Conversable Economist

David A. Price carries out an “Interview” with Melissa Kearney, subtitled “On the American fertility decline, the role of social norms, and the link between single-parent households and economic gaps” (Econ Focus: Federal Reserve Bank of Richmond, Third Quarter 2023, pp. 16-20). Here are a few comments that caught my eye:

What is “two-parent privilege”?

More consequentially for children’s outcomes and socioeconomic gaps, children born to college-educated parents are now much more likely to live in a household with married parents and have the associated benefits of that. To be specific, 84 percent of children whose mothers have a college degree live with married parents, compared to less than 60 percent of children whose mothers don’t have a college degree.

This means that the kids born to college-educated mothers live in a household with much higher levels of income, not just because their mother has the potential to make more income, but because she’s much more likely to have a working spouse in the home or to have a spouse in the home at all. But also, there are many more parental resources in general when there are two parents in the home — more parenting time for supervision, nurturing, and so on. To the extent that parenting inputs shape children’s outcomes, this widens the gap in kids’ behavioral and educational outcomes and exacerbates class gaps. This is why I referred to this phenomenon as the “two-parent privilege,” because the two-parent home has now become another advantage of the college-educated class and their children.

Discomfort among academics about discussing the role of family structure

 I was at a conference on poverty earlier this summer where someone in attendance, not me, brought up the subject of family structure. The panelists, who were not all economists — they included sociologists and a social worker — were visibly uncomfortable, even annoyed, and promptly dismissed the person’s question.

I think this discomfort stems from a well-intentioned instinct to not want to come across as sounding judgmental or shaming certain types of families. And I’m very sympathetic to that instinct. The problem, though, is that avoiding this topic is counterproductive. Denying the importance of family structure and the role of families to children’s outcomes and economic mobility is just dishonest, based on the preponderance of evidence. Another reason why I think it makes economists, in particular, uncomfortable is that we don’t have a ready solution for the challenge. It would be much easier for us to talk about this issue if there were an obvious policy lever to address it. ..

That’s something that highly educated Americans often speculate about this topic: “Oh, we’re just becoming more northern European in our attitudes about this.” But that’s not what’s happening. The decline in marriage among parents in the U.S. has not been replaced with a corresponding rise in unmarried parents stably living together for the long haul and essentially being married in all but name. In the U.S., cohabitation is a very fragile arrangement.

To what extent can government transfers address this issue?

I am in favor of increasing income support to low-income families with children, given all we know about the benefits of alleviating material deprivation for children. … I do want to acknowledge the concern that insofar as transfer payments increase the economic viability of single-parent households, that might lead to some small increase in these types of households. My read of the evidence is that the behavioral effects there are likely to be small. But either way, I’ll take the trade-off. I am firmly of the view that we cannot just allow children to continue suffering the consequences in the hope that entices some more parents to get married.

Having said that, even an increase in transfer payments isn’t going to fully make up for the absence of the second parent in the home. Parents do more than just pay the bills. They invest their time and energy into their children. They provide supervision and guidance. They read to them and play with them. We should be clear that a government check is never going to be able to fully make up for the absence of a second committed parent in the home.

Furthermore, the reality is that in this country, we couldn’t even muster the political support last year to maintain an annual child tax credit of $3,000 per year. That indicates to me politically how far we are from a situation where we might conceivably have income transfers to make up for the absence of a second earning parent in the home. What are the chances we’re going to have a child allowance equal to, say, the median earnings of a high school graduate, around $40,000 a year, year after year until the child is 18? The idea that we’re going to solve this problem with a government check is just not plausible. And it doesn’t account for all the many things that a second parent brings to the home beyond income.

For couple of examples of Kearney’s work from the Journal of Economic Perspectives, where I work as Managing Editor, see:

• Kearney, Melissa S., Phillip B. Levine, and Luke Pardue. 2022. “The Puzzle of Falling US Birth Rates since the Great Recession.” Journal of Economic Perspectives, 36 (1): 151-76.
• Guryan, Jonathan, Erik Hurst, and Melissa Kearney. 2008. “Parental Education and Parental Time with Children.” Journal of Economic Perspectives, 22 (3): 23-46.

“Remittances” refers to when someone migrates to another country, works and earns money, and then sends some of that money back to people in their country of origin. In effect, some countries both exports goods and services, and receive payment from buyers in other countries, but also export worker, and receive payment from other countries. The World Bank has a Migration and Remittances Team, and it provides an update on the numbers in “Remittances Remain Resilient but Are Slowing” (Migration and Development Brief 38, June 2023).

Here’s the overall pattern. In 2000, the level of remittances was quite similar to “official development assistance” (ODA), while both of those were substantially lower than foreign direct investment (FDI). Now, remittances are roughly triple official development assistance. And if you take foreign direct investment going to China out of the picture, as shown in the bottom panel, remittances are roughly double the level of FDI going to all other low- and middle-income countries.

In short, remittances are a huge part of the capital flows between countries. However, they often don’t make the news. Development assistance from nation to nation or a big overseas investment by a US company can make headlines. But payments of remittances, often within families, are individually quite small–it’s just that they add up to big stuff.

