regardless of how many so-called scientists stand behind it.) If there are such objections, have they been answered fully, with factual evidence, or merely dismissed (perhaps with accompanying scorn)?
• Has the model been tested rigorously by researchers who are unaffiliated with the model’s developers? With what results? Are the results highly sensitive to the data underlying the model; for example, does the omission or addition of another year’s worth of data change the model or its statistical robustness? Does the model comport with observations made after the model was developed?

For two masterful demonstrations of the role of data manipulation and concealment in the debate about climate change, read Steve McIntyre’s presentation and this paper by Syun-Ichi Akasofu. For a masterful demonstration of a model that proves what it was designed to prove by the assumptions built into it, see this.

IMPLICATIONS

Government policies can be dangerous and impoverishing things. Despite that, it is hard (if not impossible) to modify and reverse government policies. Consider, for example, the establishment of public schools more than a century ago, the establishment of Social Security more than 70 years ago, and the establishment of Medicare and Medicaid more than 40 years ago. There is plenty of evidence that all four institutions are monumentally expensive failures. But all four institutions have become so entrenched that to call for their abolition is to be thought of as an eccentric, if not an uncaring anti-government zealot. (For the latest about public schools, see this.)

The principal lesson to be drawn from the history of massive government programs is that those who were skeptical of those programs were entirely justified in their skepticism. Informed, articulate skepticism of the kind I counsel here is the best weapon — perhaps the only effective one — in the fight to defend what remains of liberty and property against the depredations of massive government programs.

Skepticism often is met with the claim that such-and-such a model is the “best available” on a subject. But the “best available” model — even if it is the best available one — may be terrible indeed. Relying on the “best available” model for the sake of government action is like sending an army into battle — and likely to defeat — on the basis of rumors about the enemy’s position and strength.

With respect to the economy and the climate, there are too many rumor-mongers (“scientists” with an agenda), too many gullible and compliant generals (politicians), and far too many soldiers available as cannon-fodder (the paying public).

CLOSING THOUGHTS

The average person is so mystified and awed by “science” that he has little if any understanding of its limitations and pitfalls, some of which I have addressed here in the context of modeling. The average person’s mystification and awe are unjustified, given that many so-called scientists exploit the public’s mystification and awe in order to advance personal biases, gain the approval of other scientists (whence “consensus”), and garner funding for research that yields results congenial to its sponsors (e.g., global warming is an artifact of human activity).

Isaac Newton, who must be numbered among the greatest scientists in human history, was not a flawless scientist. (Has there ever been one?) But scientists and non-scientists alike should heed Newton on the subject of scientific humility:

I do not know what I may appear to the world, but to myself I seem to have been only like a boy playing on the seashore, and diverting myself in now and then finding a smoother pebble or a prettier shell than ordinary, whilst the great ocean of truth lay all undiscovered before me. (Quoted in Horace Freeland Judson,The Search for Solutions, 1980, p. 5.)

Related reading: Willis Eschenbach, “How Not to Model the Historical Temperature“, Watts Up With That?, March 25, 2018