Imagine a criminal justice system with such a high degree of effectiveness that 100% of crimes are immediately solved and 100% of the offenders are incarcerated. What sort of prison population would we expect? Now imagine the opposite extreme, where 0% of crimes are solved. What sort of prison population would we expect? I suspect that the answer to the first question is “fairly low” and the answer to the second question is “precisely zero.” In the first case, crime wouldn’t pay, so the only crimes would be crimes of passion—say a jealous husband murdering his wife. In fact, neither of these scenarios describes the US, which has a prison and jail population of nearly 2 million. There’s a sort of Laffer curve effect with crime, whereby (starting from zero) stricter enforcement of laws results in more people in prison, and then beyond some point fewer people in prison.In the following, I’ll use murder rates, as the accuracy of other crime data is highly suspect due to spotty reporting. I was born 1955, a time when the annual US murder rate was about 4.5 per 100,000. It rose to a peak of over 10 per 100,000 around 1980, and then fell sharply in the 1990s and 2000s. It was 6.81 per 100,000 in 2021, and seems to have fallen in 2022 (although the national data is reported with an oddly long lag.)   During the 1960s and 1970s, the US adopted a soft on crime approach that contributed to a sharp rise in the crime rate.  We moved to the left on the incarceration Laffer curve, toward a more lenient policy.  Despite this softer approach, however, the total amount of incarceration actually increased during the 1970s.  Crime rates rose faster than punishment rates declined.  In the 1980s, we switched back toward a tougher approach toward crime, and for a time the incarceration rate rose even further.  Eventually, crime rates fell and incarcerations also declined.  In recent years, places like California have moved back to a softer approach to crimes like shoplifting and car theft.  Not surprisingly (except to sociologists), the rate of shoplifting is rising.  Eventually, voters will demand a crackdown and incarcerations rates for shoplifting will begin rising again. Here’s an analogy.  It is possible that a central bank would have to raise interest rates in order to reduce inflation.  But that does not imply that a low inflation world would be expected to feature high interest rates.   Richard Hanania recently attracted some controversy with this tweet: This is a pretty bleak vision, and one that I do not share.  It’s true that we need more effective law enforcement.  But I do not believe that a low crime rate requires incarcerating a large share of the black population.  In my view, Hanania is overlooking Laffer curve effects. America’s incarceration rate was far lower in the 1950s than it is today.  And yet the murder rate was also lower (and I suspect the overall crime rate was lower as well.)   If you don’t like comparisons over time, how about comparisons across nations?  In the UK, blacks are much more likely to be killed than whites.  That might seem to support Hanania’s argument, as most murders occur within a given race.  But even if British blacks commit murder at a much higher rate than other British residents, the rate seems to be roughly the same as for whites living in America (around 4 per 100,000).  And yet the incarceration rate in the UK is far lower than in the US.  Not only is a high level of incarceration not the only solution to high rates of crime, it is not even the only solution to high rates of crime in the black community. The ideal solution is high rates of incarceration and low levels of incarceration.  Punishment so certain that the crime doesn’t get committed.  The UK isn’t perfect, but it’s much closer to that ideal than is the US.  Indeed it’s closer to that ideal even among the black portion of the British population.  The ideal solution is to have a criminal justice system that is so effective that the incentive to commit crimes falls to very low levels.  We don’t need “more incarceration”; we need higher rates of incarceration per offense and much lower total levels of incarceration due to lower crime rates.  Ending the War on Drugs might also push us toward that goal.  During Prohibition, America’s murder rate soared much higher (during both booms and depressions.)  After Prohibition was repealed in 1933, our murder rate plunged much lower, despite very high unemployment. California has recently seen mobs of young people ransacking department stories.  This followed a decision to stop prosecuting so-called “minor crimes” such a shoplifting.  But shoplifting is not a minor crime—jaywalking is a minor crime.    California needs to take a much tougher approach to crime.  But the ultimate goal should not be thousands of young shoplifters rotting in California prisons, rather the ultimate goal should be to return to the situation where mobs of young people were not raiding our department stores.  If they don’t do the crime, they won’t have to do the time. You might argue that there’s no meaningful difference between what I’m saying and what Hanania is saying, as we both favor a “tough on crime” approach.  But his fatalistic vision seems much less likely to lead to the sorts of changes that are actually needed.  Hanania implies we don’t have the “stomach” for policies with a “disparate impact”.  But our criminal justice policies already have a hugely disparate impact, so he’s clearly wrong on that point.  And contrary to popular opinion, voters in black neighborhoods typically do not favor a “defund the police” approach to crime.  