Government Failure as a Root Cause of Market Failure

10 Monday Jul 2023

Posted by Nuetzel in Government Failure, Market Failure

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Capital Formation, central planning, Chevron Doctrine, Competitive Equilibrium, Corruption, crowding out, Declaration of Independence, Don Boudreaux, External Benefits, External Costs, Government Failure, Inflation, John Cochrane, Labor Supply, Market Failure, Michael Munger, monopoly power, Pareto Superiority, Peter Boettke, Price Controls, Protectionism, Redistribution, Regulatory Capture, rent seeking, Risk-Free Asset, Side Payments, Social Security, State Capacity, Tax Distortions, Thomas Jefferson, Treasury Debt, William R. Keech

We’re told again and again that government must take action to correct “market failures”. Economists are largely responsible for this widespread view. Our standard textbook treatments of external costs and benefits are constructed to demonstrate departures from the ideal of perfectly competitive market equilibria. This posits an absurdly unrealistic standard and diminishes the power and dramatic success of real-world markets in processing highly dispersed information, allocating resources based on voluntary behavior, and raising human living standards. It also takes for granted the underlying institutional foundations that lead to well-functioning markets and presumes that government possesses the knowledge and ability to rectify various departures from an ideal. Finally, “corrective” interventions are usually exposited in economics classes as if they are costless!

Failed Disgnoses

This brings into focus the worst presumption of all: that government solutions to social and economic problems never fail to achieve their intended aims. Of course that’s nonsense. If defined on an equivalent basis, government failure is vastly more endemic and destructive than market failure.

Related to this point, Don Boudreaux quotes from Peter Boettke’s Living Economics:

“According to ancient legend, a Roman emperor was asked to judge a singing contest between two participants. After hearing the first contestant, the emperor gave the prize to the second on the assumption that the second could be no worse than the first. Of course, this assumption could have been wrong; the second singer might have been worse. The theory of market failure committed the same mistake as the emperor. Demonstrating that the market economy failed to live up to the ideals of general competitive equilibrium was one thing, but to gleefully assert that public action could costlessly correct the failure was quite another matter. Unfortunately, much analytical work proceeded in such a manner. Many scholars burst the bubble of this romantic vision of the political sector during the 1960s. But it was [James] Buchanan and Gordon Tullock who deserve the credit for shifting scholarly focus.”

John Cochrane sums up the whole case succinctly in the “punchline” of a recent post:

“The case for free markets never was their perfection. The case for free markets always was centuries of experience with the failures of the only alternative, state control. Free markets are, as the saying goes, the worst system; except for all the others.”

Tracing Failures

We can view the relation between market failure and government failure in two ways. First, we can try to identify market failures and root causes. For example, external costs like pollution cause harm to innocent third parties. This failure might be solely attributable to transactions between private parties, but there are cases in which government engages as one of those parties, such as defense contracting. In other cases government effectively subsidizes toxic waste, like the eventual disposal of solar panels. Another kind of market failure occurs when firms wield monopoly power, but that is often abetted by costly regulations that deliver fatal blows to small competitors.

The second way to analyze the nexus between government and market failures is to first examine the taxonomy of government failure and identify the various damages inflicted upon the operation of private markets. That’s the course I’ll follow below, though by no means is the discussion here exhaustive.

Failures In and Out of Scope

An extensive treatment of government failure was offered eight years ago by William R. Keech and Michael Munger. To start, they point out what everyone knows: governments occasionally perpetrate monstrous acts like genocide and the instigation of war. That helps illustrate a basic dichotomy in government failures:

“… government may fail to do things it should do, or government may do things it should not do.’

Both parts of that statement have numerous dimensions. Failures at what government should do run the gamut from poor service at the DMV, to failure to enforce rights, to corrupt bureaucrats and politicians skimming off the public purse in the execution of their duties. These failures of government are all too common.

What government should and should not do, however, is usually a matter of political opinion. Thomas Jefferson’s axioms appear in a single sentence at the beginning of the Declaration of Independence; they are a tremendous guide to the first principles of a benevolent state. However, those axioms don’t go far in determining the range of specific legal protections and services that should and shouldn’t be provided by government.

Pareto Superiority

Keech and Munger engage in an analytical exercise in which the “should and shouldn’t” question is determined under the standard of Pareto superiority. A state of the world is Pareto superior if at least one person prefers it to the current state (and no one else is averse to it). Coincidentally, voluntary trades in private markets always exploit Pareto superior opportunities, absent legitimate external costs and benefits.

The set of Pareto superior states available to government can be expanded by allowing for side payments or compensation to those who would have preferred the current state. Still, those side payments are limited by the magnitude of the gains flowing to those who prefer the alternative (and if those gains can be redistributed monetarily).

Keech and Munger define government failure as the unexploited existence of Pareto superior states. Of course, by this definition, only a benevolent, omniscient, and omnipotent dictator could hope to avoid government failure. But this is no more unrealistic than the assumptions underlying perfectly competitive market equilibrium from which departure are deemed “market failures” that government should correct. Thus, Keech and Munger say:

“The concept of government failure has been trapped in the cocoon of the theory of perfect markets. … Government failure in the contemporary context means failing to resolve a classic market failure.”

But markets must operate within a setting defined by culture and institutions. The establishment of a social order under which individuals have enforceable rights must come prior to well-functioning markets, and that requires a certain level of state capacity. Keech and Munger are correct that market failure is often a manifestation of government failure in setting and/or enforcing these “rules of the game”.

“The real question is … how the rules of the game should be structured in terms of incentives, property rights, and constraints.”

The Regulatory State and Market Failures

Government can do too little in defining and enforcing rights, and that’s undoubtedly a cause of failure in markets in even the most advanced economies. At the same time there is an undeniable tendency for mission creep: governments often try to do too much. Overregulation in the U.S. and other developed nations creates a variety of market failures. This includes the waste inherent in compliance costs that far exceed benefits; welfare losses from price controls, licensing, and quotas; diversion of otherwise productive resources into rent seeking activity, anti-competitive effects from “regulatory capture”; Chevron-like distortions endemic to the administrative judicial process; unnecessary interference in almost any aspect of private business; and outright corruption and bribe-taking.

Central Planning and Market Failures

Another category of government attempting to “do too much” is the misallocation of resources that inevitably accompanies efforts to pick “winners and losers”. The massive subsidies flowing to investors in various technologies are often misdirected. Many of these expenditures end up as losses for taxpayers, and this is not the only form in which failed industrial planning takes place. A related evil occurs when steps are taken to penalize and destroy industries in political disfavor with thin economic justification.

Other clear examples of government “planning” failure are protectionist laws. These are a net drain on our wealth as a society, denying consumers of free choice and saddling the country with the necessity to produce restricted products at high cost relative to erstwhile trading partners.

There are, of course, failures lurking within many other large government spending programs in areas such as national defense, transportation, education, and agriculture. Many of these programs can be characterized as centrally planning. Not only are some of these expenditures ineffectual, but massive procurement spending seems to invite waste and graft. After all, it’s somebody else’s money.

Redistribution and Market Failures

One might regard redistribution programs as vehicles for the kinds of side payments described by Keech and Munger. Some might even say these are the side payments necessary to overcome resistance from those unable to thrive in a market economy. That reverses the historical sequence of events, however, since the dominant economic role of markets preceded the advent of massive redistribution schemes. Unfortunately, redistribution programs have been plagued by poor design, such as the actuarial nightmare inherent in Social Security and the destructive work incentives embedded in other parts of the social safety net. These are rightly viewed as government failures, and their distortionary effects spill variously into capital markets, labor markets and ultimately product markets.

Taxation and Market Failures

All these public initiatives under which government failures precipitate assorted market failures must be paid for by taxpayers. Therefore, we must also consider the additional effects of taxation on markets and market failures. The income tax system is rife with economic distortions. Not only does it inflict huge compliance costs, but it alters incentives in ways that inhibit capital formation and labor supply. That hampers the ability of input markets to efficiently meet the needs of producers, inhibiting the economy’s productive capacity. In turn, these effects spill into output market failures, with consequent losses in .social welfare. Distortionary taxes are a form of government failure that leads to broad market failures.

Deficits and Market Failure

More often than not, of course, tax revenue is inadequate to fund the entire government budget. Deficit spending and borrowing can make sense when public outlays truly produce long-term benefits. In fact, the mere existence of “risk-free” assets (Treasury debt) across the maturity spectrum might enhance social welfare if it enables improvements in portfolio diversification that outweigh the cost of the government’s interest obligations. (Treasury securities do bear interest-rate risk and, if unindexed, they bear inflation risk.)

Nevertheless, borrowing can reflect and magnify deleterious government efforts to “do too much”, ultimately leading to market failures. Government borrowing may “crowd out” private capital formation, harming economy-wide productivity. It might also inhibit the ability of households to borrow at affordable rates. Interest costs of the public debt may become explosive as they rise relative to GDP, limiting the ability of the public sector to perform tasks that it should *actually* do, with negative implications for market performance.

Inflation and Market Failure

Deficit spending promotes inflation as well. This is more readily enabled when government debt is monetized, but absent fiscal discipline, the escalation of goods prices is the only remaining force capable of controlling the real value of the debt. This is essentially the inflation tax.

Inflation is a destructive force. It distorts the meaning of prices, causes the market to misallocate resources due to uncertainty, and inflicts costs on those with fixed incomes or whose incomes cannot keep up with inflation. Sadly, the latter are usually in lower socioeconomic strata. These are symptoms of market failure prompted by government failure to control spending and maintain a stable medium of exchange.

Conclusion

Markets may fail, but when they do it’s very often rooted in one form of government failure or another. Sometimes it’s an inadequacy in the establishment or enforcement of property rights. It could be a case of overzealous regulation. Or government may encroach on, impede, or distort decisions regarding the provision of goods or services best left to the market. More broadly, redistribution and taxation, including the inflation tax, distort labor and capital markets. The variety of distortions created when government fails at what it should do, or does what it shouldn’t do, is truly daunting. Yet it’s difficult to find leaders willing to face up to all this. Statism has a powerful allure, and too many elites are in thrall to the technocratic scientism of government solutions to social problems and central planning in the allocation of resources.

Biden OMB Suggests Minimal Discounts of Future Benefits

28 Wednesday Jun 2023

Posted by Nuetzel in Big Government, Risk, Tradeoffs

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Administrative State, Certainty Equivalent, Consumer Price Index, Discount Rate, John Cochrane, Joshua Rauh, MIT, Modernizing Regulatory Review, Office of Management and Budget, Present Value, Real Interest Rate, Regulatory Impact Analysis, Risk-Free Rate, TIPS, Tradeoffs, Treasury Bonds, Unintended Consequences

Tweaks to the projected costs and benefits of prospective regulations or programs can be a great way to encourage domination of resources and society by the state. Of course, public policy ideas will never receive serious consideration unless their “expected” benefits exceed costs. It’s therefore critical that the validity of cost and benefit estimates — to say nothing of their objectivity — are always subject to careful review. By no means does that ensure that the projections are reasonable, however.

Traditionally less scrutinized is the rate at which the future costs and benefits of a program or regulation are discounted into present value terms. The discount rate can have a tremendous impact on the comparison of costs and benefits when their timing differs significantly, which is usually the case.

Intertemporal Tradeoffs

People generally aren’t willing to forsake present pleasure without at least a decent prospect of future gain. Thus, we observe that the deferral of $1 of consumption today generally brings a reward of more than $1 of future consumption. That’s made possible by the existence of productive opportunities for the use of resources. These opportunities, and the freedom to exploit them, allow a favorable tradeoff at which we transform resources across time for the benefit of both our older selves and our progeny. The interaction of savers and investors in such opportunities results in an equilibrium interest rate balancing the supply and demand for saving.

We can restate the tradeoff to demonstrate the logic of discounting. That is, the promise of $1 in the future induces the voluntary deferral of less than $1 of consumption today. To arrive at the amount of the deferral, the promised $1 in the future is discounted at the consumer’s rate of time preference. The promised $1 must cover the initial deferral of consumption plus the consumer’s perceived opportunity cost of lost consumption in the present, or else the “trade” won’t happen.

Discounting practices are broadly embedded in the economy. They provide a rational basis of evaluating inter-temporal tradeoffs. The calculation of net present values (NPVs) and internal rates of return (the discount rate at which NPV = 0) are standard practices for capital budgeting decisions in the private sector. Public-sector cost-benefit analysis often makes use of discounting methodology as well, which is unequivocally good as long as the process is not rigged.