The report provides lots of detail about remittances in regions and countries. Here’s one more chart. The left-hand panel shows remittances received by country. The right-hand panel shows remittances as a share of GDP, which is more than one-fifth of GDP for the countries listed there.

These flows also help to explain the interest, in many low- and middle-income countries, in finding ways to transfer money across international borders at lower cost, even if it involves using cryptocurrencies or other new financial technologies.

I’ll leave it for another day to write about whether remittances are “good” or “bad” (although personally, I lean heavily to the “good” side). On one side, there are concerns that countries sending migrants may suffer from “brain drain,” as those who are more educated or highly motivated may go other places. On the other side, when people of your country are earning and sending home tens of billions of dollars, or in some cases more than one-fifth of GDP, that’s not obviously a bad thing! Moreover, the skills learned by migrants and the economic connections they make can often be of considerable use to those who remained in the country of origin.

In the United States, we naturally celebrate the Labor Day holiday with a holiday from work. While this may be counterintuitive for others, economists have long see the price of labor and leisure as intimately intertwined. Although prices are often stated in terms of money, which is a useful convenience, the true price of anything is determined by its “opportunity cost,” which is what you give up or trade off. A standard example is that attending college has two costs: what you pay for tuition, room, and board, and also the opportunity cost of what you could have earned if you had been working at a job during that time. In a similar spirit, leisure has a opportunity cost–it’s the income you could have earned if you had been working. This insight isn’t new, of course: any gig worker in the modern economy knows it at a visceral level.

But the idea that leisure has an opportunity cost has some perhaps surprising implications. It means, for example, that as an economy becomes better off over a long period of time and the standard of living rises, leisure becomes more expensive in the opportunity cost sense. Moreover, as any good or service becomes more expensive, it will tend to be used differently. Alex Tabarrok explains some of the implications in a 2022 essay (“William Baumol and the Cost Disease,” in Research in the History of Economic Thought and Methodology: Including a Symposium on the Work of William J. Baumol: Heterodox Inspirations and Neoclassical Models ungated version here). Tabarrok writes:

Travelers to developing countries notice that haircuts and restaurant meals are cheap and often something else. Life in developing countries seems slower, more tranquil, and less harried. Meals are longer, conversations deeper, time seems to move less quickly. Development seems to be accompanied by fast food, fast talking and even fast walking (Levine & Norenzayan, 1999). In The Harried Leisure Class, Staffan Linder (1970) proved a theorem … As productivity increases, as measured by wages, so does the opportunity cost of leisure or more generally, time. A higher price of time encourages us to economize on time, so as wages rise, we schedule our time more carefully with time planners, “to do” lists, calendaring and incessant notifications. We consume more quickly and we consume more goods that are quick to consume so “fast food” becomes the norm and we choose to watch television or movies “on demand” rather than read books or go to plays or live music performances. We consume multiple goods at the same time as when we eat and watch, talk and drive, and exercise and listen. …

Linder notes that goods and services take time to consume, and time is limited so the price of good x should include not just its money price but also its time price, the wage rate multiplied by the time it takes to consume the good … Or, as Baumol (1973, p. 630) put it, “rising productivity decreases the demand for commodities whose consumption is expensive in time.” …

[T]here are qualifications and additional considerations. Most notably, since the … Linder theorem [is] driven by an increase in productivity, consumers are not made worse off by the respective increase in prices. The choice to consume fewer time-intensive goods as wages increase is welfare-maximizing. It is also true that time is not entirely fixed. Time-saving devices such as faster internet or supersonic aircraft are possible. We can also increase life expectancy giving us more time to enjoy our greater productivity of goods and services (Hall & Jones, 2007). Indeed, we are consuming more leisure over time. Nevertheless, the power of the Linder theorem should be evident. One reason we consume more leisure than in the past is that we manage our time at higher levels of intensity than in the past. A search at Amazon for “time management,” for example, leads to over 10,000 hits. It is also the case that leisure, especially passive leisure such as watching television, has become more concentrated in people with lower incomes (Aguiar & Hurst, 2009).

An obvious question here is the extent to which you wish to push back against more intensive management of your leisure time. Are you planning a day that involves travelling multiple places, preparing and eating multiple foods, while paying attention to multiple music channels and social media feeds? Do you have a desire, or perhaps the internal fortitude, to commit a substantial block of time to a single activity: perhaps sitting down for an uninterrupted conversation, or a swim or a hike, or a couple of hours with a single book. There’s no best answer here, of course. Preferences will differ. But if when you reach the end of your holiday you are exhausted in such a way that you feel as if you need another day off, maybe it’s time to take closer look at how you are being influenced by the rising time costs of leisure.

Considerable evidence has been suggesting for some time now that children suffered learning loss from the K-12 during the pandemic. From a research perspective, it’s trickier to demonstrate exactly why children suffered such losses. School closures are an obvious possibility, and probably also part of the answer. But the other disruptions of the pandemic to family health, economic prospects, and social lives surely played a complementary role. But for the affected children, the arguments over causes are also arguments about the past: for this group, the policy question is whether remediation efforts can help them catch up to where they would have been.

Santiago Pinto pulls together the existing research on this issue in “The Pandemic’s Effects on Children’s Education” (Economic Brief: Federal Reserve Bank of Richmond, August 2023, #23-29).

