Conversable Economist

One of the famous anecdotes in economics is about division of labor in a pin factory, as told by Adam Smith starting in the third paragraph of The Wealth of Nations. (One suspects the fame of the story is partly related to the fact anyone who cracks open the book will find it at the very beginning.) Smith notes in the text that his example was already common at the time he used it. But those who specialize in this area have pointed that Smith’s example was based on second- and third-hand reporting, while actual studies of pin-making in the 18th century suggest that it may not be a great example of the gains from division of labor.

As a starting point, here’s how Smith tells the pin factory story in the third paragraph of the Wealth of Nations:

To take an example, therefore, from a very trifling manufacture; but one in which the division of labour has been very often taken notice of, the trade of the pin-maker; a workman not educated to this business (which the division of labour has rendered a distinct trade), nor acquainted with the use of the machinery employed in it (to the invention of which the same division of labour has probably given occasion), could scarce, perhaps, with his utmost industry, make one pin in a day, and certainly could not make twenty. But in the way in which this business is now carried on, not only the whole work is a peculiar trade, but it is divided into a number of branches, of which the greater part are likewise peculiar trades. One man draws out the wire, another straights it, a third cuts it, a fourth points it, a fifth grinds it at the top for receiving the head; to make the head requires two or three distinct operations; to put it on, is a peculiar business, to whiten the pins is another; it is even a trade by itself to put them into the paper; and the important business of making a pin is, in this manner, divided into about eighteen distinct operations, which, in some manufactories, are all performed by distinct hands, though in others the same man will sometimes perform two or three of them. I have seen a small manufactory of this kind where ten men only were employed, and where some of them consequently performed two or three distinct operations. But though they were very poor, and therefore but indifferently accommodated with the necessary machinery, they could, when they exerted themselves, make among them about twelve pounds of pins in a day. There are in a pound upwards of four thousand pins of a middling size. Those ten persons, therefore, could make among them upwards of forty-eight thousand pins in a day. Each person, therefore, making a tenth part of forty-eight thousand pins, might be considered as making four thousand eight hundred pins in a day. But if they had all wrought separately and independently, and without any of them having been educated to this peculiar business, they certainly could not each of them have made twenty, perhaps not one pin in a day; that is, certainly, not the two hundred and fortieth, perhaps not the four thousand eight hundredth part of what they are at present capable of performing, in consequence of a proper division and combination of their different operations.

When Smith writes at the start that pin manufacturing is “one in which the division of labour has been very often taken notice of,” what does he have mind? The standard answer seems to be an entry in Denis Diderot’s Encyclopedia, published in 1755, which seems partially correct. Jean-Louis Peaucelle and Cameron Guthrie dig deeper in “How Adam Smith Found Inspiration in French Texts on Pin Making in the Eighteenth Century” (History of Economic Ideas, 2011, 19: 3, pp. 41-67, available via JSTOR). They write:

Adam Smith used four French sources on pin-making: Journal des sçavans, 1761, Delaire’s article «Pin» in Diderot’s Encyclopaedia (1755), Duhamel’s The pinmaker’s art (1761), and Macquer’s Portative arts and crafts dictionary (1766) … We will see that the original texts do not support Smith’s analysis. The workers were specialized in eight or nine trades, and not eighteen as Smith understood. In a work shop there were many workers for heading but very few for cutting the pins, for example. Attempts to divide this latter operation further were unsuccessful. One of the original texts that Smith did not consult also provides an example of production without specialisation where productivity was a hundred times higher than Adam Smith believed.

However, the works on which Smith was drawing were often second-hand, based on earlier research. Apparently, the studies of pin-making in France apparently started around 1675, King Louis XIV asked the French Academy of Sciences to write up a detailed description of the arts and crafts. After some local efforts along these lines by trade inspectors, the first of these reports by Gilles Filleau des Billette was completed in 1702, but never published. However, he described 12 operations involved in making pins, calculated a speed of production for 10 of the operations, and provided a picture of the tools used for each one, with four workers carrying out the tasks.

Thus, Mathieu de Guéroult de Boisrobert, known as Guéroult, did a new study in 1715. He describes seven occupations involved in pin-making, although it’s not clear that they are done by seven different people.

“The first printed text about pin making is an article in the Universal trade dictionary, published in 1723 by Savary. Jacques Savary des Bruslons (1657-1715) was director of customs and collected for his own use all available information from the central Royal Administration and Academy. This information formed the basis of his dictionary.” He wrote that pin-making involved “more than 25 laborers, working in succession.” But this seems to involve an assumption that there was a different laborer for each task named in the earlier reports, rather than each laborer taking on multiple tasks.

