Monthly Archives: June 2023

Biden OMB Suggests Minimal Discounts of Future Benefits

28 Wednesday Jun 2023

Posted by in Big Government, Risk, Tradeoffs

≈ Leave a comment

Tags

, , , , , , , , , , , , , , , ,

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 in Inflation, Monetary Policy

≈ Leave a comment

Tags

, , , , , , , , , , , , , , , , , , ,

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 in Forest Fires, Global Warming, Wildfires

≈ Leave a comment

Tags

, , , , , , , , , , , ,

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 in Artificial Intelligence, Central Planning, Markets

≈ Leave a comment

Tags

, , , , , , , , , , , , , , , , ,

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.

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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.