As I’ve noted here a couple of months ago, recent test scores show student’s falling behind during the pandemic. Pinto writes: “The 2023 paper “A Systematic Review and Meta-Analysis of the Evidence on Learning During the COVID-19 Pandemic” looked at more than 40 studies around the world and reached similar conclusions. In the study, the overall size effect is a loss of 0.14 SD [standard deviations], or about 0.4 years of schooling lost.” Evidence from the US shows losses of this size or slightly larger.

It’s worth putting that learning loss of about a half-year in perspective. In some ways, it doesn’t seem like a lot. Shake it off! Catch up! But US schools have had a substantial share of students lagging behind grade-level for decades now, and they have not shown much ability to help large groups of students catch up. Indeed, if there was a school reform that would boost average student learning by a half-year, it would be thought of as a near-miracle. Conversely, losing a half-year of schooling is a near-disaster.

Moreover, US schools do not seem to be mobilizing in a way that will help students catch up. For example, students have shifted out of K-12 schools to alternatives and absenteeism is high. Pinto writes:

The 2023 report “Where the Kids Went: Nonpublic Schooling and Demographic Change During the Pandemic Exodus From Public Schools” uses data from 21 states plus D.C. (covering the 2020-21 and 2021-22 school years) to explain what happened with students leaving public schools. The report shows that an increase in home-school enrollment and a decrease in school-age population each explain 26 percent of the decline in public-school enrollment, and 14 percent was explained by an increase in private-school enrollment. About one-third of the decline, however, remains unexplained.

We don’t yet know if those who shifted to alternative schools will be more able to catch up. We do know that school districts with less in-person learning had the biggest drops in test scores, which doesn’t suggest that the alternatives are performing especially well. In general, student learning is tied to the amount and the continuity of instructional time received, and neither the amount nor the continuity seems to be rising in a way that will help students as a group to catch up.

It’s of course dicey to estimate what learning loss means in the long-run. Pinto describes one effort this way:

[A]n additional year of schooling increases income by about 11 percent on average in the U.S. If it is assumed that the pandemic and the associated changes in schooling generated a loss of one-third of a school year, then this would translate into a loss of income for the affected students of about 3.5 percent over their entire working life. 

The losses in lifetime earnings are of course only part of the issue: “Empirical evidence has linked school closures to several factors, including rising mental health concerns, lower levels of engagement, reports of violence against children, rising obesity, increases in teenage pregnancy, rising levels of chronic absenteeism and dropouts, and overall deficits in the development of socioemotional skills due to social isolation from networks and peers.”

These effects tend to be larger for student who are from economically disadvantaged families, and those who are already falling behind academically. Schools tend to be a “great equalizer,” making up to some extent for the unequal distribution of other educational resources across families. Those children who depended most on public schools also lost the most when the schools shut down.

What would an emergency-level response to these issues look like? One possible step would be a dramatic rise in programs of in-person tutoring. “The 2022 working paper “The Challenges of Implementing Academic COVID Recovery Interventions: Evidence From the Road to Recovery Project” claims that making up the gap would require approximately 40 to 100 hours of high-quality tutoring for the average student (slightly less for reading than math).” Think of this as maybe two hours of tutoring per student every week. Making this happen would require an immediate and dramatic expansion of tutoring programs, drawing on parents, retirees, college students , and others.

Another step would be to expand the school year by, say, six weeks: “The 2023 paper “The Fiscal and Welfare Effects of Policy Responses to the COVID-19 School Closures” shows that extending schools by three months (or six weeks over the next two summers) generates significant welfare gains for the children and raises future taxes to pay for the cost of this schooling expansion.”

Frankly, a dramatic rise in tutoring and expanded school years should have been much higher on the K-12 policy agenda before the pandemic.  During the pandemic, schools should already have been planning for the implementation of these steps back in 2021 and 2022. A decrepit bridge can sometimes wait a few years for necessary repairs. A current fourth-grader or an eight-grader or a high school senior, lagging behind academically, doesn’t have the luxury of waiting.

It’s well-known (although it’s not clear anyone wants to do anything about it) that US budget deficits and government debt took a big jump during the Great Recession from 2007-9, then another big jump during the pandemic recession, and are projected to rise steadily in the middle-term as an aging US population leads to higher government spending on Medicare, Medicaid, and Social Security. But it’s not just the United States. Especially after the pandemic, government debts around the world are high. The question is, based on past experience, what steps have some plausibility for reducing these debts.

The International Monetary Fund takes up this question in Chapter 3 of the World Economic Outlook report that came out in April 2023, titled “Coming Down to Earth: How to Tackle Soaring Public Debt.” At the most recent annual conference held by the Kansas City Fed at Jackson Hole, Serkan Arslanalp and Barry Eichengreen take up the same subject in “Living with High Public Debt.” These reports mostly agree on the problem, but differ on what solutions are plausible, with the IMF report offering mildly greater optimism.

Here’s a figure from the IMF report on trends in public debt as a share of GDP. The black line shows rising global debt; the blue line shows the US; and the red line shows China. Of course, the relatively moderate rise in overall averages shown in the figure represents an average of countries where debt is reasonably under control and countries where it is not.