Next in line was Jean-Rodolphe Perronet, who wrote an unpublished manuscript in 1739, which although it was a new work had a description quite similar to that of Guéroult–perhaps not surprising, given that Perronet succeeded Guéroult as an engineer in Avignon.

All of this leads up to the article in Diderot’s Encyclopedia by Alexandre Delaire: “Delaire wrote as if he had personally observed workshop activity: «this article is written by Mr. Delaire who describes the manufacture of pins in the workshops with the workers themselves» (Delaire 1755, 807). But this was not true. An analysis of the parts of Delaire’s article reveals his sources. The technical vocabulary was copied from previous descriptions of pin making, authored by Savary, Guéroult, Perronet, and Réaumur.” Apparently what happened here was that in an earlier version of the Encyclopedia, the Jesuits accused Diderot of copying their article on pins. So Diderot hired Delaire, who ‘had studied literature and knew very little about technology,” to write up a blend of the earlier sources in a way that wouldn’t be susceptible to the accusation of copying.

There’s more about all these linkages, but for the purposes of economists referring to this example today, perhaps the more interesting question is not the interrelationship between all the sources, but whether Adam Smith is basically telling the truth about pin manufacturing. There is reason for doubt.

1. At a basic level, the count of operations in pin-making is suspect. Delaire is the one who came up with 18 “operations,” but in most places, these did not involve separate workers. At most, there seem to be 8 or 9 different types of workers.
2. Smith’s estimate of the number of pins to be made by a single person in a day is made up. The 1723 report from Savary suggests: “The productive power of labour would be some 2,000 pins per day and per pin-maker working without any division of labour. Productivity im provements would not have been as spectacular as Adam Smith imagined. They would have been closer to a factor of 2.4 rather than 240.”
3. In pin-making around Smith’s time, pin-makers with fewer employees seemed to compete with those with more employees on an equal basis. They all seemed to draw from the same pool of unskilled labor, and to pay similar wages. In that sense, pin-making firms with greater division of labor did not seem more efficient, and workers often switched between tasks rather than specializing in a certain task.

In 1794 an inventory of workshops was undertaken in Bourth, 10 km from Laigle. 500 pinmakers worked in 70 workshops. The average of 7 workers per workshop however is misleading. 40% of workers were employed in small workshops of 6 people of less, 40% in workshops of 7 to 9 workers, and 20% in large workshops with 10 to 20 workers (Marchand 1966, 35). Workshops of different sizes coexisted. The organisation of labour varied according to the size of the workshop. It was not standardized. There were no economies of scale, nor any productivity gains in large workshops where pin makers could be more specialized. No workshop would have had a significant advantage over another. The productivity of labour and the level of wages were the same. More di vided labour wasn’t more productive. The theory of the division of labour does not hold true in Smith’s first example, that of pin making.

4) The most important division of labor in pin-making during the 18th century may have been that certain tasks were reserved for men or for women. In his 1715 study, Guéroult noted that there were roughly twice as many women as men in the pin-making firms, focused on certain tasks (like putting the heads on pins), and typically paid less than half as much. This particular aspect of the division of labor typically goes unmentioned in modern pedagogy.

A few years ago, John Kay looked at this evidence and argued that teaching about the division of labor was useful, even if Smith’s use of the historical evidence was oversimplified at best. Kay wrote:

We might conclude that neither Smith nor Ferguson, neither Diderot nor Delaire, knew anything about the pin factories they claimed to describe. But does it matter? The two Frenchmen are more worthy of censure, because their readers might have been misled into thinking that their description provided guidance as to how you made pins. The two Scotsmen were making an important, and justly influential, argument even if the particular illustration they used in its support was wrong. In business schools, I have sometimes engaged in argument over whether the case studies that teachers use to illustrate issues need be true. The lesson of the pin factory is that it probably doesn’t matter. My students needed to understand the division of labour. Few if any needed to understand techniques of manufacturing pins in eighteenth century France.

In a similar spirit, Peaucelle and Guthrie conclude their article by writing: “The weak probative value of his [Adam Smith’s] pin-making example takes nothing away from the reach of his economic ideas.”

I have qualms on this point. Examples should stand and fall, at least to some extent, on their actual merits, not on whether they are picturesque. At very least, when using an historical example that is vivid and imperfect, it seems important to know something of the strengths and weaknesses that lurk in the background.

About 35 years ago, when I started my career as the managing editor of an economics journal, producing figure and tables was expensive. My memory is that at Princeton University, where I was based at the time, there was still a skilled draftsman who hand-drew beautiful figures, plotting the points and and then putting in a best-fit curve for the data using French curves.