Government Discounting

The Office of Management and Budget (OMB) provides guidance to federal agencies on matters like cost-benefit analysis. As part of a recent proposal that was prompted by executive orders on “Modernizing Regulatory Review” from the Biden Administration, the OMB has recommended revisions to a 2003 Circular entitled “Regulatory Analysis”. A major aspect of the proposal is a downward adjustment to recommended discount rates, largely dressed up as an update for “changes in market conditions”.

Since 2003, the OMB’s guidance on discount rates called for use of a historical average rate on 10-year government bonds. Before averaging, the rate was converted to a “real rate” in each period by subtracting the rate of increase in the Consumer Price Index (CPI). The baseline discount rate of 3% was taken from the average of that real rate over the 30 years ending in 2002. There has been an alternative discount rate of 7% under the existing guidance intended as a nod to the private costs of capital, but it’s not clear how seriously agencies took this higher value.

The new proposal seeks to update the calculation of recommended discount rates by using more recent data on Treasury rates and inflation. One aspect of the proposal is to utilize the rate on 10-year inflation-indexed Treasury bonds (TIPS) for the years in which it is available (2003-2022). The first ten years of the “new” 30-year average would use the previous methodology. However, the proposal gives examples of how other methods would change the resulting discount rate and requests comments on the most appropriate method of updating the calculation of the 30-year average.

The new baseline discount rate proposed by OMB is 1.7%, and it is lower still for very distant flows of benefits. This is intended as a real, after-tax discount rate on Treasury bonds. It represents an average (and ex post) risk-free rate on bonds held to maturity over the historical period in question, calculated as described by OMB. However, like the earlier guidance, it is not prospective in any sense. And of course it is quite low!

Our Poor Little Rich Ancestors

The projected benefits of regulations or other public initiatives can be highly dubious in the first place. Unintended consequences are the rule rather than the exception. Furthermore, even modest economic growth over several generations will leave our ancestors with far more income and wealth than we have at our disposal today. That means their ability to adapt to changes will be far superior, and they will have access to technologies making our current efforts seem quaint.

Now here’s the thing: discounting the presumed benefits of government intervention at a low rate would drastically inflate their present value. John Cochrane uses an extreme case to illustrate the point. Suppose a climate policy is projected to avoid costs equivalent to 5% of GDP 100 years from now. Those avoided costs would represent a gigantic sum! By then, at just 2% growth, real GDP will be over seven times larger than this year’s output. Cochrane calculates that 5% of real GDP in 2123 is equivalent to 37% of 2023 real GDP. And the presumed cost saving goes on forever.

We can calculate the present value of the climate policy’s benefits to determine whether it’s greater than the proposed cost of the policy. Let’s choose a fairly low discount rate like … oh, say zero. In that case, the present value is infinite, and it is infinite at any discount rate below 2% (such as 1.7%). That’s because the benefits grow at 2% (like real GDP) and go on forever! That’s faster than the diminishing effect of discounting on present value. In mathematical terms, the series does not converge. Of course, this is not discounting. It is non-discounting. Cochrane’s point, however, is that if you take these calculations seriously, you’d be crazy not to implement the policy at any finite cost! You shouldn’t mind the new taxes at all! Or the inflation tax induced by more deficit spending! Or higher regulatory costs passed along to you as a consumer! So just stop your bitching!

Formal Comments to OMB

If Cochrane’s example isn’t enough to convince you of the boneheadedness of the OMB proposal, there are several theoretical reasons to balk. Cochrane provides links to a couple of formal comments submitted to OMB. Joshua Rauh of the Stanford Business School details a few fundamental objections. His first point is that a regulatory impact analysis (RIA), or the evaluation of any other initiative, “should be based on market conditions that prevail at the time of the RIA”. In other words, the choice of a discount rate should not rely on an average over a lengthy historical period. Second, it is unrealistic to assume that the benefits and costs of proposed regulations are risk-free. In fact, unlike Treasury securities, these future streams are quite risky, and they are not tradable, and they are not liquid.

Rauh also notes that the OMB’s proposed decline in discount rates to be applied to benefits or cash flows in more distant periods has no reliable empirical basis. He believes that results based on a constant discount rate should at least be reported. Moreover, agencies should be required to offer justification for their choice of a discount rate relative to the risks inherent in the streams of costs and benefits on any new project or rule.

Rauh is skeptical of recommendations that agencies should add a theoretical risk premium to a risk-free rate, however, despite the analytical superiority of that approach. Instead, he endorses the simplicity of the OMB’s previous guidance for discount rates of 3% and 7%. But he also proposes that RIAs should always include “the complete undiscounted streams of both benefits and costs…”. If there are distributions of possible cost and benefit streams, then multiple streams should be included.

Furthermore, Rauh says that agencies should not recast streams of benefits in the form of certainty equivalents, which interpose various forms of objective functions in order to calculate a “fair guarantee”, rather than a range of actual outcomes. Instead, Rauh insists that straightforward expected values should be used, This is for the sake of transparency and to enable independent assessment of RIAs.

Another comment on the OMB proposal comes from a group of economists at MIT. They have fewer qualms than Rauh regarding the use of risk-adjusted discount rates by government agencies. In addition, they note that risk in the private sector can often be ameliorated by diversification, whereas risks inherent in public policy must be absorbed by changes in taxes, government spending, or unintended costs inflicted on the private sector. Taxpayers, those having stakes in other programs, and the general public bear these risks. Using Treasury rates for discounting presumes that bad outcomes have no cost to society!

Conclusion

Discounting the costs and benefits of proposed regulations and other government programs should be performed with discount rates that reflect risks. Treasury rates are wholly inappropriate as they are essentially risk-free over time horizons often much shorter than the streams of benefits and costs to be discounted. The OMB proposal might be a case of simple thoughtlessness, but I doubt it. To my mind, it aligns a little too neatly with the often expansive agenda of the administrative state. It would add to what is already a strong bias in favor of regulatory action and government absorption of resources. Champions of government intervention are prone to exaggerate the flow of benefits from their pet projects, and low discount rates exaggerate the political advantages they seek. That bias comes at the expense of the private sector and economic growth, where inter-temporal tradeoffs and risks are exploited only at more rational discounts and then tested by markets.

A Monetary Cease-Fire As Inflation Retreats, For Now

20 Tuesday Jun 2023

Posted by Nuetzel in Inflation, Monetary Policy

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Bank Reserves, Bureau of Labor Statistics, CPI, Debt Ceiling, Fed Pause, Federal Funds, Federal Open Market Committee, Hoarding Labor, Inflation, Inverted Yield Curve, Jobless Claims, Leading Economic Indicators, Liquidity, PCE Deflator, Philip Jefferson, PPI, Quantitative Tightening, Real Weekly Earnings, Soft Landing, Stock Rally

The inflation news was good last week, with both the consumer and producer price indices (CPI and PPI) for May coming in below expectations. The increase in the core CPI, which excludes food and energy prices, was the same as in April. As this series of tweets attempts to demonstrate, teasing out potential distortions from the shelter component of the CPI shows a fairly broad softening. That might be heartening to the Federal Reserve, though at 4.0%, the increase in the CPI from a year ago remains too high, as does the core rate at 5.3%. Later in the month we’ll see how much the Fed’s preferred inflation gauge, the PCE deflator, exceeds the 2% target.

Inflation has certainly tapered since last June, when the CPI had its largest monthly increase of this cycle. After that, the index leveled off to a plateau lasting through December. But the big run-up in the CPI a year ago had the effect of depressing the year-over-year increase just reported, and it will tend to depress next month’s inflation report as well. After this June’s CPI (to be reported in July), the flat base from a year earlier might have a tendency to produce rising year-over-year inflation numbers over the rest of this year. Also, the composition of inflation has shifted away from goods prices and into services, where markets aren’t as interest-rate sensitive. Therefore, the price pressure in services might have more persistence.

So it’s way too early to say that the Fed has successfully brought inflation under control, and they know it. But last week, for the first time in 10 meetings, the Fed’s chief policy-making arm (the Federal Open Market Committee, or FOMC) did not increase its target for the federal funds rate, leaving it at 5% for now. This “pause” in the Fed’s rate hikes might have more to do with internal politics than anything else, as new Vice Chairman Philip Jefferson spoke publicly about the “pause” several days before the meeting. That statement might not have been welcome to other members of the FOMC. Nevertheless, at least the pause buys some time for the “long and variable lags” of earlier monetary tightening to play out.

There are strong indications that the FOMC expects additional rate hikes to be necessary in order to squeeze inflation down to the 2% target. The “median member” of the Committee expects the target FF rate to increase by an additional 50 basis points by the end of 2023. At a minimum, it seems they felt compelled to signal that later rate hikes might be necessary after having their hand forced by Jefferson. That “expectation” might have been part of a “political bargain” struck at the meeting.

In addition, the Fed’s stated intent is to continue drawing down its massive securities portfolio, an act otherwise known as “quantitative tightening” (QT). That process was effectively interrupted by lending to banks in the wake of this spring’s bank failures. And now, a danger cited by some analysts is that a wave of Treasury borrowing following the increase in the debt ceiling, along with QT, could at some point lead to a shortage of bank reserves. That could force the Fed to “pause” QT, essentially allowing more of the new Treasury debt to be monetized. This isn’t an imminent concern, but perhaps next year it could present a test of the Fed’s inflation-fighting resolve.

It’s certainly too early to declare that the Fed has engineered a “soft landing”, avoiding recession while successfully reigning-in inflation. The still-inverted yield curve is the classic signal that credit markets “expect” a recession. Here is the New York Federal Reserve Bank’s recession probability indicator, which is at its highest level in over 40 years:

There are other signs of weakness: the index of leading economic indicators has moved down for the last 13 months, real retail sales are down from 13 months ago, and real average weekly earnings have been trending down since January, 2021. A real threat is the weakness in commercial real estate, which could renew pressure on regional banks. Credit is increasingly tight, and that is bound to take a toll on the real economy before long.

The labor market presents its own set of puzzles. The ratio of job vacancies to job seekers has declined, but it is still rather high. Multiple job holders have increased, which might be a sign of stress. Some have speculated that employers are “hoarding” labor, hedging against the advent of an ultimate rebound in the economy, when finding new workers might be a challenge.

Despite some high-profile layoffs in tech and financial services, job gains have held up well thus far. Of course, the labor market typically lags turns in the real economy. We’ve seen declining labor productivity, consistent with changes in real earnings. This is probably a sign that while job growth remains strong, we are witnessing a shift in the composition of jobs from highly-skilled and highly-paid workers to lower-paid workers.

A further qualification is that many of the most highly-qualified job applicants are already employed, and are not part of the pool of idle workers. It’s also true that jobless claims, while not at alarming levels, have been trending higher.

It’s important to remember that the Fed’s policy stance over the past year is intended to reduce liquidity and ultimately excess demand for goods and services. In typical boom-and-bust fashion, the tightening was a reversal from the easy-money policy pursued by the Fed from 2020 – early 2022, even in the face of rising inflation. The money supply has been declining for just over a year now, but the declines have been far short of the massive expansion that took place during the pandemic. There is still quite a lot of liquidity in the system.

That liquidity helps explain the stock market’s recovery in the face of ongoing doubts about the economy. While the market is still well short of the highs reached in early 2022, recent gains have been impressive.

Some would argue that the forward view driving stock prices reflects an expectation of a mild recession and an inevitable rebound in the economy, no doubt accompanied by eventual cuts in the Fed’s interest rate target. But even stipulating that’s the case, the timing of a stock rally on those terms seems a little premature. Or maybe not! It wouldn’t be the first time incoming data revealed a recession had been underway that no one knew was happening in real time. Are we actually coming out of shallow woods?

To summarize, inflation is down but not out. The Fed might continue its pause on rate hikes through one more meeting in late July, but there will be additional rate increases if inflation remains persistent or edges up from present levels, or if the economy shows unexpected signs of strength. I’d like to be wrong about the prospects of a recession, but a downturn is likely over the next 12 months. I’ve been saying that a recession is ahead for the past eight months or so, which reminds me that even a broken clock is right twice a day. In any case, the stock market seems to expect something mild. However misplaced, hopes for a soft landing seem very much alive.