Many are concerned about their safety and wish more money was spent on protecting their lives and property.  I suspect they understand the difference between high rates of incarceration and high levels of incarceration.  And they also understand that more police on the streets can reduce crime for any given level of incarceration.   PS.  In this post, I’ve focused on how prison can deter crime.  But other approaches are likely to be far more effective, including putting more police on the streets and ending the War on Drugs. PPS.  Hanania’s tweet seems aimed at liberals.  But he might also have asked how many Americans have the “stomach” to enforce our tax laws (and which political party lacks the stomach to enforce those laws)?  How many Americans have the stomach to enforce our laws against trying to interfere in Georgia elections?  How many Americans have the stomach to enforce laws on stealing classified documents, or lying to law enforcement officers after the crime is uncovered?  I’m not encouraging people to be “woke”, but unconscious bias is a real thing.   PPPS.  I’ve ignored the issue of gun control, as it’s orthogonal to my claims here.  My argument does not depend on whether gun control is or is not a good idea, or the extent to which it explains the low UK murder rate.  Gun control may or may not be wise, but it is clearly not mass incarceration.  If you wish to raise the issue of guns, ask whether Americans have the “stomach” to enforce our existing gun laws. (0 COMMENTS)

Unlike many of the people who are writing encomiums to James Buckley (see here and here, for example), who died yesterday at age 100, I didn’t know him. But I still remember sitting in my Winnipeg apartment with some libertarian friends and watching U.S. election returns on November 3, 1970. The media showed James Buckley’s victory speech and I still remember his words: “How sweet it is.” Buckley, running on the Conservative Party ticket in New York state, was running against Richard Ottinger, the Democratic candidate, and Charles Goodell, the Republican candidate and incumbent whom Governor Nelson Rockefeller had appointed to the U.S. Senate after Senator Robert F. Kennedy was murdered in June 1968. Goodell, by the way, was the father of Roger Goodell, the commissioner of the National Football League. It’s not often that one has reason to remember a one-term U.S. senator. The reason I do remember is the case he brought, on First Amendment free-speech grounds, against the 1971 Federal Election Campaign Act. The case, which made it all the way to the Supreme Court, was Buckley v. Valeo. This link gives a nice summary. Buckley prevailed on a few key points but not on all.   (0 COMMENTS)

One hundred years ago today, Vilfredo Pareto passed away in his villa near Lausanne. I’ve writen a little piece for Project Syndacate on him and this anniversary. Also a new entry is up in the Encyclopedia at Libertarianism.Org. Pareto’s is a household name for many, because of the notion of Pareto optimality or the so-called Pareto principle. His contributions go way beyond that. Pareto was a pioneer in economics, political science, and sociology, and he contributed original ideas of all three fields. This is all the more surprising, when you consider that he never gave a University lecture before he was 45. For the first part of his life, Pareto, who studied mathematics and engineering, was a businessman, a CEO. In his spare time, he became an advocate of free market liberalism, contemplated a career in politics (which luckily for us all, it wasn’t to be), wrote and published extensively, in Italian but also in French. He befriended Gustave de Molinari and published on the Journal des économistes en France. He read an article, there, about Benjamin Tucker’s Liberty and sent the American anarchist journal a few correspondences. He admired English liberalism, Cobden and Gladstone, and was saddened by how liberty was watered down in England, too. A number of Pareto’s writings are translated into English and could be found on archive.org. More recently, a few books worth reading were added to the body of Pareto scholarship. For one thing, now we are lucky we have the three volumes biography by Fiorenzo Mornati (available in English from Palgrave Macmillan), which is a superb examination of Pareto’s thinking and its evolution through time. A critical edition of the Manual of political economy was published a few years ago, thanks to Aldo Montesano, Alberto Zanni, Luigino Bruni, John S. Chipman, and Michael McLure. This year, Christopher Adair-Toteff edited a collection of essays on the occasion of the centennial. A few years ago, we had a Pareto conversation on LibertyMatters. Giandomenica Becchio, Rosolino Candela and Richard E. Wagner contributed to it. This is a good day to pick up a Pareto’s book. (0 COMMENTS)

Every week I read a few outstanding articles but I have little or nothing to add. So I don’t post on them. But occasionally–and this is the first time–I will link to a few of the articles, quote a few segments, and maybe add my few thoughts. Here are two excellent articles that I read this week. Jesse Walker, “The Battlefields of Cable,” Reason, August 15, 2023. Excerpt: When C-SPAN’s cameras came to Congress in 1979, a wave of bloodless guerrilla maneuvers followed. Newt Gingrich, in those days a brash young Georgia congressman, led an insurgent cell of Republicans looking for ways to make the cameras work for them. One of their techniques was to deliver so-called “special order” speeches when the day’s business was over, which in addition to airing live on cable could be shared with local channels back home. “These speeches frequently called out the Democratic