For those born after 1980 (or 1970?), a French curve was a clear piece of plastic with a smooth edge that combined many different types of curves. The design is commonly attributed to the German mathematician Ludwig Bermester (1840-1927).  There were three primary French curves: one for hyperbolas, one for ellipses, and one for parabolas. You rotated the French curve over your data until one of the curves seemed to fit the points, and then used the edge of the curve to draw a smooth curved line. Drawing publishable figure was once a specialized skill. In 8^th-grade shop class in my Minnesota junior high school, the boys were required to take a one-quarter class in mechanical drawing, where we sat at sloped drafting tables and learned how to make blueprint-style detailed drawings of a screw, top and side views, with the head, the threaded shank, and the point precisely delineated. French curves were far too high-end for us.  

Figures have gone from time-consuming and expensive to dirt cheap. As an economist, I’m generally in favor of improvements in quality accompanied by a sharp drop in price. But the related economic lessons are that when something gets much cheaper, it may be used much more often. When something is used much more often, diminishing returns may arise: while the first few figures may be illuminating and valuable, the last few are likely to range from overkill to actively confusing.  

In addition, researchers have an incentive to generate lots of figures and tables as the basis for seminar presentations, so that listeners have something to look at.  By the time that the researcher writes up the paper for publication, long propinquity to the figures has made them part of how the researcher conceives of the ideas.

Put it all together, and a few decades ago it was fairly common for me to receive a first draft with zero figures, or just a few. Now, it’s not unusual for me to receive a first draft with 10, 15, even 20 figures and tables—some of those with four or six or 12 separate panels.  The paper can ends up feeling like a string of figures, each accompanied by bite-sized chunks of text.

Thus, I would promulgate some guidelines both for reducing the clutter of too many figures and for improving the quality of the remaining figures in written presentations.

1. Written and spoken communication differ, just as reading and listening differ. In spoken exposition, summarizing a simple pattern with a simple bar graph or a line chart can help a listener focus. But for a reader, sometimes it’s just better to give people the numbers. Just because software will generate a figure doesn’t mean the figure is a good way of explaining to readers.
2. Remember the basics. Figures need a title, and labels on the axes. Multiple lines or bars need labels, too. Use the note under the figure to list sources of data and to explain any abbreviations.
3. A set of five or seven or eleven lines on a graph, each with its own separate key—one solid, one dashed, one dotted, one dash-dot-dash-dot, one dot-dot-dash, dot-dot-dash, and so on—requires some rethinking.  
4. It’s generally better—although admittedly not always practical— to label lines or bars directly, rather than using a separate key under the paper, which requires the eyes of the reader to jump back and forth.
5. A greater ability to use color is one of the great and useful breakthroughs of modern graphics.  Take advantage. But remember that some readers are red/green or blue/green or yellow/red colorblind. When using shades of color, the human eye is best at perceiving multiple shades of green, and worst at perceiving multiple shades of yellow.
6. Sometimes it’s useful to label points: perhaps they represent countries or US states. But be cautious about labelling every country or state, which can lead to a blur of overlapping and unreadable labels. It’s often better to pick a few points worthy of labelling—perhaps specific points discussed directly in the text.
7. A figure takes up the space of several hundred words. If it takes one or two sentences to convey the message of a figure, then the figure becomes just a big weirdly-shaped exclamation point for a message already fully conveyed in the text and dropping the figure probably makes sense.
8. If you can’t make a good Figure 1 for an empirical paper with raw data, you ultimately aren’t likely to convince a lot of people (a saying I have heard attributed to the economist Steven Levitt).
9. In the same way that you will automatically try to keep current with the evolution of terminology in your field of research,   keep expanding your vocabulary for presentation of data.  William Playfair, who invented the basic pie graph, bar graph, and line graph, died almost 200 years ago in 1823. More options are now available: bubble charts, waterfall charts, the bullet-graph variation on a bar chart, Mekko charts, heat maps of the cluster or spatial variety, and others.  
10. If you’ve been a victim of figures ranging from purposeless to indecipherable, don’t be a perpetrator. If you can’t remember having been a victim, take a closer look at the figures you are producing.

An advertising executive named Frank Barnard popularized the phrase, “A picture is worth a thousand words.” But Barnard was writing a century ago, and his topic was how to design advertising for the sides of moving streetcars.  Now that modern statistical software can spit out a suite of figures on demand to be cut-and-pasted over to Powerpoint slides, Barnard’s rule of thumb needs rethinking.

The best figures are worth much more than a thousand words; indeed, a few well-chosen and well-constructed figures can sometimes convey the main arguments of an article (at least to a reader already somewhat knowledgeable in the subject). But figures can also be extraneous and unclear—imposing higher costs on readers than any plausible benefit. Expository wisdom involves learning the difference.