One can dig down into exactly how public debt is being measured, or shifts in what parties are holding public debt, and those interested in doing so can plow into these reports. Here, I want to focus on the statements about how debt/GDP burdens might be reduced in theory, and the evidence about what has worked in practice.

The first and most obvious approach to reducing public debt, of course, is to stop running budget deficits and start running surpluses. But as Arslanalp and Eichengreen write:

The conventional way of bringing down high public-debt ratios … is by running primary budget surpluses. … There are instances in history where governments have succeeded in doing just this. But while the logic is impeccable in an accounting sense, it may be problematic in a political sense, in that the political conditions allowing heavily-indebted governments to run primary budget surpluses for extended periods are not present today.

They refer to some classic examples in which governments reduced debt by running sustained budget surpluses for long periods of time, but these examples have a 19th century feel, like the US after the Civil War and the UK after the French and Napoleonic Wars. In more recent episodes, as the IMF notes: “[P]artly because fiscal consolidation tends to slow GDP growth, the average fiscal consolidation
has a negligible effect on debt ratios.”

The IMF also digs down into the situations in which this approach has worked. They argue that running long-run budget surpluses does tend to bring down debt burdens in the historical evidence of recent decades when: 1) it happens in a context where the economy is growing steadily; 2) public debt has been “crowding out” private investment, so the reduction in public debt leads to a rise in public investment; and 3) the debt reduction is driven more by spending cuts than by tax increases. Conversely, when a country tries to reduce its budget deficits in a setting of slow growth or recession, at a time when the lower government borrowing doesn’t lead to a rise in private investment, and by raising taxes rather than cutting spending, it is often unsuccessful in reducing the debt/GDP ratio.

For a useful overview of the evidence that a permanent reduction in the expected future path of government spending is more likely to reduce public debt, with fewer tradeoffs, than raising taxes, I recommend the discussion by Alberto Alesina, Carlo Favero, and Francesco Giavazzi in the Spring 2019 issue of the Journal of Economic Perspectives (where I work as Managing Editor), “Effects of Austerity: Expenditure- and Tax-Based Approaches.” 

A second approach to reducing government debt is to have higher inflation, which eats away at the value of past debt. In the short-term, a burst of unexpected inflation can have a one-time effect like this. But in the longer-term, persistent inflation leads to correspondingly higher interest rates. Arslanalp and Eichengreen write:

inflation is not a sustainable route to reducing high public debts. Only unanticipated inflation has this effect. Although an anticipated increase in inflation may reduce debt ratios in the short run by raising the denominator of the debt-to-GDP ratio, in the long run it is apt to raise interest rates and shorten maturities. At both horizons, these effects are unlikely to be economically important.

The IMF adds: ” Although high inflation can reduce debt ratios, the chapter’s findings do not suggest that it is a desirable policy tool. High inflation can lead to losses on the balance sheets of sovereign debt holders such as banks and other financial institutions and, more crucially, damage the credibility of institutions such as central banks.”

A third approach to reducing public debt relies on the gap between the interest rates on public debt and the growth rate of the economy. Remember that the goal here is to reduce the ratio of debt/GDP over time. If interest rates are low, that will help to reduce the rise of the debt, and if combined with steady growth in GDP, then the ratio of debt/GDP would decline. Without going into great detail here, we are living in a time when interest rates are rising and policies for how to raise economic growth in a near-term, sustained, and sustainable way are thin on the ground.

A fourth approach to reducing public debt goes under the general heading of “financial repression.” Basically, these are policies in which governments pass regulations or laws that require certain parties like banks or pension funds to hold public debt, or that seek to limit or cap higher interest rates. These steps also often require limits on investments moving across borders. Historically, such steps have been able to assure that governments are able to keep issuing public debt while paying relatively low interest rates. But widespread efforts along these lines seem unlikely. As Arslanalp and Eichengreen write: “[S]tatutory ceilings on interest rates and related measures of financial repression are less feasible than in the past. Investors opposed to the widespread application of repressive policies are a more powerful lobby. Financial liberalization, internal and external, is an economic fact of life. The genie is out of the bottle.”

A final approach to reducing debt is a what the IMF calls a “debt restructuring,” but which man of us would just call a partial default. This step can reduce debt, but it’s a last-ditch step for desperate and relatively small economies, not a useful strategy for major advanced economies.

So where does that leave us? Arslanalp and Eichengreen write: “Our thesis in this paper is that high public debts are not going to decline significantly for the foreseeable future. Countries are going to have to live with this new reality as a semipermanent state. These are not normative statements of what is desirable; they are positive statements of what is likely.”

The IMF is not as blunt, but the report notes: “Ultimately, reducing debt ratios in a durable manner depends on strong institutional frameworks, which prevent `below the line’ operations that undermine debt reduction efforts and ensure that countries indeed build buffers and reduce debt during good times.”

In other words, whether the ratio of public debt to GDP has doubled in the last 18 years or so, as it has for the US economy in the figure above, or quadupled, as it has for China in the figure above, there isn’t an easy fix. Taking on high levels of debt is easy; reducing debt is hard. If you don’t seize the opportunity in good economic times to make a serious effort to reduce debts, then it’s even harder to do so in lukewarm or bad economic times. It would help the long-term debt picture if the US political system could get serious both about finding ways to hold down the projected rise in expenses on the huge-ticket programs like Medicare, Medicaid, and Social Security, as well to focus on the many small things that don’t matter all that much individually, but do add up (for suggestions, see this GAO report on reducing duplication and overlap in government programs, or this discussion of underutilized government office space). More broadly, my sense is that too many public actors have fallen into the bad habit of thinking that federal spending is free.