Canadian Wildfires, Smoky Days Are Recurring Events

11 Sunday Jun 2023

Posted by Nuetzel in Forest Fires, Global Warming, Wildfires

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Anthropomorphic Global Warming, Boreal Forests, Canadian Fires, Climate Change, Dark Days, David Marcus, Edward Struzik, Fire Suppression, Forest Management, Prescribed Burns, Québec Fires, rent seeking, Wildfires

Smoke from this spring’s terrible forest fires in Canada has fouled the air in much of the country and blown into the northeastern U.S. and mid-Atlantic coastal states. The severity of the fires, if they continued at this pace over the rest of the fire season, would break Canadian records for number of fires and burned area.

Large wildfires with smoky conditions occur in these in regions from time-to-time, and it’s not unusual for fires to ignite in the late spring. The article shown above appeared in the New York Tribune on June 5, 1903. Other “dark day” episodes were recorded in New England in 1706, 1732, 1780, 1814, 1819, 1836, 1881, 1894, and 1903, and several times in the 20th century. I list early years specifically because they preceded by decades (even centuries) the era of supposed anthropomorphic global warming, now euphemistically known as “climate change”.

More recently, however, in the past 10 years, Quebec experienced relatively few wildfires. That left plenty of tinder in the boreal forests with highly flammable, sappy trees. In May, a spell of sunshine helped dry the brush in the Canadian forests. Then lightning and human carelessness sparked the fires, along with multiple instances of arson, some perpetrated by climate change activists.

On top of all that, poor forest management contributed to the conflagrations. So-called fire suppression techniques have done more harm than good over the years, as I’ve discussed on this blog in the past. David Marcus emphasizes the point:

“For years, Canadian parks officials have been warning that their country does not do enough to cull its forests and now we’re witnessing the catastrophic results.

It’s simple really. Edward Struzik, author of ‘Dark Days at Noon, The Future of Fire’ lays it out well.

‘We have been suppressing fires for so many decades in North America that we have forests that are older than they should be,’ he said. …

‘Prescribed burns are one of the best ways to mitigate the wildfire threat,’ he added.”

Nevertheless, the media are eager to blame climate change for any calamity. That’s one part simple naïveté on the part of young journalists, fresh off the turnip truck as it were, with little knowledge or inclination to understand the history and causes of underlying forest conditions. But many seasoned reporters are all too ready to support the climate change narrative as well. There’s also an element of calculated political misinformation in these claims, abetted by those seeking rents from government climate policies.

Wildfires are as old as time; without good forest management practices they are necessary for forest renewal. Agitation to sow climate panic based on wildfires is highly unscrupulous. There is no emergency except for the need to reform forest management, reduce the fuel load, and more generally, put an end to the waste of resources inherent in government climate change initiatives.

See this tweet! Hmmm.

The Impotence of AI for the Socialist Calculation Debate

05 Monday Jun 2023

Posted by Nuetzel in Artificial Intelligence, Central Planning, Markets

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Allocative efficiency, CATO Institute, central planning, Don Boudreaux, F.A. Hayek, incentives, Industrial Policy, Invisible Hand, Jason Kuznicki, Jesús Fernández-Villaverde, Knowledge Problem, Libertarianism.org, Machine Learning, Michael Munger, Opportunity cost, Protectionism, Robert Lucas, Socialist Calculation Debate

Recent advances in artificial intelligence (AI) are giving hope to advocates of central economic planning. Perhaps, they think, the so-called “knowledge problem” (KP) can be overcome, making society’s reliance on decentralized market forces “unnecessary”. The KP is the barrier faced by planners in collecting and using information to direct resources to their most valued uses. KP is at the heart of the so-called “socialist calculation debate”, but it applies also to the failures of right-wing industrial policies and protectionism.

Apart from raw political motives, run-of-the-mill government incompetence, and poor incentives, the KP is an insurmountable obstacle to successful state planning, as emphasized by Friedrich Hayek and many others. In contrast, market forces are capable of spontaneously harnessing all sources of information on preferences, incentives, resources, as well as existing and emergent technologies in allocating resources efficiently. In addition, the positive sum nature of mutually beneficial exchange makes the market by far the greatest force for voluntary social cooperation known to mankind.

Nevertheless, the hope kindled by AI is that planners would be on an equal footing with markets and allow them to intervene in ways that would be “optimal” for society. This technocratic dream has been astir for years along with advances in computer technology and machine learning. I guess it’s nice that at least a few students of central planning understood the dilemma all along, but as explained below, their hopes for AI are terribly misplaced. AI will never allow planners to allocate resources in ways that exceed or even approximate the efficiency of the market mechanism’s “invisible hand”.

Michael Munger recently described the basic misunderstanding about the information or “data” that markets use to solve the KP. Markets do not rely on a given set of prices, quantities, and production relationships. They do not take any of those as givens with respect to the evolution of transactions, consumption, production, investment, or search activity. Instead, markets generate this data based on unobservable and co-evolving factors such as the shape of preferences across goods, services, and time; perceptions of risk and its cost; the full breadth of technologies; shifting resource availabilities; expectations; locations; perceived transaction costs; and entrepreneurial energy. Most of these factors are “tacit knowledge” that no central database will ever contain.

At each moment, dispersed forces are applied by individual actions in the marketplace. The market essentially solves for the optimal set of transactions subject to all of those factors. These continuously derived solutions are embodied in data on prices, quantities, and production relationships. Opportunity costs and incentives are both an outcome of market processes as well as driving forces, so that they shape the transactional footprint. And then those trades are complete. Attempts to impose the same set of data upon new transactions in some repeated fashion, freezing the observable components of incentives and other requirements, would prevent the market from responding to changing conditions.

Thus, the KP facing planners isn’t really about “calculating” anything. Rather, it’s the impossibility of matching or replicating the market’s capacity to generate these data and solutions. There will never be an AI with sufficient power to match the efficiency of the market mechanism because it’s not a matter of mere “calculation”. The necessary inputs are never fully unobservable and, in any case, are unknown until transactions actually take place such that prices and quantities can be recorded.

In my 2020 post “Central Planning With AI Will Still Suck”, I reviewed a paper by Jesús Fernández-Villaverde (JFV), who was skeptical of AI’s powers to achieve better outcomes via planning than under market forces. His critique of the “planner position” anticipated the distinction highlighted by Munger between “market data” and the market’s continuous generation of transactions and their observable footprints.

JFV emphasized three reasons for the ultimate failure of AI-enabled planning: impossible data requirements; the endogeneity of expectations and behavior; and the knowledge problem. Again, the discovery and collection of “data” is a major obstacle to effective planning. If that were the only difficulty, then planners would have a mere “calculation” problem. This shouldn’t be conflated with the broader KP. That is, observable “data” is a narrow category relative the arrays of unobservables and the simultaneous generation of inputs and outcomes that takes place in markets. And these solutions are found by market processes subject to an array of largely unobservable constraints.

An interesting obstacle to AI planning cited by JFV is the endogeneity of expectations. It too can be considered part of the KP. From my 2020 post:

“Policy Change Often Makes the Past Irrelevant: Planning algorithms are subject to the so-called Lucas Critique, a well known principle in macroeconomics named after Nobel Prize winner Robert Lucas. The idea is that policy decisions based on observed behavior will change expectations, prompting responses that differ from the earlier observations under the former policy regime. … If [machine learning] is used to “plan” certain outcomes desired by some authority, based on past relationships and transactions, the Lucas Critique implies that things are unlikely to go as planned.”

Again, note that central planning and attempts at “calculation” are not solely in the province of socialist governance. They are also required by protectionist or industrial policies supported at times by either end of the political spectrum. Don Boudreaux offers this wisdom on the point:

“People on the political right typically assume that support for socialist interventions comes uniquely from people on the political left, but this assumption is mistaken. While conservative interventionists don’t call themselves “socialists,” many of their proposed interventions – for example, industrial policy – are indeed socialist interventions. These interventions are socialist because, in their attempts to improve the overall performance of the economy, proponents of these interventions advocate that market-directed allocations of resources be replaced with allocations carried out by government diktat.”

The hope that non-market planning can be made highly efficient via AI is a fantasy. In addition to substituting the arbitrary preferences of planners and politicians for those of private agents, the multiplicity of forces bearing on individual decisions will always be inaccessible to AIs. Many of these factors are deeply embedded within individual minds, and often in varying ways. That is why the knowledge problem emphasized by Hayek is much deeper than any sort of “calculation problem” fit for exploitation via computer power.

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Note: The image at the top of this post is attributed by Bing to the CATO Institute-sponsored website Libertarianism.org and an article that appeared there in 2013, though that piece, by Jason Kuznicki, no longer seems to feature that image.

No Radar, No Rudder: Fiscal & Monetary Destabilization

31 Wednesday May 2023

Posted by Nuetzel in Fiscal policy, Monetary Policy

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budget deficits, Credible Committments, crowding out, David Beckworth, David Henderson, Discretionary Spending, economic stimulus, Federal Reserve, Great Depression, Housing Bubble, Inflation Reduction Act, Long and Variable Lags, Lucas Critique, Mortgage Crisis, Pandemic Relief, Rational Expectations, Robert Lucas, Shovel-Ready Projects, Spending Multipliers, Stabilization policy, Tyler Cowen

Policy activists have long maintained that manipulating government policy can stabilize the economy. In other words, big spending initiatives, tax cuts, and money growth can lift the economy out of recessions, or budget cuts and monetary contraction can prevent overheating and inflation. However, this activist mirage burned away under the light of experience. It’s not that fiscal and monetary policy are powerless. It’s a matter of practical limitations that often cause these tools to be either impotent or destabilizing to the economy, rather than smoothing fluctuations in the business cycle.

The macroeconomics classes seem like yesterday: Keynesian professors lauded the promise of wise government stabilization efforts: policymakers could, at least in principle, counter economic shocks, particularly on the demand side. That optimistic narrative didn’t end after my grad school days. I endured many client meetings sponsored by macro forecasters touting the fine-tuning of fiscal and monetary policy actions. Some of those economists were working with (and collecting revenue from) government policymakers, who are always eager to validate their pretensions as planners (and saviors). However, seldom if ever do forecasters conduct ex post reviews of their model-spun policy scenarios. In fairness, that might be hard to do because all sorts of things change from initial conditions, but it definitely would not be in their interests to emphasize the record.

In this post I attempt to explain why you should be skeptical of government stabilization efforts. It’s sort of a lengthy post, so I’ve listed section headings below in case readers wish to scroll to points of most interest. Pick and choose, if necessary, though some context might get lost in the process.

Expectations Change the World
Fiscal Extravagance
Multipliers In the Real World
Delays
Crowding Out
Other Peoples’ Money
Tax Policy
Monetary Policy
Boom and Bust
Inflation Targeting
Via Rate Targeting
Policy Coordination
Who Calls the Tune?
Stable Policy, Stable Economy

Expectations Change the World

There were always some realists in the economics community. In May we saw the passing of one such individual: Robert Lucas was a giant intellect within the economics community, and one from whom I had the pleasure of taking a class as a graduate student. He was awarded the Nobel Prize in Economic Science in 1995 for his applications of rational expectations theory and completely transforming macro research. As Tyler Cowen notes, Keynesians were often hostile to Lucas’ ideas. I remember a smug classmate, in class, telling the esteemed Lucas that an important assumption was “fatuous”. Lucas fired back, “You bastard!”, but proceeded to explain the underlying logic. Cowen uses the word “charming” to describe the way Lucas disarmed his critics, but he could react strongly to rude ignorance.

Lucas gained professional fame in the 1970s for identifying a significant vulnerability of activist macro policy. David Henderson explains the famous “Lucas Critique” in the Wall Street Journal:

“… because these models were from periods when people had one set of expectations, the models would be useless for later periods when expectations had changed. While this might sound disheartening for policy makers, there was a silver lining. It meant, as Lucas’s colleague Thomas Sargent pointed out, that if a government could credibly commit to cutting inflation, it could do so without a large increase in unemployment. Why? Because people would quickly adjust their expectations to match the promised lower inflation rate. To be sure, the key is government credibility, often in short supply.”

Non-credibility is a major pitfall of activist macro stabilization policies that renders them unreliable and frequently counterproductive. And there are a number of elements that go toward establishing non-credibility. We’ll distinguish here between fiscal and monetary policy, focusing on the fiscal side in the next several sections.

Fiscal Extravagance

We’ve seen federal spending and budget deficits balloon in recent years. Chronic and growing budget deficits make it difficult to deliver meaningful stimulus, both practically and politically.