---

Even in this time when any yahoo with a computer can self-publish a blog like this one–or perhaps especially in this time–there is still an honor in being published in a more formal way in a a recognized serial publication or by a known publisher. However, the honor comes with a price. Specifically, you need to deal with the editors at the recognized publication, who may interrupt your life with a lengthy series of requests for multiple rounds of time-consuming revisions and changes. Some of these changes may seem useful to you, and some may not. But it’s the quantity of them, arriving over a period of months or even years, that wear you out.

This process is what the English historian G.M Young was referring to when he apparently said: “Being published by the Oxford University Press is rather like being married to a duchess: the honour is almost greater than the pleasure.”

I say “apparently” because the quotation is attributed to Young in a letter from Rupert Hart-Davis to George Lyttelton in The Lyttelton Hart-Davis letters : correspondence of George Lyttelton and Rupert Hart-Davis (vol. 1, p. 122, letter of April 29, 1956).

The problem can be apparent from the publisher’s side, too. The New Yorker magazine of several decades ago was (in)famous for its detailed editing and fact-checking. The editor at the time, Harold Ross, once wrote in a letter to H.L. Mencken: ““We have carried editing to a very high degree of fussiness here, probably to a point approaching the ultimate. I don’t know how to get it under control.” The quotation can be found in Letters from the Editor: The New Yorker’s Harold Ross, edited by Thomas Kunkel (letter of November 9, 1948).

The “honor” of publication is reminiscent of the story commonly attributed to Abraham Lincoln, when he was asked about the “honor” of being the President of the United States during the US Civil War. Lincoln is supposed to have said: “You have heard the story, haven’t you, about the man who was tarred and feathered and carried out of town on a rail? A man in the crowd asked him how he liked it. His reply was that if it was not for the honor of the thing, he would much rather walk.”

Here, I say “attributed” because the quotation comes from a book written many years later: that is, Emanuel Hertz, Lincoln Talks: A Biography in Anecdote (1939, pp. 258-59). I don’t know of a more contemporaneous source. Thus, I include it here in the blog, but an fussy editor might well ask me to rewrite the attribution three times, and then to leave it out altogether.

Toni Morrison (Nobel ’93) described how, for her, writing is a process of self-editing and rewriting. This is from “The Site of Memory,” which appeared in the 1995 (second) edition of Inventing the Truth: The Art and Craft of Memoir, edited by William Zinsser (pp. 83-102). Here’s Morrison:

By now I know how to get to that place where something is working. I didn’t always know; I thought every thought I had was interesting — because it was mine. Now I know better how to throw away things that are not useful. …

When you first start writing – and I think its true for a lot of beginning writers – you’re scared to death that if you don’t get that sentence right that minute it’s never going to show up again. And it isn’t. But it doesn’t matter another one will, and it’ll probably be better. And I don’t mind writing badly for a couple of days because I know I can fix it — and fix it again and again and again, and it will be better. I don’t have the hysteria that used to accompany some of those dazzling passages that I thought the world was just dying for me to remember. I’m a little more sanguine about it now. Because the best part of it all, the absolutely most delicious part, is finishing it and then doing it over. That’s the thrill of a lifetime for me: if I can just get done with that first phase and then have infinite time to fix it and change it. I rewrite a lot, over and over again, so that it looks like I never did. I try to make it look like I never touched it, and that takes a lot of time and a lot of sweat.

Rachel Glennerster is a professor of economics at the University of Chicago, which is more-or-less the dictionary definition of an academic economist. But earlier in her career, she worked as a policy economist at the UK Treasury, the IMF, and the the UK Foreign, Commonwealth & Development Office, which focuses on topics of international economic cooperation and foreign aid. When it comes to distinctions between academic and policy economists, she knows whereof she speaks. In a blog post back in 2014, she summarized the distinctions with this table.

There are some economists who can move fluidly between the academic and the policy world. But the table helps to explain why many don’t make the jump very well, or prefer not to try.

Here’s a comment from Lant Pritchett in an interview last June. He was asked: “What is the role of an economist?” He answered:

The thing I like most about the field of economics is that it is still mostly people who are open to empirically grounded discussions of problems in which you’ll acknowledge what the facts are and alternative approaches to modalities of making the facts different.

Then the other thing … I don’t really teach undergraduates very often, but I was invited to give the opening lecture to a development economics course of undergraduates. My take was that economics is the social science of love. It’s the truly loving social science, and what I meant—and they were, of course, like, “What? Economics and love? That’s crazy.” But think about what economists do. We take individuals—objective functions are objective functions. We don’t start with any premise about what would be good for society or good for X or good for Y.

But I think economists, when they’re doing it right, they start from, what is it that people want to accomplish with their lives? Okay. Let’s think about what the actual outcomes are. Let’s think about modalities at the society, political, market level that would facilitate individuals achieving their objectives more or less. And what could be a better description of love than “I’m going to take—what you want is what I want for you, and I’m going to help you achieve that.” Economics is the loving social science, is my take on what economists do best.