opposition directly, daring them to respond,” the Purdue historian Kathryn Cramer Brownell writes in 24/7 Politics, a new history of cable news and the regulatory forces that shaped it. “But nobody did,” she adds, “because the legislative session had ended and everyone was gone.” Not that you could tell that by watching the show, since the camera’s eye stayed fixed on the person speaking. And: C-SPAN was the brainchild of Brian Lamb, who had worked for Whitehead at the Office of Telecommunications Policy, and it was sponsored by the cable industry, which hoped the channel would prove the medium’s value. Between its noncommercial ethos, its commitment to shining a light on the government’s inner workings, and its Warholian willingness to let a motionless camera run while nothing appeared to be happening, C-SPAN was one of the few national cable channels of the 1980s that resembled those old hippie dreams of what TV could be. But it was also a creature of the milieu it covered, a place where Bob Walkers and Tip O’Neills could jockey for position. If this was guerrilla television, it wasn’t the sort the New Left had imagined a decade before. It was a landscape for folks like Gingrich to conduct guerrilla warfare. I’ve long been a fan of Brian Lamb. He was one of C-SPAN’s best interviewers of authors. His questions were not “gotcha” questions but, instead, “information-seeking” questions. But along the way, he occasionally got incredible admissions from authors who, because of his format, relaxed. David J. Bier, “The Government Cheats, Loses, and Cheats Again to Make Immigrating Illegal,” Cato at Liberty, August 16, 2023. Excerpt: You traveled a thousand miles and spent thousands of dollars to reach the United States. The immigration rulebook (sometimes called “the law”) says that if you made it, you could apply for asylum and that officials “shall” process you. But guess what? In this game, the government cheats. It doesn’t want to process you. It wants you to go home. So when you reached the border in 2019, the officials at the legal crossing point wouldn’t process you. They stood in the middle of the bridge to block you. You joined a lawsuit, and a court said, “Government, what you’re doing is illegal. Stop.” So in November 2021, the government issued a new policy that says, “You border guys, you can’t tell people to go away.” But it then promptly ignored that policy “because of COVID-19.” But that excuse ended in May 2023, so it reiterated the policy in a formal rulemaking. It couldn’t be clearer: “Our policy is to inspect and process all arriving noncitizens.” So you’d think you would get processed if you arrived at the border. But no, the government cheats. Border officials are telling people that they must make appointments before they can request asylum, and they cap the number of appointments, even though the new rules make it perfectly clear an appointment will not be required. You can’t even schedule an appointment at all. Rather, you are put in a lottery to decide if you can even request an appointment. When Isabel “Doe” showed up unannounced at a legal crossing point with her bleeding husband whom a cartel shot, she was turned away. Her husband was then murdered in Mexico. A number of my friends tell me that they are not against immigration but, rather, against illegal immigration. Here’s the test of their sincerity: Do they favor having the government obey its own law? If not, they are not in favor of legal immigration and are, in fact, in favor of government illegality. (0 COMMENTS)

The famous statement attributed to Lavrentiy Beria, Stalin’s secret police chief (“Show me the man and I’ll find you the crime”), is the paradigmatic example of what the rule of law is not. It represents a sort of social and political institution antithetical to individual liberty, economic prosperity, and human flourishing. Mark Meadows, Donald Trump’s chief of staff, was charged in Georgia with participation in a criminal enterprise. The prosecutor, Fani Willis, used the state’s imitation of the federal Racketeering and Corrupt Organization (RICO) Act. A Wall Street Journal story contrasts the Georgia indictments with the federal one for attempting to overturn the 2020 election (“The Curious Case of Mark Meadows, Told Through Two Indictments,” August 17, 2023): The Georgia prosecution, however, is a racketeering case, with Trump charged as being at the center of a criminal enterprise. Under Georgia’s RICO law, Fulton County District Attorney Fani Willis has the power to cast a wider net and implicate any player—big or small—who took part in the alleged conspiracy. Any act that furthers the alleged enterprise, which could be as simple as making a phone call or sending an email, can place an individual in legal jeopardy if done to advance the conspiracy’s broader goals. RICO is a very dangerous sort of law that was officially meant to go prosecute mafia bosses. If serious evidence exists that a mafia boss has committed a real crime, he should of course be prosecuted for that crime. Conspiring or attempting to commit a crime was always a crime, long before the invention of RICO in 1970. Standard law-and-economics theory explains this with simple incentives: if you try to steal $1 million and your probability of success is 0.5, your expected gain (not the net gain, of course) remains an attractive $500,000. Law-and-economics would also explain why delusion cannot be an excuse for a crime. (See David Friedman, Law’s Order: What Economics Has to Do with Law and Why It Matters [Princeton University Press, 2000].) Contra Rico, the minion who just carried the mafia boss’s luggage should not be prosecuted—a