The next chart is from the most recent Congressional Budget Office (CBO) report. It shows the growing contribution of interest payments to deficit spending. Ever-larger deficits mean ever-larger amounts of debt on which interest is owed, putting an ever-greater squeeze on government finances going forward. This is particularly onerous when interest rates rise, as they have over the past few years. Both new debt is issued and existing debt is rolled over at higher cost.

Relief payments made a large contribution to the deficits during the pandemic, but more recent legislation (like the deceitfully-named Inflation Reduction Act) piled-on billions of new subsidies for private investments of questionable value, not to mention outright handouts. These expenditures had nothing to do with economic stabilization and no prayer of reducing inflation. Pissing away money and resources only hastens the debt and interest-cost squeeze that is ultimately unsustainable without massive inflation.

Hardly anyone with future political ambitions wants to address the growing entitlements deficit … but it will catch up with them. Social Security and Medicare are projected to exhaust their respective trust funds in the early- to mid-2030s, which will lead to mandatory benefit cuts in the absence of reform.

If it still isn’t obvious, the real problem driving the budget imbalance is spending, not revenue, as the next CBO chart demonstrates. The “emergency” pandemic measures helped precipitate our current stabilization dilemma. David Beckworth tweets that the relief measures “spurred a rapid recovery”, though I’d hasten to add that a wave of private and public rejection of extreme precautions in some regions helped as well. And after all, the pandemic downturn was exaggerated by misdirected policies including closures and lockdowns that constrained both the demand and supply sides. Beckworth acknowledges the relief measures “propelled inflation”, but the pandemic also seemed to leave us on a permanently higher spending path. Again, see the first chart below.

The second chart below shows that non-discretionary spending (largely entitlements) and interest outlays are how we got on that path. The only avenue for countercyclical spending is discretionary expenditures, which constitute an ever-smaller share of the overall budget.

We’ve had chronic deficits for years, but we’ve shifted to a much larger and continuing imbalance. With more deficits come higher interest costs, especially when interest rates follow a typical upward cyclical pattern. This creates a potentially explosive situation that is best avoided via fiscal restraint.

Putting other doubts about fiscal efficacy aside, it’s all but impossible to stimulate real economic activity when you’ve already tapped yourself out and overshot in the midst of a post-pandemic economic expansion.

Multipliers In the Real World

So-called spending multipliers are deeply beloved by Keynesians and pork-barrel spenders. These multipliers tell us that every dollar of extra spending ultimately raises income by some multiple of that dollar. This assumes that a portion of every dollar spent by government is re-spent by the recipient, and a portion of that is re-spent again by another recipient. But spending multipliers are never what they’re cracked up to be for a variety of reasons. (I covered these in “Multipliers Are For Politicians”, and also see this post.) There are leakages out of the re-spending process (income taxes, saving, imports), which trim the ultimate impact of new spending on income. When supply constraints bind on economic activity, fiscal stimulus will be of limited power in real terms.

If stimulus is truly expected to be counter-cyclical and transitory, as is generally claimed, then much of each dollar of extra government spending will be saved rather than spent. This is the lesson of the permanent income hypothesis. It means greater leakages from the re-spending stream and a lower multiplier. We saw this with the bulge in personal savings in the aftermath of pandemic relief payments.

Another side of this coin, however, is that cutting checks might be the government’s single-most efficient activity in execution, but it can create massive incentive problems. Some recipients are happy to forego labor market participation as long as the government keeps sending them checks, but at least they spend some of the income.

Delays

Another unappreciated and destabilizing downside of fiscal stimulus is that it often comes too late, just when the economy doesn’t need stimulus. That’s because a variety of delays are inherent in many spending initiatives: legislative, regulatory, legal challenges, planning and design, distribution to various spending authorities, and final disbursement. As I noted here:

“Even government infrastructure projects, heralded as great enhancers of American productivity, are often subject to lengthy delays and cost overruns due to regulatory and environmental rules. Is there any such thing as a federal ‘shovel-ready’ infrastructure project?”

Crowding Out

The supply of savings is limited, but when government borrows to fund deficits, it directly competes with private industry for those savings. Thus, funds that might otherwise pay for new plant, equipment, and even R&D are diverted to uses that should qualify as government consumption rather than long-term investment. Government competition for funds “crowds-out” private activity and impedes growth in the economy’s productive capacity. Thus, the effort to stimulate economic activity is self-defeating in some respects.

Other Peoples’ Money

Government doesn’t respond to price signals the way self-interested private actors do. This indifference leads to mis-allocated resources and waste. It extends to the creation of opportunities for graft and corruption, typically involving diversion of resources into uses that are of questionable productivity (corn ethanol, solar and wind subsidies).

Consider one other type of policy action perceived as counter-cyclical: federal bailouts of failing financial institutions or other troubled businesses. These rescues prop up unproductive enterprises rather than allowing waste to be flushed from the system, which should be viewed as a beneficial aspect of recession. The upshot is that too many efforts at economic stabilization are misdirected, wasteful, ill-timed, and pro-cyclical in impact.

Tax Policy

Like stabilization efforts on the spending side, tax changes may be badly timed. Tax legislation is often complex and can take time for consumers and businesses to adjust. In terms of traditional multiplier analysis, the initial impact of a tax change on spending is smaller than for expenditures, so tax multipliers are smaller. And to the extent that a tax change is perceived as temporary, it is made less effective. Thus, while changes in tax policy can have powerful real effects, they suffer from some of the same practical shortcomings for stabilization as changes in spending.

However, stimulative tax cuts, if well crafted, can boost disposable incomes and improve investment and work incentives. As temporary measures, that might mean an acceleration of certain kinds of activity. Tax increases reduce disposable incomes and may blunt incentives, or prompt delays in planned activities. Thus, tax policy may bear on the demand side as well as the timing of shifts in the economy’s productive potential or supply side.

Monetary Policy

Monetary policy is subject to problems of its own. Again, I refer to practical issues that are seemingly impossible for policy activists to overcome. Monetary policy is conducted by the nation’s central bank, the Federal Reserve (aka, the Fed). It is theoretically independent of the federal government, but the Fed operates under a dual mandate established by Congress to maintain price stability and full employment. Therein lies a basic problem: trying to achieve two goals that are often in conflict with a single policy tool.

Make no mistake: variations in money supply growth can have powerful effects. Nevertheless, they are difficult to calibrate due to “long and variable lags” as well as changes in money “velocity” (or turnover) often prompted by interest rate movements. Excessively loose money can lead to economic excesses and an overshooting of capacity constraints, malinvestment, and inflation. Swinging to a tight policy stance in order to correct excesses often leads to “hard landings”, or recession.

Boom and Bust

The Fed fumbled its way into engineering the Great Depression via excessively tight monetary policy. “Stop and go” policies in the 1970s led to recurring economic instability. Loose policy contributed to the housing bubble in the 2000s, and subsequent maladjustments led to a mortgage crisis (also see here). Don’t look now, but the inflationary consequences of the Fed’s profligacy during the pandemic prompted it to raise short-term interest rates in the spring of 2022. It then acted with unprecedented speed in raising rates over the past year. While raising rates is not always synonymous with tightening monetary conditions, money growth has slowed sharply. These changes might well lead to recession. Thus, the Fed seems given to a pathology of policy shifts that lead to unintentional booms and busts.

Inflation Targeting

The Fed claims to follow a so-called flexible inflation targeting policy. In reality, it has reacted asymmetrically to departures from its inflation targets. It took way too long for the Fed to react to the post-pandemic surge in inflation, dithering for months over whether the surge was “transitory”. It wasn’t, but the Fed was reluctant to raise its target rates in response to supply disruptions. At the same time, the Fed’s own policy actions contributed massively to demand-side price pressures. Also neglected is the reality that higher inflation expectations propel inflation on the demand side, even when it originates on the supply side.

Via Rate Targeting

At a more nuts and bolts level, today the Fed’s operating approach is to control money growth by setting target levels for several key short-term interest rates (eschewing a more direct approach to the problem). This relies on price controls (short-term interest rates being the price of liquidity) rather than allowing market participants to determine the rates at which available liquidity is allocated. Thus, in the short run, the Fed puts itself into the position of supplying whatever liquidity is demanded at the rates it targets. The Fed makes periodic adjustments to these rate targets in an effort to loosen or tighten money, but it can be misdirected in a world of high debt ratios in which rates themselves drive the growth of government borrowing. For example, if higher rates are intended to reduce money growth and inflation, but also force greater debt issuance by the Treasury, the approach might backfire.

Policy Coordination

While nominally independent, the Fed knows that a particular monetary policy stance is more likely to achieve its objectives if fiscal policy is not working at cross purposes. For example, tight monetary policy is more likely to succeed in slowing inflation if the federal government avoids adding to budget deficits. Bond investors know that explosive increases in federal debt are unlikely to be repaid out of future surpluses, so some other mechanism must come into play to achieve real long-term balance in the valuation of debt with debt payments. Only inflation can bring the real value of outstanding Treasury debt into line. Continuing to pile on new debt simply makes the Fed’s mandate for price stability harder to achieve.

Who Calls the Tune?

The Fed has often succumbed to pressure to monetize federal deficits in order to keep interest rates from rising. This obviously undermines perceptions of Fed independence. A willingness to purchase large amounts of Treasury bills and bonds from the public while fiscal deficits run rampant gives every appearance that the Fed simply serves as the Treasury’s printing press, monetizing government deficits. A central bank that is a slave to the spending proclivities of politicians cannot make credible inflation commitments, and cannot effectively conduct counter-cyclical policy.

Stable Policy, Stable Economy

Activist policies for economic stabilization are often perversely destabilizing for a variety of reasons. Good timing requires good forecasts, but economic forecasting is notoriously difficult. The magnitude and timing of fiscal initiatives are usually wrong, and this is compounded by wasteful planning, allocative dysfunction, and a general absence of restraint among political leaders as well as the federal bureaucracy..

Predicting the effects of monetary policy is equally difficult and, more often than not, leads to episodes of over- and under-adjustment. In addition, the wrong targets, the wrong operating approach, and occasional displays of subservience to fiscal pressure undermine successful stabilization. All of these issues lead to doubts about the credibility of policy commitments. Stated intentions are looked upon with doubt, increasing uncertainty and setting in motion behaviors that lead to undesirable economic consequences.

The best policies are those that can be relied upon by private actors, both as a matter of fulfilling expectations and avoiding destabilization. Federal budget policy should promote stability, but that’s not achievable institutions unable to constrain growth in spending and deficits. Budget balance would promote stability and should be the norm over business cycles, or perhaps over periods as long as typical 10-year budget horizons. Stimulus and restraint on the fiscal side should be limited to the effects of so-called automatic stabilizers, such as tax rates and unemployment compensation. On the monetary side, the Fed would do more to stabilize the economy by adopting formal rules, whether a constant rate of money growth or symmetric targeting of nominal GDP.

Health Care & Education: Slow Productivity Growth + Subsidies = Jacked Prices

14 Sunday May 2023

Posted by Nuetzel in Education, Health Care, Priductivity

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Abundance Agenda, Alex Tabarrok, Baumol's Disease, Beethoven’s String Quartet No. 14, CHIPS, competition, Consumer Sovereignty, Education Cost, Education Grants, Education Productivity, Employer-Paid Coversge, Eric Helland, Exchange subsidies, health care costs, Health Care Productivity, Industrial Concentration, Mark Perry, Medicaid, Medical Technology, Medicare, Obamacare, Peter Suderman, Relative Prices, Slow Productivity Growth, Student Loans, Subsidies, Tax Subsidies, third-party payments, Willian Baumol

This post is about relative prices in two major sectors of the U.S. economy, both of which are hindered by slow productivity growth while being among the most heavily subsidized: education and health care. Historically, both sectors have experienced rather drastic relative price increases, as illustrated for the past 20 years in the chart from Mark Perry above.

Baumol’s Cost Disease

These facts are hardly coincidental, though it’s likely the relative costs education and health care would have risen even in the absence of subsidies. Over long periods of time, the forces primarily guiding relative price movements are differentials in productivity growth. The tendency of certain industries to suffer from slow growth in productivity is the key to something known among economists as Baumol’s Disease, after the late William Baumol, who first described the phenomenon’s impact on relative prices.

Standards of living improve when a sufficient number of industries enjoy productivity growth. That creates a broad diffusion of new demands across many industries, including those less amenable to productivity growth, such as health care and education. But slow productivity growth and rising demand in these industries are imbalances that push their relative prices upward.