I speak from personal experience when I say that perhaps the professional advantage of economists is not greatest in discussions and definitions of love. But what I like about Pritchett’s comment is that so many noneconomists I meet think about the subject in terms of topics like how to make money in the stock market or how to run a profitable business. Pritchett’s definition has its limitations. But at least it captures the idea of economics as subject that focuses on what people want for themselves, and thus on the importance of people having freedom to make choices about work, skill acquisition, and types of consumption.

For those who would like a little more love-talk from economists, in a post some years back about “Is Altruism a Scarce Resource that Needs Conserving?“, I discuss the line of argument among some economists that by allowing a substantial portion of the world’s material needs to be met by the actions of self-interested producers and consumers, we can save our scarce resources of love and altruism for where they are needed.

My tradition on this blog is to take a break (mostly!) from current events in the later part of August. Instead, I pre-schedule daily posts based on things I read during the year about three of my preoccupations: economics, academia, and writing.

___________________

For economists, “widgets” are the example of a hypothetical product you use when you don’t want to get specific. Another common hypothetical product is “leets,” which is “steel” spelled backward. But where did the terminology of widgets first appear, and how did it work its way over to economics?

According to the Oxford English dictionary, the etymology of “widgets” is unclear. It’s sometimes thought to be a spin-off of “gadgets,” but there don’t seem to be examples to support this claim. Instead, the origin of “widgets” is usually credited to the playwrights George S. Kaufman and Marc Connelly in their 1924 play, Beggar on Horseback.

The play revolves around Neil McRae, who is a poor and unknown composer of classical music, working odd jobs to get by. There is a wealthy industrialist named Mr. Cady, with a beautiful daughter named Gladys. Will Neil give up his classical music dreams, marry the boss’s daughter, and work at the factory? In the play, the factory makes “widgets.” Here’s some dialogue from the play between Neil, Mr. Cady, and a secretary named Miss You:

CADY: Why, Neil!

NEIL: Here I am—at work!

CADY: Yes, sir! Business! Big business!

NEIL: Yes. Big business. What business are we in?

CADY: Widgets. We’re in the widget business.

NEIL: The widget business?

CADY: Yes, sir! I suppose I’m the biggest manufacturer in the world of overhead and underground A-erial widgets. Miss You!

MISS YOU: Yes, sir.

CADY: Let’s hear what our business was during the first six months of the fiscal year. [To Neil.] The annual report.

MISS YOU [Reading.]: “The turnover in the widget industry last year was greater than ever. If placed alongside the Woolworth Building it would stretch to the moon. The operating expenses alone would furnish every man, woman and child in the United States, China and
similar places with enough to last for eighteen and one-half years, if laid end to end.”

CADY: How’s that?

NEIL: It’s wonderful!

CADY: And wait for September 17th!

NEIL: Why?

CADY: That’s to be National Widget Week! The whole country!

NEIL: That’s fine, but what I came up about …

CADY: Never mind that now—we’ve got more important things. Conferences, mostly.

The terminology of widget seems to have caught hold fairly soon. I was especially struck by this short 1939 movie by the General Motors Department of Public Relations. It’s called “Round and Round,” and as you will see, it’s an attempt to describe a circular flow in the economy. It’s about a factory that uses skilled labor and machines to make widgets. As the video explains: “A widget might be a radio, a refrigerator, a musical instrument, or a motor car. A widget, you know, is just a symbol for any manufactured product that people use.” The factory sells widgets to farmers, coal miners, steel manufacturers, and others. In turn, they use the widgets to produce the inputs needed by the widget manufacturer to make more widgets.

In 1969, the Guinness company decided to take the widget out of the hypothetical, and to make and patent an actual product that has come to be called a “widget.” The company filed a patent application in Ireland for an “Improved Method of and Means of Dispensing Carbonated Liquids from Containers.” As explained here, the widget is a small plastic ball with a hole in it that sits inside a can of beer. When the beer is put under pressure, there is nitrogenated beer under pressure inside this hole. When the can is popped open, this extra dose of nitrogenated beer combines with the rest of the beer in the can to produce a foamy head on the beer as it is poured.

Modern software programmers have also tried to commandeer the terminology of widgets for their own. For example, the Techopedia webpage defines widgets in this way:

Widget is a broad term that can refer to either any GUI (graphical user interface) element or a tiny application that can display information and/or interact with the user. A widget can be as rudimentary as a button, scroll bar, label, dialog box or check box; or it can be something slightly more sophisticated like a search box, tiny map, clock, visitor counter or unit converter. … The term widget is understood to include both the graphical portion, with which the user interacts, and the code responsible for the widget’s functionality.