fortiori if he was trying to restrain the boss from committing crimes, as Meadows may have done. This remains true if one believes that Trump was engaged in a criminal enterprise and trying to expand it. It would probably have been wise for his collaborators to jump ship earlier, as some did. On the other hand, it would have been very dangerous to have Trump running loose in the City of Command, as Bertrand de Jouvenel called the seat of the state. I note with the Wall Street Journal that the federal prosecutor, Jack Smith, did not use RICO nor prosecute Meadows. I think that my critique is consistent with the liberal conception of the rule of law as defended notably by Friedrich Hayek and James Buchanan. A prosecutor naturally hopes to “flip” criminal accomplices into providing evidence lest their own crimes be more harshly punished. On the accomplices’ side, we meet what game theory calls the “prisoner’s dilemma.” This actually explains why complex conspiracies involving large groups of individuals are rare and rarely unpunished—why, for example, a complex conspiracy to overturn a US presidential election does not happen often. But a strict rule of law, not to mention civilized decency, would not incentivize prosecutors to round up all those who were standing around. Show me the man… In the case under consideration here, there is also a supreme irony, if not something like natural justice. In the 1980s, Rudolph Giuliani, who was a politically ambitious and immoral federal district attorney, used the federal RICO to wage a witch-hunt against New York financiers, sending many innocent men to prison and destroying many lives. He was too ignorant of political economy to suspect that the same sort of law could turn against him and, more worryingly, against future innocent individuals. It is all to the honor of the Wall Street Journal to have, at that time, defended many of the persecuted financiers. (0 COMMENTS)

There was a discussion on Facebook a few years ago about whether you can be a scholar but not be in academia. One person was claiming that you can’t. My Exhibit A that says you can is Phil Magness. Phil got his Ph.D. in Public Policy at George Mason University in 2010. Since then he has spent most of his time at think tanks rather than academia. He has been full-time in academia for only 1 of the last 13 years and that was not a tenure-track job. For 10 of the last 13 years, he has been a full-time employee of think tanks: the Institute of Humane Studies from 2010 to 2017 and the American Institute for Economic Research from 2018 to the present. I won’t list all his academic publications. I’ll list only those in top journals. “The Mainstreaming of Marx: Measuring the Effect of the Russian Revolution on Karl Marx’s Influence” Co-authored with Michael Makovi. Journal of Political Economy (June 2023) “How pronounced is the U-curve? Revisiting income inequality in the United States, 1917-1960” Co-authored with Vincent Geloso, Philip Schlosser, and John Moore. The Economic Journal (March 2022) “The Great Overestimation: Tax Data and Inequality Measurements in the United States, 1913-1943.” Co-authored with Vincent Geloso. Economic Inquiry (April 2020). “The anti-discriminatory tradition in Virginia school public choice theory.” Public Choice. (March 2020). “James M. Buchanan and the Political Economy of Desegregation,” Co-authored with Art Carden and Vincent Geloso. Southern Economic Journal (January 2019).   Now it is true, as those who know Phil well know, that he does not do this by working a 40-hour week or even a 50-hour week. My guess from being around him is that he works an approximately 75-hour week. That way he can do the responsibilities that come with his job at a think tank, only some of which involve writing for academia journals. But the point is that it can be done. Is Phil a genius? I’m not sure, but I don’t think so. What he has is a lot of smarts, a LOT of passion, and a willingness to work very hard. My guess is that because of all the hoops academic departments make you jump though nowadays, the disadvantage of working in a think tank, though still there, has diminished.   (0 COMMENTS)

Gross output (GO) is a relatively new macroeconomic statistic that measures total economic activity. Gross domestic product (GDP)—the other major measure of economic activity—accounts only for final goods and services. However, GO’s scope includes both final output as well as intermediate inputs at all earlier stages of production. Therefore, GO is a much more comprehensive measure of economic activity and presents a broader image of the overall economy. The Bureau of Economic Analysis (BEA) defines GO as “a measure of an industry’s sales or receipts, which can include sales to final users in the economy (GDP) or sales to other industries (intermediate inputs). Gross output can also be measured as the sum of an industry’s value added and intermediate inputs.” This means that GO is equal to the value of GDP plus intermediate inputs (II). Thus, GO = GDP + II (intermediate inputs), which means that GDP = GO – II The BEA has been publishing the gross output statistic, as well as the gross output-by-industry breakdown, every quarter along with GDP since April 2014.1 In an announcement, BEA director Steven Landefeld stated, “Gross Output provides an important new perspective on the economy and a powerful new set of tools of analysis, one that is closer to the way many businesses see themselves.”  