Alex Tabarrok and Eric Helland noted a few years ago that it took four skilled musicians 44 minutes to play Beethoven’s String Quartet No. 14 in 1826 and also in 2010, but the inflation-adjusted cost was 23 times higher. Services involving a high intensity of skilled labor are more prone to Baumol’s Disease than manufactured goods. As well, services for which demand is highly responsive to income or sectors characterized by monopoly power may be more prone to Baumol’s disease.

Tabarrok wonders whether we should really consider manifestations of Baumol’s Disease a blessing, because they show the extent to which productivity and real incomes have grown across the broader economy. So, rather than blame low productivity growth in certain services for their increasing relative prices, we should really blame (or thank) the rapid productivity growth in other sectors.

The Productivity Slog

There are unavoidable limits to the productivity growth of skilled educators, physicians, and other skilled workers in health care. Again, in a growing economy, prices of things in relatively fixed supply or those registering slow productivity gains will tend to rise more rapidly.

Technology offers certain advantages in some fields of education, but it’s hard to find evidence of broad improvement in educational success in the U.S. at any level. In the health care sector, new drugs often improve outcomes, as do advances in technologies such as drug delivery systems, monitoring devices, imaging, and robotic surgery. However, these advances don’t necessarily translate into improved capacity of the health care system to handle patients except at higher costs.

There’s been some controversy over the proper measurement of productivity in the health care sector. Some suggest that traditional measures of health care productivity are so flawed in capturing quality improvements that the meaning of prices themselves is distorted. They conclude that adjusting for quality can actually yield declines in effective health care prices. I’d interject, however, that patients and payers might harbor doubts about that assertion.

Other investigators note that while real advances in health care productivity should reduce costs, the degree of success varies substantially across different types of innovations and care settings. In particular, innovations in process and protocols seem to be more effective in reducing health care expenditures than adding new technologies to existing protocols or business models. All too often, medical innovations are of the latter variety. Ultimately, innovations in health care haven’t allowed a broader population of patients to be treated at low cost.

Superior Goods

Therefore, it appears that increases in the relative prices of education and health care over time have arisen as a natural consequence of the interplay between disparities in productivity growth and rising demand. Indeed, this goes a long way toward explaining the high cost of health care in the U.S. compared to other developed nations, as standards of living in the U.S. are well above nearly all others. In that respect, the cost of health care in the U.S. is not necessarily alarming. People demand more health care and education as their incomes rise, but delivering more health care isn’t easy. To paraphrase Tabarrok, turning steelworkers into doctors, nurses and teachers is a costly proposition.

The Role of Subsidies

In the clamor for scarce educational and health care resources, natural tensions over access have spilled into the political sphere. In pursuit of distributing these resources more equitably, public policy has relied heavily on subsidies. It shouldn’t surprise anyone that subsiding a service resistant to productivity gains will magnify the Baumol effect on relative price. One point is beyond doubt: the amounts of these subsidies is breathtaking.

Education: Public K -12 schools are largely funded by local taxpayers. Taxpayer-parents of school-aged children pay part of this cost whether they send their children to public schools or not. If they don’t, they must pay the additional cost of private or home schooling. This severely distorts the link between payments and the value assigned by actual users of public schools. It also confers a huge degree of market power to public schools, thus insulating them economically from performance pressures.

Public K – 12 schools are also heavily subsidized by state governments and federal grants. The following chart shows the magnitude and growth of K – 12 revenue per student over the past couple of decades.

Subsidies for higher education take the form of student aid, including federal student loans, grants to institutions, as well as a variety of tax subsidies. Here’s a nice breakdown:

This represents a mix of buyer and seller subsidies. That suggests less upward pressure on price and more stimulus to output, but we still run up against the limits to productivity growth noted above. Moreover, other constraints limit the effectiveness of these subsidies, such as lower academic qualifications in a broader student population and the potential for rewards in the job market to diminish with a potential excess of graduates.

Health care: Subsidies here are massive and come in a variety of forms. They often directly provide or reduce the cost of health insurance coverage: Medicaid, the Children’s Health Insurance Program (CHIP), Obamacare exchange subsidies, Medicare savings programs, tax-subsidies on employer-paid health coverage, and medical expense tax deductions. Within limits, these subsidies reduce the marginal cost of care patients are asked to pay, thus contributing to over-utilization of various kinds of care.

The following are CBO projections from June 2022. They are intended here to give an idea of the magnitude of health care insurance subsidies:

Still Other Dysfunctions

There are certainly other drivers of high costs in the provision of health care and education beyond a Baumol effect magnified by subsidies. The third-party payment system has contributed to a loss of price discipline in health care. While consumers are often responsible for paying at least part of their health insurance premiums, the marginal cost of health care to consumers is often zero, so they have little incentive to manage their demands.

Another impediment to cost control is a regulatory environment in health care that has led to a sharply greater concentration of hospital services and the virtual disappearance of independent provider practices. Competition has been sorely lacking in education as well. Subsidies flowing to providers with market power tend to exacerbate behaviors that would be punished in competitive markets, and not just pricing.

Summary

Baumol’s Disease can explain a lot about the patterns of relative prices shown in the chart at the top of this post. That pattern is a negative side effect of general growth in productivity. Unfortunately, it also reflects a magnification engendered by the payment of subsidies to sectors with slow productivity growth. The intent of these subsidies is to distribute health care and education more equitably, but the impact on relative prices undermines these objectives. The approach forces society to exert wasted energy, like an idiotic dog chasing its tail.

Peter Suderman wrote an excellent piece in which he discussed health care and education subsidies in the context of the so-called “abundance agenda”. His emphasis is on the futility of this agenda for the middle class, for which quality education and affordable health care always seem just out of reach. The malign effects of “abundance” policies are reinforced by anti-competitive regulation and payment mechanisms, which subvert market price discipline and consumer sovereignty. We’d be far better served by policies that restore consumer responsibility, deregulate providers, and foster competition in the delivery of health care and education.

Debt Ceiling Stopgaps and a Weak Legal Challenge

07 Sunday May 2023

Posted by Nuetzel in Federal Budget, Public debt

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Bank Liquidity, Biden Administration, Bing, Capital Gains Income, Chuck Schumer, Civil War, Debt Ceiling, Debt Limit Suspension, Default, Discharge Petition, Extraordinary Measures, Federal Deficits, Fourteenth Amendment, Google, Janet Yellen, Kevin McCarthy, Minting Coin, Modern Monetary Theary, Par Value, Perpetuities, Premium Bonds, Spending Restraint, statism

Long-awaited developments in the federal debt limit standoff shook loose in late April when Republicans passed a debt limit bill in the House of Representatives. Were it signed into law, the bill would extend the debt ceiling by about $1.5 trillion while incorporating elements of spending restraint. That approach is highly unpopular with democrats, but the zero-hour looms: Treasury Secretary Janet Yellen says the Treasury will run out of funds to pay all of the government’s obligations in early June. Soon we’ll have a better fix on President Biden’s response to the republicans, as he’s invited congressional leaders to the White House this Tuesday, May 8th to discuss the issue.

Biden wants a “clean” debt limit bill without changes impacting the budget path or existing appropriations. Senate Majority Leader Chuck Schumer would like to see a “clean” suspension of the debt limit. Republicans would like to use a debt limit extension to impose some spending restraint. They’ve focused only on the discretionary side of the budget, however, while much-needed reforms of mandatory programs like Social Security and Medicare were left aside. In fairness, both political parties have made massive contributions over the years to the burgeoning public debt, so not many are free of blame. But any time is a good time to try to enforce some fiscal discipline.

The Extraordinary Has Its Limits

Three months ago I wrote that the Treasury’s “extraordinary measures” to avoid breaching the debt limit would probably allow adequate time to break the impasse. In other words, accounting maneuvers allowed spending to continue without the sale of new debt. That bought some time, but perhaps not as much as hoped … tax filing season has revealed that revenue is coming in short of expectations, probably because weak asset markets have not generated anticipated levels of taxable capital gains income. In any case, very little progress was made over the past three months on settling the debt limit issue until the House passed the plan pushed by McCarthy. So we await the results of the pow-wow at the White House this week.

A Legislative Trick?

There’s been talk that House democrats will try to push through a “clean” debt limit bill of one sort or another by using a so-called discharge petition. They conveniently snuck this measure into an unrelated piece of legislation back in January. The upshot is that a bill meeting certain conditions must go to the floor for a vote if the discharge petition on the issue has at least 218 signatures. That means at least five republicans must join the democrats to force a vote and then join them again to pass a clean debt limit bill. That’s a long shot for democrats. Given the odds, will Biden deign to negotiate with House Speaker Kevin McCarthy? Even if he does, Biden will probably stall a while longer to extend the game of chicken. His hope would be for a few House republicans to lose their resolve for budget discipline in the face of looming default.

An Aside On Some Falsehoods

There’s a good measure of jingoistic BS surrounding the public debt. For example, you’ve probably heard from prominent voices in the debate that the U.S. has never defaulted on its debt and dad-gummit, it won’t start now! But the federal government has defaulted on its debt four times in the past! In three of those cases, the government reneged on commitments to convert bills or certificates into precious metals. The first default occurred during the Civil War, however, when the Union was unable to pay its war costs and subsequently went on a money printing binge. Unfortunately, we’re now engaged in a civil war of public versus private claims on resources, but the government can’t pay its bills without piling on debt. The statist forces now in control of the executive branch continue to insist that every American should demand more federal borrowing.

Here’s more BS in the form of linguistics that seemingly pervade all budget discussions these days: the House bill includes modest spending restraints, but mostly these are reductions in the growth of spending. Yet these are routinely described by democrats and the media as spending cuts. We could use another bill in the House demanding clear language that abides by the commonly accepted meaning of words. Fat chance!

The Trillion Dollar Coin

In my earlier debt limit post, I discussed two unconventional solutions to the Treasury’s financing dilemma. Both are conceived as short-term workarounds.

One is the minting of a $1 trillion platinum coin by the Treasury, which would deposit the coin at the Federal Reserve. The Fed would then sell back to the public (banks) existing Treasury bonds out of its massive holdings (> $8 trillion). The Treasury could then use the proceeds to pay the government’s bills. Thus, the Fed would do what the Treasury is prohibited from doing under the debt ceiling: selling debt.

When the debt ceiling is ultimately lifted, the “coin” process would be reversed (and the coin melted) without any impact on the money supply. As described, this is wholly different from earlier proposals to mint coins that would feed growth in the stock of money. Those were the brainchildren of so-called Modern Monetary Theorists and a few left-wing members of Congress.

There hasn’t been much discussion of “the coin” in recent months. In any case, the Fed would not be obligated to cooperate with the Treasury on this kind of workaround. The Fed has urged fiscal discipline, and it could simply refuse to take the coin if it felt that debt limit negotiations should be settled between Congress and the President.

Premium Bonds

The other workaround I discussed earlier is the sale by the Treasury of premium bonds or even perpetuities. This involves a little definitional trickery, as the debt limit is expressed in terms of the par value of debt. An example of premium bonds is given at the link above. High interest, low par bonds could be issued by the Treasury with the proceeds used to pay off older discounted bonds and pay the government’s bills. Perpetuities are an extreme case of premium bonds because they have zero par value and would not count against the debt limit at all. They simply pay interest forever with no return of principle. Paradoxically, perpetuities might also be less controversial because they would not involve payments to retire older debt.

Constitutional Challenge

The Biden Administration has pondered another way out of the jam, one that is perhaps more radical than either premium bonds or minting a big coin: challenge the debt ceiling on constitutional grounds. The idea is based on a clause in the Fourteenth Amendment stating that the: “validity of the public debt of the United States… shall not be questioned.” That’s an extremely vague provision. Presumably, as an amendment to the Constitution, this “rule” applies to the federal government itself, not to anyone dumping Treasury debt because its value is at risk. Any fair interpretation would dictate that the government should do nothing to undermine the value of outstanding public debt.

Let’s put aside the significant degree to which the real value of the public debt has been eroded historically by inflationary fiscal and monetary policy. That leaves us with the following questions:

Does a legislated debt limit (in and of itself) undermine the value of the public debt? Why would restraining the growth of debt or setting a limit on its quantity do such a thing?