This seems a long way from National Widget Week as conceived by Kaufman and Connelly back in 1924! But economists have by and large shrugged off the attempts by beer companies and software firms to appropriate their single most prominent hypothetical example. Instead, economics lecturers stick with the meaning of “widget” as defined by the General Motors Public Relations Department.

For some decades now, the world has been following the patterns of a demographic transition with life expectancies rising and birth rates falling, as we head for a world where the elderly are a much larger share of the global population. However, Matthias Doepke, Anne Hannusch, Fabian Kindermann, and Michèle Tertilt argue that it’s time for “The New Economics of Fertility” (IZA Discussion Paper #15224, April 2022). For a short readable overview of the main themes, you can check their shorter discussion at the VoxEU website (June 11, 2022).

From the abstract of the academic paper, the authors write:

In this survey, we argue that the economic analysis of fertility has entered a new era. First-generation models of fertility choice were designed to account for two empirical regularities that, in the past, held both across countries and across families in a given
country: a negative relationship between income and fertility, and another negative
relationship between women’s labor force participation and fertility. The economics of
fertility has entered a new era because these stylized facts no longer universally hold. In
high-income countries, the income-fertility relationship has flattened and in some cases
reversed, and the cross-country relationship between women’s labor force participation
and fertility is now positive.

A couple of pictures may help, here. It used to be that countries with higher incomes had lower fertility rates, but among high-income countries, this pattern no longer holds. Here’s a figure taken from the VoxEU overview. The top panel shows that within the group of high-income countries in 1980, countries with higher per capita GDP had lower fertility, but by 2000, countries in this group with higher per capita income had higher fertility.

What about the relationship between women’s fertility and the labor force participation rate of women? Here’s the parallel figure. It shows that in 1980, within the group of high-income countries, those with higher fertility tended to have lower labor market participation for women; by 2000, the countries with higher fertility tended to have higher labor force participation for women.

The previous theories of fertility were based on some intuitively plausible claims. As incomes went up in a given country, the opportunity costs of having a child went up, so women would be more likely to enter the labor force and fertility would decline. But now it appears that as incomes rise in a given country, women are likely to have more children and also to spend more time in the labor force. Instead of higher incomes being less compatible with children and with being in the workforce, they are apparently becoming more compatible. The authors write:

We highlight a number of factors that have blunted the forces emphasized by the first generation of economic models of fertility. For example, in high-income countries, child labor has disappeared and education for most children continues past childhood into the adult years. These changes imply that the tradeoff inherent in quantity-quality models between sending children to school versus having more resources to raise a larger family has lost salience. Similarly, models based on women’s opportunity cost of time posit that raising more children requires mothers to spend less time working in the market. While this tradeoff still exists today, it has weakened as alternative forms of childcare have become more prominent. When childcare is provided by someone other than the mother—whether a hired nanny, a government-run kindergarten, or the child’s father—the cost of children is no longer linked as directly to the mother’s opportunity cost of time.

To explain why the empirical relationship between women’s labor force participation and
fertility has not just flattened, but entirely reverted, research has taken directions that go
beyond the first-generation models. A general theme in this new literature is that the compatibility of family and career has become a key determinant of fertility in high-income economies. Where the two are easy to combine, many women have both a career and multiple children, resulting in high fertility and high female labor force participation. When career and family goals are in conflict, fewer women work and fewer babies are born. We point out four factors that help mothers combine a career with a larger family: the availability of public child care and other supportive family policies; greater contributions from fathers in providing childcare; social norms in favor of working mothers; and flexible labor markets.

It is far too early to discern whether these kinds of shifts will alter global pattern of lower birthrates. But it does suggest that those who would prefer rising birthrates should focus on policies and norms that make it easier for women to work; conversely, those who prefer lower birthrates might prefer policies and norms that increase the tradeoffs for women of entering the workplace.

“Globotics” is the name that Richard Baldwin gave to the combination of globalization and robotics in service jobs. In his essay “Globotics and macroeconomics: Globalisation and automation of the service sector” (presented at the ECB Forum on Central Banking 2022, June 27-29, where videos of presentations and comments are included), he argues that you can’t understand the likely future of globalization without it.

Baldwin argued that the global economy is in the throes of a third “unbundling” of globalization, which is a phrase he uses to describe the driving force behind a shift in what is traded across global borders. In his telling, the first “unbundling” “happened when steam power and Pax Britannica radically lowered the cost of moving goods,” and the unfolding process of reduced physical transportation costs over the decades drove the rise of globalization from the 19th century up to the 1960s or 1970s (with interruptions for world wars, the Great Depression, and other events).