He echoed the view of Sir John Hicks (1973) that “The concept of production as a process in time… is the typical business man’s viewpoint, nowadays the accountant’s viewpoint, in the old days the merchant’s viewpoint.” The Organization for Economic Cooperation and Development [OECD] now publishes GO on an annual basis for 34 countries. Economists view GO and GDP as complementary measures of aggregate economic activity. In accounting terms, GO is considered the “top line” in national income accounting and GDP is the “bottom line.” As Dale W. Jorgenson, J. Stephen Landefeld, and William D. Nordhaus (2006) state, “Gross output is the natural measure of the production sector, while net output is appropriate as a measure of welfare. Both are required in a complete system of accounts” (p. 5). Origin of GO GO has a long history of development.  In The Purchasing Power of Money: Its Determination and Relation to Credit, Interest, and Crises (1912, 1920), Irving Fisher introduced a theoretical measure of “volume of trade.” He did so with his Equation of Exchange, MV = PT. In that equation, M is the money supply, V is the transactions velocity of money, P is the price level, and T is the amount of goods and services transacted. Therefore, PT measures the “volume of trade” in the economy over some time period. PT makes no distinction between the value of final goods (which is measured by GNP [Gross National Product] and GDP) and the value of intermediate goods that are traded in the market. It includes both. In Prices and Production (1931, 1935), Austrian economist Friedrich A. Hayek introduced a diagram representing the measure of all the various stages of production. This diagram—now known as Hayek’s triangles—was the earliest basis for gross output, even prior to the introduction of GNP or GDP as macroeconomic statistics. However, Hayek did not expand this concept by calculating and measuring statistically the value of gross output. In the 1930s, Russian-American economist Simon Kuznets of the University of Pennsylvania was the first economist to measure national income. He set out to determine “the size of the final net product.” Kuznets (1934) wrote, “If all the commodities produced and all the direct services rendered during the year are added at their market value, and from the resulting total we subtract the value of that part of the nation’s stock of goods that was expended (both as raw materials and as capital equipment) in producing this total, then the remainder constitutes the net product of the national economy of the year.” Thus, net product focused on final output only. In 1942, Kuznets expanded his “net output” data to measure Gross National Product (GNP). After the Bretton Woods Agreement of 1944, GNP developed into a benchmark measure for estimating economic growth. Wassily Leontief (1966) expanded on the new concept by developing the first versions of input-output tables. In his view, they were an improved gauge of the overall economy. To formulate I-O accounts, one must examine the production process’s “intervening steps” proceeding from the first inputs to the final outputs and including all the intermediate steps, “a complex series of transactions…among real people.” This I-O data were the first approximation of gross output. Nevertheless, Leontief’s main focus was on the gross output-by-industry data, which represent, not the aggregate GO, but, rather, the fundamental interactions and relations between and among industries. In Chapter 6 of Skousen (1990), the author argued that gross output should be the starting point of national income accounting and that it offered a more complete picture of the macroeconomy. He argued also that GO could be integrated into macroeconomic analysis and textbook economics, and that it is more consistent than GNP with leading indicators and other macroeconomic data. In his view, GO and GDP complement each other as macroeconomic tools and both should play a vital role in national accounting statistics, much as top line (sales revenues) and bottom line (earnings, net profits) accounting are employed to providing a complete picture of quarterly earnings reports of publicly traded companies. Benefits of GO Some economists offer the following potential benefits of GO: 1. GO represents a missing piece of the macroeconomic puzzle.  For decades, publicly traded companies have issued quarterly financial statements including the top line (sales/revenues) and bottom line (earnings, net profits).  Now, finally, the federal government (the BEA) is reporting both total sales/revenues at all stages of production (GO) and final sales (GDP) along similar lines. 2. GO and GDP tell different stories.  GO is a more comprehensive measure of total spending in the economy that includes the supply chain. GDP accounts for final output only. GDP accounts for the end product, the “use” economy, but not how we got there. While GDP is a reasonably rough estimate of national living standards, it vastly underestimates the full contributions of business in the “make” economy, that is, the full value of business-to-business transactions that move the supply chain along the intermediate stages of production toward the final production of finished goods and services. According to the GDP model, consumption is by far the largest sector of the U.S. economy (around 67% of GDP), thus giving the impression that “consumer spending drives the economy,” a common claim in the financial media. However, based on the GO model, consumption represents only about one third of U.S. economic activity, and business spending represents over 60% of total U.S. economic activity. Business spending is almost double the size of consumer spending in the United States. 