Would a refusal to legislate an increase in the debt limit undermine or “question” the debt’s value? No, because belt-tightening is always a valid alternative to default. The Fourteenth Amendment is not a rationale for fiscal over-extension.
If we frame this as a question of default vs. fiscal restraint, only the former undermines the value of the debt.

From here, it looks like the blame for bringing the value of the public debt into question is squarely on the spendthrifts. Profligacy undermines the value of one’s commitments, so one can hardly blame those wishing to use the debt ceiling to promote fiscal responsibility. Any challenge to the debt ceiling based on the Fourteenth Amendment is likely to be guffawed out of court.

The Market’s Likely Rebuke

The market will probably react harshly if the debt ceiling impasse continues. That would bring higher yields on outstanding Treasury debt and a sharp worsening of the liquidity crisis for banks holding devalued Treasury debt. Naturally, Biden will attempt to blame the GOP for any bad outcome. His Treasury could attempt to buy more time by announcing the minting of a large coin or the sale of premium bonds, including perpetuities. Ultimately, neither of those moves would do much to stem the damage. The real problem is fiscal incontinence.

Some Critical Issues In the Gun Rights Debate

01 Monday May 2023

Posted by Nuetzel in Gun Rights, Second Amendment

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Antifa, ArmaLite Rifle, Assault Rifles, Auto Sears, Auto Switch, Black Market, Black on Black Violence, BLM, Brownshirts, Bump Stock, Defensive Gun Use, Defund the Police, Due Process, Enumerated Right, Feral Hogs, Fully Automatic, Gun Ownership, Gun-Free Zones, KKK, Machine Guns, Magazine Capacity, Mass Shootings, Mental Health, Politico, Rand Corporation, Red Flag Laws, Rep. Dan Crenshaw, Self-Defense, Semi-Automatic, Sporting Rifles, Tyranny, War on Drugs, Well-Regulated Militia

It’s long past time for me to revisit a few key issues surrounding gun rights, as well as a few sacred cows accepted uncritically by the press and nurtured by interventionists. Tragic gun violence and mass shootings have given rise to strong public reaction, but one undeniable result is that gun purchases have surged, bringing household gun ownership rates up sharply to levels of the 1980s and 1990s. This owes in part to the growing reality that police in many communities are under-resourced, unable to respond effectively to crimes and disorder in the wake of defunding and activist sentiment opposing police use of force. Under these circumstances, many private citizens believe they must be ready to defend themselves. And after all, even under better circumstances, counting on the ability of police to arrive and act promptly at a time of extreme need is a crap shoot.

As a preview, here’s a list of the sections/topics addressed below. You can skip what might not interest you, though earlier sections might provide more context.

What’s An “Assault Weapon”?
Deadlier Gun Modifications
Homicide Data
Crime and Gun Violence
Lone Wolf Psychopaths
Private Intervention and Reporting
Red Flag Laws
Defensive Gun Uses
Invitations To Kill
Second Amendment Protections

Modern Sporting Rifles

Not many politicians or people can define exactly what they mean by “assault weapons”, even those strongly opposed to … whatever they are. Scary looking things. Contrary to the implication promoted by the anti-gun lobby, what they call “assault rifles” today are not machine guns. Those have been heavily regulated since 1934, must be registered, and are now illegal for civilians to own if produced after May 19, 1986. In other words, what are frequently called “assault rifles” are not fully automatic weapons that fire a continuous stream of bullets. Rather, they are semiautomatic, which means they load the next bullet automatically but do not fire multiple bullets with a single pull of the trigger. You have to pull the trigger each time you fire a bullet. There are many semiautomatic handguns as well. Here’s a little history on semi-automatics:

“Semi-automatic, magazine-fed rifles were introduced to the civilian market here in the US in 1905. The US military adopted them about three decades later for use in World War II. … The civilian version of the modern sporting rifle, the AR-15, was introduced in 1956 so it has been with us for over six decades.”

So… it’s also misleading to call semiautomatics “military rifles” because they were originally produced for the civilian market. By the way, “AR” stands for ArmaLite Rifle, NOT “assault rifle”.

It’s more accurate to use the term “modern sporting rifle” for a semiautomatic today, rather than “assault rifle”. The vast bulk of the 15 million semiautomatic rifles held by the public were purchased for sport shooting, and people actually think they’re a lot of fun to shoot. Of course, they are also kept as a defensive weapons. By defensive, I include their use as a weapon against predators or invasive species on farms and ranches. If you don’t think that kind of weapon is especially useful for that purpose, remember that the task often involves firing with accuracy over a significant range. A modern sporting rifle is far superior to alternatives under those circumstances, especially when multiple shots at a moving target are likely to be necessary.

Obviously, a semiautomatic rifle is advantageous if there are multiple intruders. I was reminded of this by a recent article about feral hogs and the destruction they’re causing in the south, and especially in Texas. They breed fast and are so numerous that they are wreaking unprecedented damage to farms, ranches, and even suburban lawns and gardens. A handgun, shotgun, or a bolt action rifle won’t be nearly as effective against these beasts because they travel in groups of two to 30+.

Deadly Modifications

An accessory called an “auto sears” or “auto switch” can transform a semiautomatic pistol or rifle into a fully automatic weapon, but it’s a felony to possess an unregistered auto sears. Bump stocks allow semiautomatic rifles to fire more rapidly, sort of like machine guns, but they sacrifice accuracy. Bump stocks were outlawed a few years ago under an ATF rule, but their legality is still pending in court. These modifications do have legitimate uses, but I won’t argue the soundness of these bans other than to note their consistency with prior restrictions on machine guns. However, illegal bump stocks and auto sears circulate and they are easy to produce, so it’s not clear that these laws can ever produce their hoped-for result.

There are restrictions on magazine capacity in 13 states. The biggest problem with these restrictions is that they limit the effectiveness of defensive gun use. People miss their targets in high-pressure situations… a lot. Furthermore, dangerous confrontations often involve more than one attacker to defend against. Changing a magazine in the middle of all that presents a challenge that should be unnecessary. It’s no coincidence that 15+ bullet magazines are standard issue with some of the most popular guns on the market.

Homicide Data

It’s difficult to get refined data on the use of sporting rifles in gun homicides because reported categories of weapons are too broad. Nevertheless, we know semiautomatic rifles are not commonly used in violent crimes. There were 20,138 firearm deaths in the U.S. in 2022 excluding suicides, which is obviously tragic. In 2020, handguns were used in 59% of all gun homicides, while rifles (including semiautomatics) were used in just 3%. It’s possible these percentages undercount, as there is a sizable category labeled as “Type Not Stated”.

Mass shootings, defined by the FBI as four or more people killed, accounted for 3.2% of firearm deaths, for a total of 648 including deaths of shooters themselves. Rifles were used in about 30% of the mass shootings. That’s roughly consistent with the range of estimates shown in this 2021 report from the RAND Corporation.

It’s important to note that internationally, the U.S. has not been the outlier in mass public shootings that many believe it to be. In any case, you’ll hope in vain if you think a ban on sporting rifles will put a stop to mass shootings. In addition to interfering with the rights of millions of law-abiding gun owners, the decade-long ban on so-called assault weapons ending in 2004 had no impact on mass public shootings or any other type of crime (also see this post). Of course, there are plenty of other available means of committing mass murder, and there are plenty of illegal guns on the street, so this shouldn’t be a surprise.

One more important fact to bear in mind: despite efforts to convince us otherwise, gun violence is not the leading cause of death among children. By that I mean real children, not 18 – 19 year-old gang members. Kids age 12 and under die in car crashes at double the rate of gun deaths, for example.

Crime and Gun Violence

Gun violence has many causes, and criminal activity is foremost. According to this analysis, arguments or gang-related incidents accounted for 57% of 303 mass shooting deaths over a six-month period in 2021, while also accounting for more than 75% of the injuries. Much of this mayhem is black-on-black violence, and it’s odd that few seem willing to admit it. Law-abiding inner-city households and minorities just might have the most to gain from gun ownership.

A poorly conceived and politically motivated article in Politico claimed that gun violence was heavily concentrated in southern “red states”. The author’s heavy-handed attempt to focus on state-level statistics blurred more relevant distinctions. For example, he failed to emphasize the heavy concentration of gun violence in urban areas (which are heavily “blue”) and crime-ridden neighborhoods populated by those at the lowest rungs of the socioeconomic ladder.

The predominance of criminal and gang-related shootings suggests that major solutions to gun violence can be found within the criminal justice system: stiff bail, aggressive prosecution, and long sentences for criminal actions, whether gang-related or otherwise. Lately, we’ve been veering in the other direction.

On the other hand, gangs would be far less active and deadly if black market opportunities were minimized. Those tend to be created by government when it interferes with otherwise voluntary transactions. Most conspicuous in this regard is the prosecution of the drug war. This creates risk-fueled profits for dealing and trafficking that are highly enticing to hard-luck gang members. Unfortunately, competitive pressure on the black market often takes violent forms. Legalization or even decriminalization of a wider assortment of drugs would undercut black market profitability, however. This approach would be far more effective if governments avoid imposing high taxes on newly-legalized drugs, because taxes simply recreate black-market opportunities.

Psychopathic Homicide

It’s no secret that severe mental illness can lead to acts of violence, including mass shootings. One analysis found that so-called “lone wolf” attacks accounted for 15% of mass shooting deaths and less than 5% of injuries during the first half of 2021.

We can probably all agree that anyone in the grips of a severe psychosis should not be in possession of guns. The obvious problem is that we can’t easily identify such persons without severe infringements on constitutional rights. Furthermore, we won’t always accurately identify true threats and we’ll mistakenly finger some harmless individuals. So how do we decide who’s really and legally crazy? Can we agree on some threshold of craziness and who meets it? Respect for civil liberties demands restraint in limiting individual rights without just cause. The revocation of a person’s Second Amendment rights should require a high degree of certainty that the individual is a threat.

Not all disturbed individuals seek or ever receive care, and not all disturbed individuals are dangerous, so attempting to identifying them through their utilization of mental health care is imperfect at best. Indeed, most mass shooters are thought to have had an undiagnosed disorder. Should a therapist be required to report to authorities a patient whom they’ve diagnosed as psychotic or dangerous? Would that be sufficient cause to confiscate a patient’s guns? That is not as straightforward for therapists as it might seem:

“Mandatory reporting of persons believed to be at imminent risk for committing violence or attempting suicide can pose an ethical dilemma for physicians, who might find themselves struggling to balance various conflicting interests. Legal statutes dictate general scenarios that require mandatory reporting to supersede confidentiality requirements, but physicians must use clinical judgment to determine whether and when a particular case meets the requirement. In situations in which it is not clear whether reporting is legally required, the situation should be analyzed for its benefit to the patient and to public safety. Access to firearms can complicate these situations, as firearms are a well-established risk factor for violence and suicide yet also a sensitive topic about which physicians and patients might have strong personal beliefs.”

If physicians or therapists approach these questions with the greatest deference to public safety, we’re liable to see a lot fewer people seeking therapy. I would not rule out, however, that such deference might be the best for society.

Private Intervention and Reporting

Less formal mechanisms to promote public safety require vigilance by private individuals, families, and other groups. A large number of perpetrators of mass killings were known to be deeply troubled well beforehand by family and/or acquaintances. Signs of maladjustment in loved ones are easily dismissed or forgiven, but families must take great responsibility for the potential actions of their own. Seeking therapeutic help is one thing, but when a family member shows more obvious signs of psychosis, then it might be time for contact with authorities and possibly institutionalization.

There have also been many cases in which mass killers have previewed their violent thoughts on-line. Anyone connected with such an individual on social media or witnessing deranged behavior should not hesitate to contact police to intervene. Of course, things aren’t always clear cut, but it’s important to be attentive and take responsible action when an individual’s behavior appears to take an ominous turn. This too can be abused, and authorities must be fair-minded about reviewing reports of threats to be sure they aren’t motivated by petty differences, whether personal, business, or political. This is at the heart of the right to due process of law under the Fifth and Fourteenth Amendments of the Constitution.

Red Flag Laws

Among the proposals for reducing gun violence are additional measures for controlling ownership and access to guns. Red flag laws are intended to restrict more formally and comprehensively the ability of persons at risk of harming themselves or others from owning or acquiring guns. At present, 19 states and DC have some form of red flag law(s), while one state (OK) has enacted an anti-red flag law.