I have written from time to time over the years about concerns that the number of start-up firms in the US economy has been stagnant (for example, here, here and here). This is a matter of general concern, because start-up firms are often the ones providing a jolt of new goods and services, new jobs, new competition, and new energy in a dynamic economy.

However, there are some preliminary sources of data which suggest that since the end of the pandemic, the rate of new US business start-ups may be on the rise. Here are two of them.

A relatively new source for this information is the Business Formation Statistics published by the US Census Bureau starting in 2019. If a new organization is planning to hire employees, it needs to apply for an Employer Identification Number (EIN) from the Internal Revenue Service, so that the IRS can collect taxes from these employees. Here’s the monthly data on such applications, which has been extended back to 2011.

As you can see, the new applications for EIN numbers dropped during the pandemic recession, then rebounded much higher, but since have settled into a level well above the pre-pandemic levels.

There’s no guarantee that applying for an EIN will actually lead to hiring someone. Thus, the Census Bureau looks over the EIN applications and applies a few criteria to estimate the number of “high-propensity applications”–that is, those where it seems especially likely that hiring will actually happen. For example, if an organization has formed a legal corporation, has an announced date when it expects to begin paying wages, and is in an industry where employees are common like accommodation and food services, construction, manufacturing, retail, professional, scientific or technical services, educational services and healthcare, then it’s likely to be classified as “high propensity.” As you can see, the share of high propensity applications was about 100,000 per month pre-pandemic, but seems to have stepped up to a higher level of 150,000 per month.

There’s some other evidence to back up the belief that something is happening here. The Census Bureau also calculates what is called the Business Dynamics Statistics, constructed from its Longitudinal Business Database. Basically,, this data uses Census data and links the records on individual companies over time. To keep the records of individual companies confidential, the detailed data can only be accessed by qualified researchers through a network of Census Bureau Research Data Centers. Also, this data is available at quarterly intervals and with a longer lag than the EIN data. The most recent data release is up through the end of 2022. But some overall trends are apparent.

If you go back 10 years to 2012, in a given quarter, the number of “establishment births” is about 2.9-3.2% of the total number of existing firms. An “establishment,” in the jargon here, is a new geographical location where a firm is operating, and so it includes both new locations of existing firms as well as brand-new firms. But since the second quarter of 2021 through the end of 2022, the quarterly rate of establishment births has rise to about range of 3.8-4.1% of the total number of existing firms. Meanwhile, the rate of “establishment deaths” hasn’t changed much, other than an upward spike when the pandemic hit in the second quarter of 2020.

I should stress that these patterns are fairly recent, and the US economy is still climbing out of the pandemic. As these sources of data continue to accumulate, along with other sources like the National Report on Early Stage Entrepreneurship in the United States done by the Kauffman Foundation, we’ll know more.

But a reasonable if provisional hypothesis is that one reason the US economy has managed to keep unemployment rates low and to avoid an outright recession since the pandemic is an underlying surge in new start-up firms.

I sometimes say that one difference between those who have been trained as economists and normal human beings is that economist don’t believe in real people, but instead believe in statistical people. My point is that normal humans tend to reason from examples of particular people: perhaps a person who lost their job, or a stock-picker who recommended buying Amazon back in 2000s, or someone who received the COVID vaccine but became sick anyway. Let us stipulate that these individual people are real; indeed, they can be interviewed on camera.

But any economist will be reluctant to draw conclusions about causal connections or policy choices related to unemployment or investment strategies or vaccines from individual stories of real people. An economist will want to know about the statistics of all the people who were working, and which ones became unemployed; or the statistics that capture all the investment predictions made by a stock-picker, not just the ones that turned out well; or all the people who were vaccinated and what happened. Any single person being interviewed on camera may or may not represent the broader statistical reality. As the old saying goes, “The plural of `anecdote’ is not `data.'”

Daniel Simons and Christopher Chabris have developed a more elegant way of making this point clearly, and they offer an overview in “How the Possibility Grid Can Help You Evaluate Evidence Better” (Behavioral Scientist, July 17, 2023)

Consider the example of Mr. Pink Shirt, who recommended buying stock in Amazon and in Tesla years before the prices soared. Let us stipulate that Mr. Pink Shirt did indeed offer this advice. Should you take stock-picking advice from this person? Simons and Chabris offer a possibility grid to evaluate Mr. Pink Shirt.

The upper left-hand corner is the information presented to you: that is, Mr. Pink Shirt picked some stock market winners. The gray squares are the information not presented to you: that is, you don’t know what duds he picked, nor what winners he did not pick, nor what duds he did not pick. They write:

To avoid being deceived, we don’t need to know exactly how many stocks are in each box—just thinking about the possible contents of the full grid tells us there is no reason to believe that Mr. Pink Shirt, a guy who made two good picks in fourteen years, is worth paying attention to now. The possibility grid is a universal tool to draw attention to what is absent. It alerts you to think about rates of success rather than stories of successes. Applied to scientific research, the possibility grid reminds us that we can’t evaluate the state of the literature by tallying up only the significant results—we also have to think about the studies that failed or never got published. And it tells us to be wary when someone claims that their intervention will improve your performance or your health if they don’t show that the gains they promise are more likely to occur with than without their product’s help.