The second “unbundling” kicked in around 1990. It wasn’t about transportation costs, but rather about information and communication technology (ICT) and how it affected firms in big high-income countries like the G7 group (the United States, Canada, Great Britain, France, Germany, Italy, Japan). In particular, it wasn’t about how economies of some countries were able to produce goods at different prices, which is the standard intro-level theory of trade, but rather how a combination of higher-technology manufacturing firms in high-income countries could coordinate their production chain with lower-wage labor in other countries. Baldwin writes:

Globalisation changed dramatically around 1990 when it entered its offshoring-expansion
phase, or what I have called the “second unbundling” to contrast it with the first unbundling (Baldwin 2006). This was triggered by the ICT revolution which relaxed the second separation cost – communication and coordination costs. ICT made it feasible for G7 firms to fragment highly complex industrial processes into production stages, and then spatially unbundle some of them to low-wage nations. Think of this as the offshoring-expansion phase of globalisation where G7 manufacturing firms seized low-hanging opportunities for combining their advanced manufacturing knowhow with foreign low-wage labour in factories set up abroad. As the offshored process had to continue to operate as if it were still bundled, we can think of this as factories crossing borders, not just goods. Trade boomed again.

This third “unbundling,” now underway, is about how the newest versions of interconnected information and communications technology, which one might just call the digital economy, are connecting services industries. Indeed, although the rise in international trade in goods has more-or-less levelled off since about 2008, international trade in services has continued to rise and is becoming an ever-larger share of international trade.

What exactly are these “other commercial services”?

The OCS category consists of a few big items and many small items. Some are easily recognisable. Among the bigger categories are Financial Services (9%), and payments for intellectual property rights. The category Telecommunications, Computer, and Information Services accounts for 11% of the total; much of this is made up of computer services related to software, but a large share is tossed into the category ‘Other computer services other than cloud computing’ (this is typical of the lack of precision in trade statistics). The largest sub-category (23%) is ‘Other Business Services’. This includes a broad array of services. Some – like Architectural, Financial, Engineering, R&D, Advertising and Marketing, and Professional and Management Consulting services – are easily associated with sectors and jobs. Others, like Operating Lease Services, and ‘Other Business Services, not elsewhere included’ are difficult to map into jobs and sectors in the domestic economy.

In my own mind, it’s perhaps useful to think of the third “unbundling” in terms of working from home. If your job is one that can be entirely done by someone working from home, by a telecommuter, then it can be done by someone outside the country. As one of many examples, the K-12 and higher education systems just spent a year delivering their services on-line. Baldwin writes:

Note that the arbitrage here is direct wage competition among service sector workers, and wage differences are probably the largest unexploited arbitrage left in today’s world. Taking Colombia as an example of a middle-income emerging market, a recent study matched the US’s occupation classifications with those of Colombia to compare wage rates (Baldwin, Cardenaz, and Fernandez 2021). Focusing only on the occupations that Dingel and Neiman (2020) have classified as teleworkable in the US, the study found that the wages in the US were on average 1500% higher in the US than in Colombia. Plainly low wages are not the only source of competitiveness in services but with wage gaps being that large, it is likely that the digitech-driven globalisation of the service sector will have an impact on prices in advanced economies.

Some of the arbitrage is done via online freelancing platforms like Upwork, Freelancer, and Zhubajie (these are like eBay but for services). Wage comparisons based on worker-level data scrapped from such online freelancing platforms confirm the presence of enormous wage gaps, although the size varies greatly according to the data selection criteria. Data from a number of the largest freelance platforms reported in ILO (2021) indicate that average hourly earnings paid in a typical week for those engaged in online work is US$4.9, with the majority of workers (66%) earning less than the average. While $4.90 an hour seems like a low wage in Europe, it corresponds to full-time equivalent salary of about $10,000 per year – a salary which is considered comfortably middle-class in most countries.

Baldwin argues that the low-hanging fruit in this area is “intermediate services.” For example, it might be hard for a variety of regulatory reasons for a US firm to hire accountants directly from a company based in India or Brazil or Indonesia. But it’s pretty easy for US-based accounting firm to hire those accountants from other places, and to coordinate their work when delivering accounting services to US-based firms. Moreover, for a lot of emerging market economies, providing services can be pretty straightforward.

[E]xport capacity in emerging markets is not as great a limiting factor in services as it is in goods since every nation has a workforce that is already producing intermediate-service tasks. All emerging market economies have bookkeepers, forensic accountants, CV screeners, administrative assistants, online client help staff, graphic designers, copyeditors, personal assistants, travel agents, software engineers, lawyers who can check contracts, financial analysts who can write reports, etc. There is no need to develop whole new sectors, build factories, or develop farms or mines.

The term “slobalization” is used to describe the level of globalization slowing down. When it come to trade in goods, slobilization applies. But Baldwin’s analysis implies that the world economy may already be seeing the roots of a substantial rise in globalization that will happen via the services sector.