3. GO is more volatile than GDP on a quarter-to-quarter basis and, therefore, a better indicator of the ups and downs of business cycles. For example, during the 2008-09 recession, real GDP fell by 4 percent while real GO fell by over 8 percent. In the recovery stage from 2009 until 2016, real GDP rose by slightly more than 10 percent, while real GO climbed by over 18 percent. The data indicate a systematic trend in the relationship between GO and GDP over the length of the business cycle. During the expansion phase, GO tends to grow faster than GDP; during the contraction, GO declines more sharply than GDP; and during the recovery stage, GO tends to grow faster than GDP. 4. Some economists consider GO to be a leading indicator of GDP. Ranson (2017) states, “Because gross output includes the supply chain, movements in gross output serve as a leading indicator of movements in GDP’s next quarter.” Pitfalls of GO There are also limits of GO and these limits involve the degree of vertical integration of stages of production within firms. If an industry becomes much more vertically integrated so that it produces many inputs and then uses these inputs for final products, actual transactions in the market will fall even though there is just as much intermediate activity. If this happened to many industries at the same time, GO could change substantially even though the amount of intermediate activity did not. References Irving Fisher, The Purchasing Power of Money: Its Determination and Relation to Credit, Interest, and Crises (Macmillan: 1912, 1920). Friedrich A. Hayek, Prices and Production (Routledge, [1931] 1935, 2nd ed.) John Hicks, Capital and Time (Oxford University Press, 1973). Dale W. Jorgenson, J. Stephen Landefeld, and William D. Nordhaus, A New Architecture for the US National Accounts (University of Chicago Press and NBER, 2006). Simon Kuznets, National Income, 1929-1932 (National Bureau of Economic Research, 1934.) Wassily Leontief, Input-Output Economics. (Oxford University Press, 1966). David Ranson, “The economy’s supply chain as a timelier guage of its growth,” Economic and Investment Observations. HCWE & Co., June 30, 2022. Mark Skousen, The Structure of Production (New York University Press, 1990, 2015). Footnotes [1] The BEA definition is at https://www.bea.gov/data/industries/gross-output-by-industry. The GO data released by the BEA can be found under “Quarterly GDP by Industry.” Select interactive data “GDP by Industry.” Go to “Underlining Detail Tables” and select “Gross Output by Industry.” About the Author Mark Skousen is Presidential Fellow and Doti-Spogli Chair of Free Enterprise, Chapman University. (0 COMMENTS)

Economists are occasionally and wrongly accused of being too focused on money, or even of only being concerned about money. Some of the people who make this accusation simply haven’t bothered to study economics themselves. Still, there is one small way that economists might have inadvertently contributed to this perception.  Often when a regulation is proposed mandating things like more generous employee benefits or stricter health and safety standards, a common objection that comes from economists is “implementing this policy will result in lower wages.” To which someone might reply “So what? Money is good but it’s not the only good thing, and standing in the way of safety and benefits in the name of making more money is missing what really matters.”  This reply is fair as far as it goes, but it only works against a misleadingly simplified version of the economist’s objection. A fuller version of the objection is to point out that employee compensation always presents a tradeoff between wages and benefits, and there is no single correct combination that is right for everyone. Some people will happily accept lower benefits in exchange for a bigger paycheck, while others will cheerfully accept a lower paycheck for more generous benefits. Therefore, the best approach would be to maximize the scope for employees and employers to negotiate what mix of wages and benefits works best for their own circumstances and preferences – some employers will offer more wages and lower benefits, some will do the reverse, and even within a single company there can be a wide range made available for what mix of compensation will be offered. Policies that narrow the range of the wage-benefits mix of compensation are creating a deadweight loss.  I’ve taken some pains to try to make this as clear as possible when I touch on this topic, like when I said:  I’m not saying that higher benefits and lower wages is a bad thing in itself – for many people, it makes perfect sense. But it’s also easy to see how for some, it makes far more sense to prefer lower benefits and higher wages. Someone who is young and just starting out on their career may well prefer to take less vacation time and lower benefits in exchange for a bigger paycheck, in order to build up a strong financial foundation at the outset of their career, or to make it easier to save up for a down payment on a house, or any number of reasons. Should it really be a crime for them to be able to make that decision for themselves? Still, recent posts by David Henderson and Pierre Lemieux on the gender pay gap have made me wonder if sometimes its not the critics of the market who implicitly assume that money is the end-all-be-all of what matters. Both David and Pierre point out that there are significant differences in the kind of work that men and women do, particularly when it comes to work that is physically dangerous and demanding. Some time ago, Warren Farrell (who isn’t exactly a rabid right-winger – he was elected to the board of directors of the feminist group the National Organization for Women three times) wrote a book arguing that if you account for a number of different variables like these, and make an apples to apples comparison, the pay gap goes in the opposite direction. That is, women actually make more than men with the same characteristics.  