Broadly, restrictions on gun possession, whether technically part of a red flag law or otherwise, can be invoked on account of age (< 21), a federal or state criminal record, a documented alcohol or drug addiction, a formally diagnosed mental illness, or a pattern of threatening or suicidal behavior. The latter may include threats arising from domestic disputes. All of these possibilities are potentially troublesome from the perspective of civil liberty, but under red flag laws, usually a court order is required to enforce the restriction. The key point is that the individual in question must have due process rights before restrictions are imposed or guns are confiscated. Otherwise, as Rep. Dan Crenshaw (TX) objects:

“What you’re essentially trying to do with the red flag law is enforce the law before the law has been broken. And it’s a really difficult thing to do, it’s difficult to assess whether somebody is a threat. Now if they are such a threat that they’re threatening somebody with a weapon already, well, then they’ve already broken the law. So why do you need this other law?”

The answer to Crenshaw’s question is that mere threats are difficult to prosecute. Likewise, it should be difficult to revoke anyone’s Second Amendment rights. Red flag laws should ensure that anyone whose gun rights are under review will receive due process. A huge difficulty is that such reviews must be speedy. If a real danger is convincingly shown to exist, then guns are confiscated and/or the individual is placed on a red flag list, at least temporarily.

Defensive Gun Use

One of the most under-reported phenomena in the gun debate is that of defensive gun uses (DGUs), which are hard to count because they often go unreported. One component of DGUs is so-called justifiable homicide by police and private citizens, which (when reported) typically contribute 700 – 800 deaths to total homicides each year. However, a DGU does not imply that a shot is fired or that a gun is pointed in the direction of a criminal threat. At a minimum, it means a threat was deterred by the presence of an armed defender.

The 2021 Georgetown National Firearms Survey reported an estimated 1.67 million DGUs per year. Of these, 25% occur inside the gun owner’s home and another 54% on their property. There is no question that DGUs save lives, and probably many thousands of lives every year. There is also no doubt that the prospect of an armed defender inside a home or business deters criminals.

Killing Zones

As one might gather from the evidence on DGUs, one of the most misguided efforts to promote safety within environments like schools and churches is their designation as “gun-free zones”. This is an invitation to anyone crazy enough to perpetrate deadly violence against large numbers of innocents, as we learned once more in the recent Nashville school shooting. Someone on staff should be trained and always armed with a gun, whether that be a resource officer, another employee, or a volunteer. Preferably several designated individuals would be armed in buildings such as large schools, or perhaps one or two trusted and designated volunteers at gatherings in houses of worship.

Second Amendment Protections

Second Amendment rights are critical to effective self-defense, which is usually a matter of protecting one’s life and property from thieves, home invaders, and predatory or destructive beasts. Anti-gun radicals find even this rationale objectionable, demonstrating no regard for gun rights whatsoever. Another claim is that the right to bear arms was given specific purpose only by the need to maintain “a well-regulated militia”, and it is further asserted that this need is out-dated.

Despite those objections, a right’s stated purpose in the text of the Constitution does not by itself define any limit on its applicability. The fact that the Second Amendment recognizes and enumerates gun rights gives emphasis to the founders’ awareness that gun-grabbers might push any advantage were that right to be left unenumerated. Furthermore, a civilian militia, whether formal or informal, might well be needed to defend against any tyrannical force as might arise in the event of a breakdown of the constitutional order.

I’m willing to stipulate that there is no immediate threat today of physical coercion by government intended to subjugate classes of individuals, or of any federal military aggression against the sovereignty of any state. That may owe in part to private gun ownership, however, which deters against open acts of tyranny. It also tends to foster a preference for more nuanced applications of government power. There’s no need for privately-owned tanks, fighter aircraft, and missiles to offer meaningful deterrence. Direct, bloody confrontations are a bad look and no way to gain broad support for other forms of coercion by government.

A better alternative for regimes or political movements who wish to radically change the social order is to offer subtle and plausibly deniable encouragement of destructive or coercive acts by proxy forces (e.g., Brownshirts, Antifa, BLM, KKK). While possession of guns by these proxies can make them more dangerous, a general public under arms is not as vulnerable as an unarmed population. Private gun owners can defend themselves more effectively and represent a significant and healthy impediment to extensions of political power of this nature.

The Scary Progress and Hairy Promise of AI

18 Tuesday Apr 2023

Posted by Nuetzel in Artificial Intelligence, Existential Threats, Growth

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Agentic Behavior, AI Bias, AI Capital, AI Risks, Alignment, Artificial Intelligence, Ben Hayum, Bill Gates, Bryan Caplan, ChatGPT, Clearview AI, Dumbing Down, Eliezer Yudkowsky, Encryption, Existential Risk, Extinction, Foom, Fraud, Generative Intelligence, Greta Thunberg, Human capital, Identity Theft, James Pethokoukis, Jim Jones, Kill Switch, Labor Participation Insurance, Learning Language Models, Lesswrong, Longtermism, Luddites, Mercatus Center, Metaculus, Nassim Taleb, Open AI, Over-Employment, Paul Ehrlich, Pause Letter, Precautionary Principle, Privacy, Robert Louis Stevenson, Robin Hanson, Seth Herd, Synthetic Media, TechCrunch, TruthGPT, Tyler Cowen, Universal Basic Income

Artificial intelligence (AI) has become a very hot topic with incredible recent advances in AI performance. It’s very promising technology, and the expectations shown in the chart above illustrate what would be a profound economic impact. Like many new technologies, however, many find it threatening and are reacting with great alarm, There’s a movement within the tech industry itself, partly motivated by competitive self-interest, calling for a “pause”, or a six-month moratorium on certain development activities. Politicians in Washington are beginning to clamor for legislation that would subject AI to regulation. However, neither a voluntary pause nor regulatory action are likely to be successful. In fact, either would likely do more harm than good.

Leaps and Bounds

The pace of advance in AI has been breathtaking. From ChatGPT 3.5 to ChatGPT 4, in a matter of just a few months, the tool went from relatively poor performance on tests like professional and graduate entrance exams (e.g., bar exams, LSAT, GRE) to very high scores. Using these tools can be a rather startling experience, as I learned for myself recently when I allowed one to write the first draft of a post. (Despite my initial surprise, my experience with ChatGPT 3.5 was somewhat underwhelming after careful review, but I’ve seen more impressive results with ChatGPT 4). They seem to know so much and produce it almost instantly, though it’s true they sometimes “hallucinate”, reflect bias, or invent sources, so thorough review is a must.

Nevertheless, AIs can write essays and computer code, solve complex problems, create or interpret images, sounds and music, simulate speech, diagnose illnesses, render investment advice, and many other things. They can create subroutines to help themselves solve problems. And they can replicate!

As a gauge of the effectiveness of models like ChatGPT, consider that today AI is helping promote “over-employment”. That is, there are a number of ambitious individuals who, working from home, are holding down several different jobs with the help of AI models. In fact, some of these folks say AIs are doing 80% of their work. They are the best “assistants” one could possibly hire, according to a man who has four different jobs.

Economist Bryan Caplan is an inveterate skeptic of almost all claims that smack of hyperbole, and he’s won a series of bets he’s solicited against others willing to take sides in support of such claims. However, Caplan thinks he’s probably lost his bet on the speed of progress on AI development. Needless to say, it has far exceeded his expectations.

Naturally, the rapid progress has rattled lots of people, including many experts in the AI field. Already, we’re witnessing the emergence of “agency” on the part of AI Learning Language Models (LLMs), or so called “agentic” behavior. Here’s an interesting thread on agentic AI behavior. Certain models are capable of teaching themselves in pursuit of a specified goal, gathering new information and recursively optimizing their performance toward that goal. Continued gains may lead to an AI model having artificial generative intelligence (AGI), a superhuman level of intelligence that would go beyond acting upon an initial set of instructions. Some believe this will occur suddenly, which is often described as the “foom” event.

Team Uh-Oh

Concern about where this will lead runs so deep that a letter was recently signed by thousands of tech industry employees, AI experts, and other interested parties calling for a six-month worldwide pause in AI development activity so that safety protocols can be developed. One prominent researcher in machine intelligence, Eliezer Yudkowsky, goes much further: he believes that avoiding human extinction requires immediate worldwide limits on resources dedicated to AI development. Is this a severely overwrought application of the precautionary principle? That’s a matter I’ll consider at greater length below, but like Caplan, I’m congenitally skeptical of claims of impending doom, whether from the mouth of Yudkowsky, Greta Thunberg, Paul Ehrlich, or Nassim Taleb.

As I mentioned at the top, I suspect competition among AI developers played a role in motivating some of the signatories of the “AI pause” letter, and some of the non-signatories as well. Robin Hanson points out that Sam Altman, the CEO of OpenAI, did not sign the letter. OpenAI (controlled by a nonprofit foundation) owns ChatGPT and is the current leader in rolling out AI tools to the public. ChatGPT 4 can be used with the Microsoft search engine Bing, and Microsoft’s Bill Gates also did not sign the letter. Meanwhile, Google was caught flat-footed by the ChatGPT rollout, and its CEO signed. Elon Musk (who signed) wants to jump in with his own AI development: TruthGPT. Of course, the pause letter stirred up a number of members of Congress, which I suspect was the real intent. It’s reasonable to view the letter as a means of leveling the competitive landscape. Thus, it looks something like a classic rent-seeking maneuver, buttressed by the inevitable calls for regulation of AIs. However, I certainly don’t doubt that a number of signatories did so out of a sincere belief that the risks of AI must be dealt with before further development takes place.

The vast dimensions of the supposed AI “threat” may have some libertarians questioning their unequivocal opposition to public intervention. If so, they might just as well fear the potential that AI already holds for manipulation and control by central authorities in concert with their tech and media industry proxies. But realistically, broad compliance with any precautionary agreement between countries or institutions, should one ever be reached, is pretty unlikely. On that basis, a “scout’s honor” temporary moratorium or set of permanent restrictions might be comparable to something like the Paris Climate Accord. China and a few other nations are unlikely to honor the agreement, and we really won’t know whether they’re going along with it except for any traceable artifacts their models might leave in their wake. So we’ll have to hope that safeguards can be identified and implemented broadly.

Likewise, efforts to regulate by individual nations are likely to fail, and for similar reasons. One cannot count on other powers to enforce the same kinds of rules, or any rules at all. Putting our faith in that kind of cooperation with countries who are otherwise hostile is a prescription for ceding them an advantage in AI development and deployment. Regulation of the evolution of AI will likely fail. As Robert Louis Stevenson once wrote, “Thus paternal laws are made, thus they are evaded”. And if it “succeeds, it will leave us with a technology that will fall short of its potential to benefit consumers and society at large. That, unfortunately, is usually the nature of state intrusion into a process of innovation, especially when devised by a cadre of politicians with little expertise in the area.

Again, according to experts like Yudkowsky, AGI would pose serious risks. He thinks the AI Pause letter falls far short of what’s needed. For this reason, there’s been much discussion of somehow achieving an alignment between the interests of humanity and the objectives of AIs. Here is a good discussion by Seth Herd on the LessWrong blog about the difficulties of alignment issues.

Some experts feel that alignment is an impossibility, and that there are ways to “live and thrive” with unalignment (and see here). Alignment might also be achieved through incentives for AIs. Those are all hopeful opinions. Others insist that these models still have a long way to go before they become a serious threat. More on that below. Of course, the models do have their shortcomings, and current models get easily off-track into indeterminacy when attempting to optimize toward an objective.

But there’s an obvious question that hasn’t been answered in full: what exactly are all these risks? As Tyler Cowen has said, it appears that no one has comprehensively catalogued the risks or specified precise mechanisms through which those risks would present. In fact, AGI is such a conundrum that it might be impossible to know precisely what threats we’ll face. But even now, with deployment of AIs still in its infancy, it’s easy to see a few transition problems on the horizon.

White Collar Wipeout

Job losses seem like a rather mundane outcome relative to extinction. Those losses might come quickly, particularly among white collar workers like programmers, attorneys, accountants, and a variety of administrative staffers. According to a survey of 1,000 businesses conducted in February:

“Forty-eight percent of companies have replaced workers with ChatGPT since it became available in November of last year. … When asked if ChatGPT will lead to any workers being laid off by the end of 2023, 33% of business leaders say ‘definitely,’ while 26% say ‘probably.’ … Within 5 years, 63% of business leaders say ChatGPT will ‘definitely’ (32%) or ‘probably’ (31%) lead to workers being laid off.”