As the authors point out, when there is a great success story about someone who “just went with their gut” or “just knew what to do” or “just followed their bliss,” you can’t evaluate whether that course of action is useful to follow unless you have information about the rest of the probability grid. Sometimes people are lucky or unlucky. Sometime unlikely things do happen: an event that has only a 0.01% chance of happening will in fact actually happen one out of every 10,000 times–but you might not want to rely on it happening to you.

Mitchell List and Kurt Schuler serve as interlocutors in “An Interview with James D. Gwartney on His Life and Work in Economics” (August 2023 (Johns Hopkins Institute for Applied Economics, Global Health and the Study of Business Enterprise, SAE #238, August 2023). The interview offers an in-depth overview of his pathway to and within economics. here are a few of the points that caught my eye.

A One-Room Schoolhouse

I went to a one-room school, and when I was in eighth grade there were only 12 students in the entire school from kindergarten to eighth grade. The interesting thing about that is that when you were, say, in the fifth grade, you’d be able to follow what the sixth and seventh graders were doing, and as a result, it was easy to sort of work ahead and be doing things that the more advanced students were doing. We had some cold winters in Kansas, where you couldn’t be outside for lunch hour or recess, and the older students would often explain to younger students
how they could do certain kinds of things. Vernon Smith, a Nobel Prize-winning economist, also went to a one-room school in Kansas, and Vernon and I have talked about this. We both feel that at the elementary level we actually received a superior education compared to what students are getting today because of this interaction with students at a more advanced level. Then, as we progressed into the upper grades, we started explaining things to the younger students. As anybody who’s been in teaching knows, you often learn a lot about a subject yourself by communicating it to somebody else.

From his time with the Joint Economic Committee in Congress starting in 1999:

Even though we weren’t a legislative committee, we played a central role and we provided supporting research for eliminating the earnings test associated with receiving Social Security. After age 65, in those days, if you earned more than just a few thousand dollars, your Social Security payments would be reduced by 50 percent of your earnings. It meant that when you paid the payroll tax and maybe a little income tax and faced the 50 percent offset in loss of Social Security benefits, there was very little incentive for people over age 65 to work, so their labor force participation rate was low. We put together some estimates indicating that there would be a rise in the labor force participation rate, and projected that the government would actually gain revenue rather than lose revenue from eliminating the offset. That was, I think one could argue, the most important piece of legislation during the time that we were there. It exerted a lasting impact on the U.S. economy. Still today, the U.S. has one of the world’s highest labor force participation rates for people over age 65. Today, the U.S has a substantially higher labor force participation rate for people over age 65 than Western European countries primarily because of the legislation removing the loss of Social Security benefits as earnings increased.

About the motivation behind his well-known intro economics textbook, now in its 17th edition, and now co-authored by Richard Stroup, Russell Sobel, and David Macpherson:

The motivation to write the text was that it seemed to me that … there did not seem to be a general framework about how the political process worked. I wanted to integrate public choice analysis into a principles of economics text. Around 45 percent of [U.S.] GDP was allocated through the political process in 2020 and through most of the history of the book it’s been in the 30 to 35 percent range. So, you’re allocating a large share of resources through government, and we need to know something about how the political process works as well as how markets work.

In the very first edition in the preface, I made a statement that at the time economists [i.e., authors of other textbooks] were doing three things in economics. The first thing was that they used supply and demand to explain how markets worked. The second thing was, they explained why markets might not work so well for certain categories of activities, mainly externalities, public goods, and monopolies, which one would expect would be sources of economic inefficiency. Finally, they explained ideally what government could do to correct these failures, and that was the end of it. There was no analysis at all of the political process.

The political process is merely an alternative form of making decisions. We need to know something about how that process works as well as how markets work. This is the contribution of our text. Merely stating, “Here’s what the benevolent, omnipotent dictator” (an expression my friend Randy Holcombe likes to use when talking about the political process) “would do” is not very useful. Political decisionmakers may not be very benevolent, but even if they are benevolent, they’re not going to be omniscient, therefore there’s no reason to expect that they’re going to come up with ideal solutions. Even today, much of economics reflects this misleading view. Our book integrating public choice was really an attack on the idea that government is a corrective device that’s lying around so that if something goes wrong, we’ll just call on the corrective device and fix it. That seemed a very naive view of what the role of government in the economy should be. I believe this integration of public choice accounts for the staying power of our text.