Still, some people push back against this by arguing the reason men and women make such systematically different choices about their careers is because society, implicitly or explicitly, encourages men and women to make those different choices. So, this argument would go, it’s not the case that men are intrinsically more willing to do physically demanding work with a high risk of injury or death than women, or that men are naturally more willing to do work with longer hours that might require frequent relocation than women – it’s because society primes men and women differently. This line of thinking is not new, of course. John Stuart Mill, in his work The Subjection of Women, asserted there were no natural differences between men and women and that “the nature of women is an eminently artificial thing—the result of forced repression in some directions, unnatural stimulation in others.”  I think Mill overstates the case, but let’s ignore that for now. Indeed, let’s go ahead and grant that all of the differences we see in the career choices made by men and women are 100% due differences in social pressure. Should we conclude that this means the gross (that is, unadjusted) pay gap between men and women is a sign that men are systematically advantaged over women? Well, no – not unless you also harbor the assumption that higher wages are lexically superior to every other consideration. Or, put more bluntly, only if you assume that money is the only thing that matters. For example, women tend to choose careers that offer greater flexibility with their time and require fewer hours. Again, assume this entirely the result of social conditioning. It’s hard to see why this is inherently to the disadvantage of women. One can easily find endless think-pieces on the importance of maintaining a good “work-life balance” and not letting one’s job consume the rest of their life. If men are being socialized into distorting the work-life balance in favor of working longer hours, while women are being socialized into favoring a work-life balance with fewer hours, it’s not at all obvious that the group being pressured into maximizing money while having less time for the everything else in life is getting the better deal. Similarly, if one group is socially conditioned to do dangerous work that pays higher wages, and the other group is socially conditioned to prefer an arrangement with lower wages but much lower risk of being killed or maimed on the job, I think it’s at least arguable that the second group has the better deal.  Acting as if differences in income between groups is evidence that the group with higher income is unfairly better off makes sense only if you assume that maximizing income is all that matters to living a good life. But if money isn’t all that matters, and if there are things in life worth pursing even if they mean getting less money, then this conclusion doesn’t follow.    (0 COMMENTS)

Coleman Hughes recently interviewed  Eliezer Yudkowsky, Gary Marcus and Scott Aaronson on the subject of AI risk.  This comment on the difficulty of spotting flaws in GPT-4 caught my eye: GARY: Yeah, part of the problem with doing the science here is that — I think, you [Scott] would know better since you work part-time, or whatever, at OpenAI — but my sense is that a lot of the examples that get posted on Twitter, particularly by the likes of me and other critics, or other skeptics I should say, is that the system gets trained on those. Almost everything that people write about it, I think, is in the training set. So it’s hard to do the science when the system’s constantly being trained, especially in the RLHF side of things. And we don’t actually know what’s in GPT-4, so we don’t even know if there are regular expressions and, you know, simple rules or such things. So we can’t do the kind of science we used to be able to do. This is a bit similar to the problem faced by economic forecasters.  They can analyze reams of data and make a recession call, or a prediction of high inflation.  But the Fed will be looking at their forecasts, and will try to prevent any bad outcomes.  Weather forecasters don’t face that problem. Note that this “circularity problem” is different from the standard efficient markets critique of stock price forecasts.  According to the efficient markets hypothesis, a prediction that a given stock is likely to do very well because of (publicly known) X, Y or Z will be ineffective, as X, Y and Z are already incorporated into stock prices.   In contrast, the circularity problem described above applies even if markets are not efficient.  Because nominal wages are sticky, labor market are not efficient in the sense that financial markets are efficient.  This means that if not for the Fed, it ought to be possible to predict movements in real output.    Before the Fed was created it might have been possible to forecast the macroeconomy.  Thus an announcement of a gold discovery in California could have led to forecasts of faster RGDP growth in 1849.  There’s no “monetary offset” under the gold standard.  This suggests that moving to fiat money ought to make economic forecasting less reliable than under the gold standard.  Central bankers would begin trying to prove forecasters wrong. We tend to assume that fields progress over time, that we are smarter than our ancestors.  