A rapid rate of adoption could well lead to widespread unemployment and even social upheaval. For perspective, that implies a much more rapid rate of technological diffusion than we’ve ever witnessed, so this outcome is viewed with skepticism in some quarters. But in fact, the early adoption phase of AI models is proceeding rather quickly. You can use ChatGPT 4 easily enough on the Bing platform right now!

Contrary to the doomsayers, AI will not just enhance human productivity. Like all new technologies, it will lead to opportunities for human actors that are as yet unforeseen. AI is likely to identify better ways for humans to do many things, or do wonderful things that are now unimagined. At a minimum, however, the transition will be disruptive for a large number of workers, and it will take some time for new opportunities and roles for humans to come to fruition.

Robin Hanson has a unique proposal for meeting the kind of challenge faced by white collar workers vulnerable to displacement by AI, or for blue collar workers who are vulnerable to displacement by robots (the deployment of which has been hastened by minimum wage and living wage activism). This treatment of Hanson’s idea will be inadequate, but he suggests a kind of insurance or contract sold to both workers and investors by owners of assets likely to be insensitive to AI risks. The underlying assets are paid out to workers if automation causes some defined aggregate level of job loss. Otherwise, the assets are paid out to investors taking the other side of the bet. Workers could buy these contracts themselves, or employers could do so on their workers’ behalf. The prices of the contracts would be determined by a market assessment of the probability of the defined job loss “event”. Governmental units could buy the assets for their citizens, for that matter. The “worker contracts” would be cheap if the probability of the job-loss event is low. Sounds far-fetched, but perhaps the idea is itself an entrepreneurial opportunity for creative players in the financial industry.

The threat of job losses to AI has also given new energy to advocates of widespread adoption of universal basic income payments by government. Hanson’s solution is far preferable to government dependence, but perhaps the state could serve as an enabler or conduit through which workers could acquire AI and non-AI capital.

Human Capital

Current incarnations of AI are not just a threat to employment. One might add the prospect that heavy reliance on AI could undermine the future education and critical thinking skills of the general population. Essentially allowing machines to do all the thinking, research, and planning won’t inure to the cognitive strength of the human race, especially over several generations. Already people suffer from an inability to perform what were once considered basic life skills, to say nothing of tasks that were fundamental to survival in the not too distant past. In other words, AI could exaggerate a process of “dumbing down” the populace, a rather undesirable prospect.

Fraud and Privacy

AI is responsible for still more disruptions already taking place, in particular violations of privacy, security, and trust. For example, a company called Clearview AI has scraped 30 billion photos from social media and used them to create what its CEO proudly calls a “perpetual police lineup”, which it has provided for the convenience of law enforcement and security agencies.

AI is also a threat to encryption in securing data and systems. Conceivably, AI could be of value in perpetrating identity theft and other kinds of fraud, but it can also be of value in preventing them. AI is also a potential source of misleading information. It is often biased, reflecting specific portions of the on-line terrain upon which it is trained, including skewed model weights applied to information reflecting particular points of view. Furthermore, misinformation can be spread by AIs via “synthetic media” and the propagation of “fake news”. These are fairly clear and present threats of social, economic, and political manipulation. They are all foreseeable dangers posed by AI in the hands of bad actors, and I would include certain nudge-happy and politically-motivated players in that last category.

The Sky-Already-Fell Crowd

Certain ethicists with extensive experience in AI have condemned the signatories of the “Pause Letter” for a focus on “longtermism”, or risks as yet hypothetical, rather than the dangers and wrongs attributable to AIs that are already extant: TechCrunch quotes a rebuke penned by some of these dissenting ethicists to supporters of the “Pause Letter”:

“‘Those hypothetical risks are the focus of a dangerous ideology called longtermism that ignores the actual harms resulting from the deployment of AI systems today,’ they wrote, citing worker exploitation, data theft, synthetic media that props up existing power structures and the further concentration of those power structures in fewer hands.”

So these ethicists bemoan AI’s presumed contribution to the strength and concentration of “existing power structures”. In that, I detect just a whiff of distaste for private initiative and private rewards, or perhaps against the sovereign power of states to allow a laissez faire approach to AI development (or to actively sponsor it). I have trouble taking this “rebuke” too seriously, but it will be fruitless in any case. Some form of cooperation between AI developers on safety protocols might be well advised, but competing interests also serve as a check on bad actors, and it could bring us better solutions as other dilemmas posed by AI reveal themselves.

Imagining AI Catastrophes

What are the more consequential (and completely hypothetical) risks feared by the “pausers” and “stoppers”. Some might have to do with the possibility of widespread social upheaval and ultimately mayhem caused by some of the “mundane” risks described above. But the most noteworthy warnings are existential: the end of the human race! How might this occur when AGI is something confined to computers? Just how does the supposed destructive power of AGIs get “outside the box”? It must do so either by tricking us into doing something stupid, hacking into dangerous systems (including AI weapons systems or other robotics), and/or through the direction and assistance of bad human actors. Perhaps all three!

The first question is this: why would an AGI do anything so destructive? No matter how much we might like to anthropomorphize an “intelligent” machine, it would still be a machine. It really wouldn’t like or dislike humanity. What it would do, however, is act on its objectives. It would seek to optimize a series of objective functions toward achieving a goal or a set of goals it is given. Hence the role for bad actors. Let’s face it, there are suicidal people who might like nothing more than to take the whole world with them.

Otherwise, if humanity happens to be an obstruction to solving an AGI’s objective, then we’d have a very big problem. Humanity could be an aid to solving an AGI’s optimization problem in ways that are dangerous. As Yudkowsky says, we might represent mere “atoms it could use somewhere else.” And if an autonomous AGI were capable of setting it’s own objectives, without alignment, the danger would be greatly magnified. An example might be the goal of reducing carbon emissions to pre-industrial levels. How aggressively would an AGI act in pursuit of that goal? Would killing most humans contribute to the achievement of that goal?

Here’s one that might seem far-fetched, but the imagination runs wild: some individuals might be so taken with the power of vastly intelligent AGI as to make it an object of worship. Such an “AGI God” might be able to convert a sufficient number of human disciples to perpetrate deadly mischief on its behalf. Metaphorically speaking, the disciples might be persuaded to deliver poison kool-aid worldwide before gulping it down themselves in a Jim Jones style mass suicide. Or perhaps the devoted will survive to live in a new world mono-theocracy. Of course, these human disciples would be able to assist the “AGI God” in any number of destructive ways. And when brain-wave translation comes to fruition, they better watch out. Only the truly devoted will survive.

An AGI would be able to create the illusion of emergency, such as a nuclear launch by an adversary nation. In fact, two or many adversary nations might each be fooled into taking actions that would assure mutual destruction and a nuclear winter. If safeguards such as human intermediaries were required to authorize strikes, it might still be possible for an AGI to fool those humans. And there is no guarantee that all parties to such a manufactured conflict could be counted upon to have adequate safeguards, even if some did.

Yudkowsky offers at least one fairly concrete example of existential AGI risk:

“A sufficiently intelligent AI won’t stay confined to computers for long. In today’s world you can email DNA strings to laboratories that will produce proteins on demand, allowing an AI initially confined to the internet to build artificial life forms or bootstrap straight to postbiological molecular manufacturing.”

There are many types of physical infrastructure or systems that an AGI could conceivably compromise, especially with the aid of machinery like robots or drones to which it could pass instructions. Safeguards at nuclear power plants could be disabled before steps to trigger melt down. Water systems, rivers, and bodies of water could be poisoned. The same is true of food sources, or even the air we breathe. In any case, complete social disarray might lead to a situation in which food supply chains become completely dysfunctional. So, a super-intelligence could probably devise plenty of “imaginative” ways to rid the earth of human beings.

Back To Earth

Is all this concern overblown? Many think so. Bryan Caplan now has a $500 bet with Eliezer Yudkowsky that AI will not exterminate the human race by 2030. He’s already paid Yudkowsky, who will pay him $1,000 if we survive. Robin Hanson says “Most AI Fear Is Future Fear”, and I’m inclined to agree with that assessment. In a way, I’m inclined to view the AI doomsters as highly sophisticated, change-fearing Luddites, but Luddites nevertheless.

Ben Hayum is very concerned about the dangers of AI, but writing at LessWrong, he recognizes some real technical barriers that must be overcome for recursive optimization to be successful. He also notes that the big AI developers are all highly focused on safety. Nevertheless, he says it might not take long before independent users are able to bootstrap their own plug-ins or modules on top of AI models to successfully optimize without running off the rails. Depending on the specified goals, he thinks that will be a scary development.

James Pethokoukis raises a point that hasn’t had enough recognition: successful innovations are usually dependent on other enablers, such as appropriate infrastructure and process adaptations. What this means is that AI, while making spectacular progress thus far, won’t have a tremendous impact on productivity for at least several years, nor will it pose a truly existential threat. The lag in the response of productivity growth would also limit the destructive potential of AGI in the near term, since installation of the “social plant” that a destructive AGI would require will take time. This also buys time for attempting to solve the AI alignment problem.

In another Robin Hanson piece, he expresses the view that the large institutions developing AI have a reputational Al stake and are liable for damages their AI’s might cause. He notes that they are monitoring and testing AIs in great detail, so he thinks the dangers are overblown.:

“So, the most likely AI scenario looks like lawful capitalism…. Many organizations supply many AIs and they are pushed by law and competition to get their AIs to behave in civil, lawful ways that give customers more of what they want compared to alternatives.”

In the longer term, the chief focus of the AI doomsters, Hanson is truly an AI optimist. He thinks AGIs will be “designed and evolved to think and act roughly like humans, in order to fit smoothly into our many roughly-human-shaped social roles.” Furthermore, he notes that AI owners will have strong incentives to monitor and “delimit” AI behavior that runs contrary to its intended purpose. Thus, a form of alignment is achieved by virtue of economic and legal incentives. In fact, Hanson believes the “foom” scenario is implausible because:

“… it stacks up too many unlikely assumptions in terms of our prior experiences with related systems. Very lumpy tech advances, techs that broadly improve abilities, and powerful techs that are long kept secret within one project are each quite rare. Making techs that meet all three criteria even more rare. In addition, it isn’t at all obvious that capable AIs naturally turn into agents, or that their values typically change radically as they grow. Finally, it seems quite unlikely that owners who heavily test and monitor their very profitable but powerful AIs would not even notice such radical changes.”

As smart as AGIs would be, Hanson asserts that the problem of AGI coordination with other AIs, robots, and systems would present insurmountable obstacles to a bloody “AI revolution”. This is broadly similar to Pethokoukis’ theme. Other AIs or AGIs are likely to have competing goals and “interests”. Conflicting objectives and competition of this kind will do much to keep AGIs honest and foil malign AGI behavior.

The kill switch is a favorite response of those who think AGI fears are exaggerated. Just shut down an AI if its behavior is at all aberrant, or if a user attempts to pair an AI model with instructions or code that might lead to a radical alteration in an AI’s level of agency. Kill switches would indeed be effective at heading off disaster if monitoring and control is incorruptible. This is the sort of idea that begs for a general solution, and one hopes that any advance of that nature will be shared broadly.

One final point about AI agency is whether autonomous AGIs might ever be treated as independent factors of production. Could they be imbued with self-ownership? Tyler Cowen asks whether an AGI created by a “parent” AGI could legitimately be considered an independent entity in law, economics, and society. And how should income “earned” by such an AGI be treated for tax purposes. I suspect it will be some time before AIs, including AIs in a lineage, are treated separately from their “controlling” human or corporate entities. Nevertheless, as Cowen says, the design of incentives and tax treatment of AI’s might hold some promise for achieving a form of alignment.

Letting It Roll

There’s plenty of time for solutions to the AGI threat to be worked out. As I write this, the consensus forecast for the advent of real AGI on the Metaculus online prediction platform is July 27, 2031. Granted, that’s more than a year sooner than it was 11 days ago, but it still allows plenty of time for advances in controlling and bounding agentic AI behavior. In the meantime, AI is presenting opportunities to enhance well being through areas like medicine, nutrition, farming practices, industrial practices, and productivity enhancement across a range of processes. Let’s not forego these opportunities. AI technology is far too promising to hamstring with a pause, moratoria, or ill-devised regulations. It’s also simply impossible to stop development work on a global scale.

Nevertheless, AI issues are complex for all private and public institutions. Without doubt, it will change our world. This AI Policy Guide from Mercatus is a helpful effort to lay out issues at a high-level.