As Gwartney tells his story of becoming an economist, I was struck by how his path through college and graduate school brought him in contact with economists who were at that time relatively early in their careers, but who became quite well-known. As one example, when Gwartney attended Ottawa University in Kansas, he took a number of classes from Wayne Angell, who later ended up being on the Federal Reserve Board of Governors from 1986-1994. When Gwartney took a first try at attending graduate school in economics at Washington State University, he didn’t make close connections with faculty members, and it went poorly. But when he ended up attending the University of Washington a few years later (with stops to work as an engineer at Boeing), he made a close connection with department chair Douglass North (Nobel ’93), as well as getting to know Walter Oi, and hearing a series of lectures from a visiting James Buchanan (Nobel ’86). Other personal connections, a blend of Gwartney’s own passions and serendipity, led to a stint of teaching at at Central European University in the mid-1990s, his involvement in the genesis of the Economic Freedom of the World volumes, and his time at the Joint Economic Committee. Thus, Gwartney’s description of his path seems to me a story of contingency, like many of our stories: it’s not just who you are or what your interests are or how hard you work that determines outcomes, but also the context in which you are operating and some key people you meet along the way.

Back around 2000, oh so long ago, e-commerce was 0.8% of total retail sales. Now, it’s about 15%. One result is that the shopping space in bricks-and-mortar regional shopping malls has declined sharply. In the next decade or so, could the new work-from-home patterns lead to a similar decline for commercial office space?

Tom Doolittle and Arthur Fliegelman of the Office of Financial Research sketch out this possibility in “Work-from-Home and the Future Consolidation of
the U.S. Commercial Real Estate Office Sector: The Decline of Regional Malls May Provide Insight” (OFR Brief Series 23-03, August 24, 2023).

(The Office of Financial Research is an independent bureau within the US Department of the Treasury. It was established by the  the Wall Street Reform and Consumer Protection Act of 2010 (commonly known as the Dodd-Frank act)(, with the goal of providing data and analysis on financial sector issues, especially those relating to aspects of financial stability.)

Here are the rising sales of e-commerce and the correspondingly declining sales of department stores in the last two decades. The OLR writes: “The number of U.S. regional malls peaked in 2006 at 1,522 (with nearly 1.4 billion square feet of GLA) and has since declined to 1,148 (with 1.0 billion square feet of GLA). The last regional mall built in the U.S. was completed in 2014, nine years ago.” GLA is the abbreviation for “gross leasable area.” There was also a negative feedback loop: “[A]s consumers chose not to shop at regional malls with fewer shopping options and sales at those malls declined further, catalyzing an additional exodus of tenants.”

Could a similar dynamic unfold for office space in an economy where work-from-home has become a viable option, at least some of the time, for a large share of workers? The official office vacancy rates is about 19%, up only modestly in the last couple of years. But the figure understates the issue, because a very large quantity is not technically vacant–that is, a firm is still paying to lease the space–but the firm is looking to “sub-lease” some of its space to another user, because it isn’t actually using the space. This figure show that the “occupancy” rate has risen since the pandemic hit in March 2020, but it’s still only around 50%.

A high desire for subleasing is a sign that when the original lease runs out, it probably won’t be renewed. OFR writes:

[D]emand for office space is actually weaker than reported due to the growth in office space available for sublease by firms that no longer need the space. Although
office space available for sublease remains rent bearing for a building owner, it portends lower future demand for office space because sublease space competes for tenants with existing vacant space, limiting its future absorption. It also signals that current tenants may renew their future leases for less space — also reducing
future demand. The amount of subleased office space has grown by nearly 130% since Q2 202011 to 210 million rentable square feet. As a point of comparison, during the Great Recession, available sublease space in the U.S. peaked at 147 million rentable square feet in Q2 2009.

If you add vacant unleased office space to the space available for subleasing, OFR calculates that the combined “structural” vacancy rate for office space is about 50%.

However, the effects of higher office vacancies are likely to unfold in slow motion. The average length of a commercial office space lease is 7 years, and leases of 10 year or more are not uncommon. Thus, the owners of many commercial office spaces are still getting (mostly) paid, and in turn, they can still make the payments on the loans they took out to buy the building.

The authors write: “The CRE office sector is currently estimated to be nearly $3.2 trillion, which is nine times as large as the regional mall sector was at its peak.” Thus, it is quite possible that investors in this sector could be exposed to losses of several hundred billion dollars in the medium-term. In addition, “[c]ommercial property taxes compose up to 10% of a city’s annual tax revenue, and the lion’s share of such taxes are on office buildings,” so city budgets would suffer as well.

Could the office buildings be converted to residential buildings? Maybe a few of them, but probably only a few. The OFR report notes:

[I]t is generally not cost-effective and may not be possible to redevelop marginal office buildings into apartment buildings. Multifamily buildings require more external surface area to internal area to accommodate windows for bedrooms and living areas than is required for office buildings, especially those with internal offices. Furthermore, the required replumbing, electrical, and life safety upgrades necessary to repurpose marginal offices are not cost-effective without subsidies. Often, the highest and best use for a marginal office building is demolition and using its land as surface parking, park area, or nothing at all.

I sometimes say that one of the main shifts of the pandemic is that a large share of what had been residential real estate was converted to commercial real estate–that is, it was converted to home offices. When people buy a house or rent an apartment now, one of the very real considerations–along with the standard kitchen, living room, bedrooms, and bathrooms–is where the home office will be. The real estate market will be living through the evolution of that shift for years to come.