But the logic of discretionary monetary policy implies that we should be worse at economic forecasting today than we were 120 years ago. Recall this famous anecdote: During a visit to the London School of Economics as the 2008 financial crisis was reaching its climax, Queen Elizabeth asked the question that no doubt was on the minds of many of her subjects: “Why did nobody see it coming?” The response, at least by the University of Chicago economist Robert Lucas, was blunt: Economics could not give useful service for the 2008 crisis because economic theory has established that it cannot predict such crises.¹ As John Kay writes, “Faced with such a response, a wise sovereign will seek counsel elsewhere.” And so might we all. If Robert Lucas had successfully predicted the 2008 crisis it would have meant that he would not have deserved a Nobel Prize in Economics. PS.  I highly recommend the Coleman Hughes interview.  It’s the best example I’ve seen of a discussion of AI safety that is pitched at my level.  Most of what I read on AI is either too hard for me to understand, or too elementary. PPS.  The comment section is also interesting.  Here a commenter draws an analogy between those who think an AI can only become more intelligent by adding data (as opposed to self-play) and people who believe a currency can only have value if “backed” by a valuable asset. Yet another prevalent (apparently) way people think about the limitations of synthetic data is that they think it’s like how prompting can bring out abilities a model already had, by biasing the discussion towards certain types of text from the other training data. In other words, they are claiming that it never adds any fundamentally new capabilities to the picture. Imagine claiming that about a chess-playing system trained through self-play… Many of these wrong ways of looking at synthetic data sort of remind me of people not grokking how “fiat currency” can have value. They think if it’s not backed by gold, say, then the whole house of cards will come crashing down. The value is in the capability it enables, the things it allows you to do, not in some tangible, external object like gold (or factual knowledge).   (0 COMMENTS)

Gregory Zuckerman is an author and investigative journalist with the Wall Street Journal. His main area of work is covering business and investing topics. In this episode of EconTalk, Russ Roberts hosts Zuckerman for a conversation on his book: A Shot to Save the World: The Inside Story of the Life-or-Death Race for a COVID-19 Vaccine. Topics the two discuss include profiling the key players involved in the groundbreaking discovery of the COVID vaccine and the science behind the shot that has saved millions of lives.     1- Zuckerman describes the purpose of his book as being an attempt to set the record straight regarding the development and discovery of the COVID vaccine. He was able to get different parties to talk to him based on their incentive of being part of a historically accurate piece, even though people would normally be swayed by their affiliates to avoid talking to the press. Russ appreciates the poignance that the book has because of the gravity of the achievement of the COVID vaccine. How do you think the book and the historical accounts of the pandemic will be received differently in the distant future?   2- Throughout the conversation,  Zuckerman and Roberts note that the image many have of doctors, epidemiologists, and infectious disease experts is far removed from real life. Roberts finds the book to depict a “petty, peculiar world” within vaccine discovery as opposed to his more relaxed field of academics. How do you react to Zuckerman’s profile of the heroes who compete and relentlessly pursue successful vaccines at any cost? Is this reality a net positive or negative? Explain.   3- Russ alludes to what he sees as a failure of government regulation in keeping mask prices extremely low, creating a shortage, and Dr. Fauci dishonesty with the public about the efficacy of masks in an attempt to fix the supply issue. To what extent do you agree with Russ that the market should have been left alone to distribute masks? What can competition do to assist in times of panic? When should (and shouldn’t) the government get involved?   4- Zuckerman describes the common disappearance of viruses and pathogens as a key part of the peculiar world of vaccine making. Companies like Moderna have made incremental progress on developing potential treatments for diseases like the zika virus, but these advancements go unnoticed and unappreciated because the threat so quickly disappears. When the COVID vaccine race began, it was ‘crazy,’ as Zuckerman says in the title of the book, and that is because these smaller companies wanted to finally prove themselves. Is this market flawed? To what extent does the rush to make a viable vaccine across all companies ensure the best outcome? Can you suggest other possibilities that might allow for a response time as quick as we saw with the COVID vaccine?   5- Zuckerman and Roberts discuss the Steve Jobs-like aura of Moderna leader Stéphane Bancel as having boundless optimism and the ability to get the most out of his staff, even though it may seem like some of his actions are cruel from the outside. The two appreciate a unique leader who can push employees to the edge for a company to be able to change the world. In sports, I think of Bob Knight as a parallel figure. What other individuals can you cite who cultivated remarkable success, but often had/has their methods questioned? What effect do you think this sort of criticism has had on their success?     Brennan Beausir is a student at Wabash College studying Philosophy, Politics, and Economics and is a 2023 Summer Scholar at Liberty Fund. (0 COMMENTS)