The idea of “place-based” economic policies is to focus on those geographic places–sometimes urban areas, sometimes neighborhoods within an urban area–where jobs are especially scarce and incomes especially low. Timothy J. Bartik offers some thoughts on how best to do this in “How State Governments Can Target Job Opportunities to Distressed Places” (Upjohn Institute Technical Report No. 22‐044, June 2022). There’s also a short readable overview in the most recent Employment Research Newsletter from the Upjohn Institute for Employment Research. I’ll quote from the newsletter here:

Distressed places, which have low employment to-population ratios (employment rates), are a big problem in America. Consider local labor markets: multicounty areas that contain most commuting flows, such as metro areas or rural commuting zones. About two-fifths of all Americans live in local labor markets whose employment rate for prime-age workers (ages 25–54) is more than 5 percentage points below full employment. For neighborhoods, about one-fifth of all Americans live in census tracts whose prime-age
employment rate is more than 5 percentage points below their local labor market’s average. These low employment rates are linked to major social problems: substance abuse, crime, and family stress.

Helping distressed local labor markets requires different policies than helping distressed
neighborhoods. In a distressed local labor market, job creation will raise employment rates, with plausibly half of the jobs going to local nonemployed residents. Local job creation is most cost-effectively accomplished by providing businesses with
“customized services” such as infrastructure, customized job training, and business advice
programs—including manufacturing extension services. Such customized services have less than one-third the cost-per-job-created of business tax incentives.

In contrast, in a distressed neighborhood, more neighborhood jobs will not much help the
neighborhood’s residents, as most neighborhood jobs are not held by residents. Residents of distressed neighborhoods can best be helped by services to increase job access,
including better transportation, job training, and child care.

Bartik offers a fleshed-out proposal in the longer paper. I’d emphasize four points here:

First, it’s important to remember that the gains from getting people back to work are partly the present and future gains to the income of workers. But the broader social gains also include stronger families, a better network of informal job connections, a decline in state-level spending on Medicaid and welfare payments, reduced drug use and crime, and other benefits.

Second, while Bartik’s proposals are admittedly expensive, they are also affordable: “Total annual costs for all states would come to $30 billion annually—$21 billion for local labor markets and $9 billion for neighborhoods. Tis $30 billion cost is affordable, as it is less than 3 percent of overall state taxes. Many states could cover the required costs by replacing their business tax incentives.”

Third, notice that Bartik is suggesting the practicality of state-level initiatives here. States have been called the “laboratories of democracy,” where policy ideas can be tried out and evaluated. These proposals don’t require the yet another argument over federal spending and taxes or the ability to get a 60-vote supermajority in the US Senate. They just require some states (maybe yours?) to give it a try.

Finally, the proposals do require states to focus on distressed areas, not on tax breaks for companies. Bartik describes his proposed policy as a set of block grants that would be spent across a state based on the employment rate. He points to funding for K-12 schools as a parallel: in many states, funds are from the state on a per-student basis and then spent by school districts under broad guidelines. In this case, funds would be allocated based on the employment rate and all areas would receive some payments–but those with especially low employment rates would receive more. He writes:

But state geographic targeting is politically difficult. At the state level, ostensibly targeted programs often allocate most aid to nondistressed places, and initially targeted programs
are then extended statewide. The political problem is partly that most state targeting formulas are arbitrary “price subsidies”: for example, this would include job-creation credits that are higher dollar amounts per job in distressed places. Because the
variation in such subsidies has no obvious relationship with need, it is easy to rationalize extending generous subsidies to favored projects in nondistressed places.

In contrast, the state block grants proposed here use targeting formulas directly tied to the number of persons in each area needing jobs. For each distressed neighborhood or local labor market, the formula calculates how many jobs the place is short of full employment by, and then it funds filling some percentage of that employment rate “gap.”

Such needs-based targeting formulas have been successful for other policy areas in making geographic targeting politically feasible. For example, tying state aid for K–12 schools to the number of students eligible for free or reduced-price lunch has been done by many states, resulting in significant targeting of funds to needier school districts.

The block grants also combine targeting with universalism. Most local labor markets would be eligible for some level of block grant, as would most local governments for neighborhood grants. The targeting is accomplished by making higher per-capita grants to places where more people need jobs. Because “everyone” gets something, the block grants have a stronger political constituency.

For some additional posts about research on place-based policies, see:

• “When Local Governments Subsidize Firms: Some Guidelines” (September 29, 2020)
• “The New Opportunity Zones” (May 27, 2022)
• “Some Economics of Place-Based Policies” (March 9, 2018)
• “Black/White Racial Inequality: A Place-Based Look” (October 5, 2018)