The “socialist calculation debate” happened in the 1920s and 1930s. The economics profession was developing a vision of the economy as made up of prices and quantities for goods and services, based on supply and demand. Socialist economists (for example, Oskar Lange) sought to build on this framework. Their argument was along the following lines: “Given the advances in economics, it’s now possible to write down how the economy works in terms of supply, demand, prices, wages, and so on. However, free-market economists make the incorrect assumption that the outcome of market forces is (at least close to) the preferred social outcome. Socialists, on the other hand, can carry out the same calculations as to what a market economy would do. But then, the socialists can consider how government planning might improve on the market outcome. At a minimum, the result of socialist planning could reproduce the market outcome–thus, socialism will be at least as good as a market outcome. But socialism offers the possibility of improving on the market outcome as well.”

There are two types of responses to the socialist argument. One argument emphasizes that, in practice, government planning is inadequate to the task of handling the economy. Even writers as committed to socialism as Leon Trotsky wrote about how the government bureaucracy imagines that it has a “universal mind,” but it doesn’t, and as a result its attempts at economic planning–inevitably mixed with a degree of unreality from political pressures–cause shortages, low quality of output, and inefficiencies.

The second main argument (often associated with Friedrich Hayek) holds that, even in principle, detailed government economic planning is impossible, because an economy is actually a process of contextual discovery. Firms do not know their costs of production, or how they will to react to unexpected shocks or new technologies, until it actually happens. Consumers don’t know what choices they will make, given a range of possible goods and prices, until they actually make those choices. Workers don’t know what jobs they prefer until they consider the options. No one knows in advance what innovations will work well in production, or be highly desired by consumers, until these innovations are tried out. Government can still have specific roles that put a thumb on the scale of unconstricted market outcomes: redistributing income to the poor, supporting education and infrastructure, reducing pollution, and the like. But from this view, the idea of a central planner foreseeing all outcomes of quantity, quality, innovation, prices, and wages to reproduce the market economy outcomes is literally impossible.

Back in the 1930s, and since then as well, one response of the socialists has been to say that as computing power improves, the feasibility of socialist calculation will improve as well. Perhaps the new developments in artificial intelligence, for example, are leading to situation where detailed socialist central economic planning will outcompete market outcomes. Peter J. Boettke and Rosolino A. Candela offer some thoughts about this scenario in “On the feasibility of technosocialism” (Journal of Economic Behavior and Organization, 2023 (205), pp. 44-54).

They start with as pure a statement of how additional computing power will make planned-economy socialism possible as you are ever likely to find, from the Chinese business leader Jack Ma, founder of Alibaba. Ma says:

Over the past 100 years, we have come to believe that the market economy is the best system, but in my opinion, there will be a significant change in the next three decades, and the planned economy will become increasingly big. Why? Because with access to all kinds of data, we may be able to find the invisible hand of the market. The planned economy I am talking about is not the same as the one used by the Soviet Union or at the beginning of the founding of the People’s Republic of China. The biggest difference between the market economy and planned economy is that the former has the invisible hand of market forces. In the era of big data, the abilities of human beings in obtaining and processing data are greater than you can imagine. With the help of artificial intelligence or multiple intelligence, our perception of the world will be elevated to a new level. As such, big data will make the market smarter and make it possible to plan and predict market forces so as to allow us to finally achieve a planned economy.

Ma’s comments, of course, is an implicit acknowledgement that planned economies of the past have not worked very well. Will this time be different? Boettke and Candela point out that Ma’s argument has a lot of other modern proponents, but write:

However, we argue that the proposal provided by technosocialism is analogous to putting old wine into an irrelevant new bottle. What seems to be a novel proposal to deliver the age-old aspiration of socialism is not fundamentally different from the market-socialist model which had been proposed by Oskar Lange and Abba Lerner in the 1930s in response to Ludwig von Mises and F.A. Hayek, both of whom had argued that economic calculation under socialism was impossible. Lange would later propose the following in response to Mises and Hayek: “Let us put the simultaneous equations on an electronic computer and we shall obtain the solution in less than a second. The market process with its cumbersome tâtonnements appears old-fashioned. Indeed, it may be considered as a computing device of the pre-electronic age”(emphasis in original; 1967: 158). … However, Lange’s assessment, like that of technosocialism, is based on a fundamental misunderstanding of the economic problem of society as being of a computational nature rather than a “knowledge problem” that must be addressed and the nature of how the market process in fact does address the problem.

Boettke and Candela review the players and arguments in the classic socialist calculation debate. However, they take the Hayekian position that a market economy itself is a social device for discovering, using and disseminating information in a wide array of real-world contexts, in a way that no computer can be programmed to replace. They write:

[I]f one assumes perfect knowledge and static conditions, then the problem of economic calculation is solved by hypothesis. Economic calculation is a tool that enables actors to steer a course in a turbulent sea of economic uncertainty, of ceaseless change, of ignorance of the environment, and of alluring hopes and haunting fears. Once all those are assumed away, then the functional significance of economic calculation disappears. But so would opportunities for mutual gain, entrepreneurial innovations, and discovery of new opportunities. In other words, if you assume away change, you assume away the possibility of economic growth and progress. … The market is a social learning process.

Of course, the authors are not arguing that advances in computing power will not affect economies, production, and jobs–as well as key questions in the field of economics. However, they are making a case that thinking of the economy as a ginormous math problem–and a problem where central planners can not only solve it, but tinker with the variables and get different results as desired–misses out on a central aspect of just what an economy is and does.